WO2025181007A1

WO2025181007A1 - Method for determining the image sharpness of a particle-optical image, method for the automated adjustment of a particle beam system with regard to its image sharpness, computer program product and particle beam system

Info

Publication number: WO2025181007A1
Application number: PCT/EP2025/054855
Authority: WO
Inventors: Christian Hendrich; Daniel Schwarz; Bernd Schindler; Maximilian Gnedel; Samuel Klamandt
Original assignee: Carl Zeiss Microscopy GmbH; Carl Zeiss Multisem GmbH
Current assignee: Carl Zeiss Microscopy GmbH; Carl Zeiss Multisem GmbH
Priority date: 2024-02-27
Filing date: 2025-02-24
Publication date: 2025-09-04
Anticipated expiration: 2026-08-27
Also published as: TW202601715A; DE102024105423A1

Abstract

A method for determining the image sharpness of a particle-optical image with an improved image sharpness criterion is disclosed. For this purpose, for an image data set, intensity gradients in different directions are evaluated. For the gradient images generated relative to different directions, a respective variance (Vi) per gradient image is calculated, wherein averaging from a plurality of direction-related variance values is carried out internally per gradient image. The minimum variance (Vmin), which represents a measure of the image sharpness, is ascertained from the variance values calculated per gradient image. This image sharpness criterion can also be used for an automated adjustment of imaging particle beam systems.

Description

Method for determining the image sharpness of a particle-optical image, method for the automated adjustment of a particle beam system with regard to its image sharpness, computer program product and particle beam system

Field of the invention

The invention relates to charged particle beam systems comprising detection units for generating particle-optical images. Specifically, the invention relates to a method for determining the image sharpness of a particle-optical image, to a method for the automated adjustment of a particle beam system with regard to its image sharpness, to associated computer program products, and to a particle beam system itself.

Prior art

Particle beam systems comprising particle beam columns, such as for example electron beam columns or ion beam columns, are known from the prior art. One example is a scanning electron microscope, in which a focused electron beam scans a region, to be imaged, of an object to be examined, and secondary electrons or backscattered electrons generated by the incident electron beam on the object are detected depending on the deflection of the focused particle beam, in order to generate or compute an electron-microscopic image of the scanned region of the object.

Basically, the primary particle beam is generated by a beam generator having a particle source, passes through beam-shaping elements such as for example a condenser lens, a stigmator or other beam-shaping elements and is then focused onto the object to be examined by an objective lens. In order to achieve a high resolution of the particle beam column or of the particle beam microscope, the particle beam on the object must be focused as well as possible, that is to say that a region illuminated by the focused particle beam on the surface of the object ("beam spot") ought to be as small and round as possible. For this purpose, the particle beam microscope with its particle-optical components is adjusted with the aim that an image plane into which the particle source is imaged by the optical system coincides with the surface of the object. In the case of an arrangement of the object at a given distance from the objective lens, this can be achieved by changing the focus setting of the particle beam microscope until the beam spot on the surface of the object is as small as possible. By way of example, the focus setting of the particle beam microscope can be changed by changing the excitation of the objective lens and/or by changing the kinetic energy of the particles of the particle beam when passing through the objective lens. Moreover, a region illuminated by the focused particle beam on the surface of the object ought to be as round as possible. For this purpose, it is often necessary to correct imaging aberrations of the particle beam system by means of stigmators. By way of example, electrostatic multipole electrodes or magnetic multipoles can be used for such an astigmatism correction.

After the focus setting of the particle beam microscope has been set in this way, even further measures are necessary, as a rule, to improve the quality of the beam focus on the surface of the object. This includes adjusting the particle beam such that it passes substantially centrally through the objective lens. That is based on the consideration that lens aberrations of a particle-optical lens become ever more noticeable the further away the beam is from the particle-optical axis of the lens when passing through the latter. Since the objective lens typically provides a majority of the refractive power required for imaging the particle source on the object surface, it is advantageous in view of reducing the imaging aberrations involved during this imaging to adjust the beam relative to the objective lens such that it passes through the objective lens as centrally as possible. For this adjustment, the particle beam system or the particle beam column according to the prior art comprises for example one or more deflection devices for displacing the particle beam within the objective lens and which is or are arranged in the beam path between the particle beam source and the objective lens. By changing the excitation of this deflection device or these deflection devices, it is possible to displace the location within a principal plane of the objective lens at which the centre of the particle beam passes through the principal plane.

It is not easy to adjust the particle beam correctly. There are already a few methods in the prior art for this purpose.

By way of example, it is known to use the recording of particle-microscopic images with the particle beam microscope in at least two different focusing settings for the adjustment in order to set the optimum excitation of the deflection device based on an analysis of these recorded images or computed images. That is based on the following consideration: If the particle beam passes centrally through the objective lens and is focused on the surface of the object, the recorded particle- microscopic image is substantially in focus. If the focus setting is slightly changed proceeding from this setting and if a particle-microscopic image is recorded for this altered setting, this image is only slightly less sharp in comparison with the previously recorded particle-microscopic image and is otherwise substantially the same as the latter. However, if the two images recorded with different focus settings are recorded using a particle beam that does not pass through the objective lens centrally, the two images differ not only in respect of image sharpness but also in respect of their position. The change in the focus setting leads to the second image being displaced or offset relative to the first image. Therefore, in the prior art, what is known as a "wobble method" is performed for the purpose of adjusting the particle beam, within the scope of which the focus setting is changed periodically while images are recorded continuously. A user observes the recorded images, which move back and forth in the case of an improperly adjusted beam, and changes the excitation of the deflection device or deflection devices until the resultant images are all essentially stationary. This is a manual process that requires a certain amount of experience and is therefore also time-consuming.

In addition to the manual wobble method described above, automated methods are also known, which record a multiplicity of images in the case of pairwise different settings of the focus setting and the excitation of the deflection device. An optimum setting of the excitation of the deflection device is computed and set on the basis of an analysis of the multiplicity of recorded images. Then, the desired high-quality particle-microscopic images of the object are recorded using this setting. By way of example, such methods are known from US 6 864 493 B2, US 2012 I 0 138 793 A1 , US 8 766 183 B2 and US 7 705 300 B2.

It holds true in principle that for particle beam systems or particle imaging apparatuses, the image sharpness achievable therewith is a major factor. An image that is as sharp as possible is desired. One problem here, however, is the occurrence of many different image aberrations, some of which also cannot be corrected independently of one another. It is possible that a user of a particle imaging apparatus or imaging particle beam system can set the image sharpness only locally and not globally. Therefore, one approach is to try to measure all image aberrations and then correct them accordingly. However, this measurement of all image aberrations is very difficult and also very timeconsuming. There is therefore a desire for a faster, simpler and more reliable adjustment method.

It is known from US 9,916,964 B1 that a sharpness measure can be derived from the absolute values of intensity gradients. If the absolute values of intensity gradients within an image vary greatly, then an image is regarded as sharper or is also actually sharper from a user’s viewpoint. The variation of absolute values of intensity gradients can thus be used as a sharpness measure. What is disadvantageous about this sharpness measure, however, is that in the course of a corresponding optimization to this sharpness measure, it is not always and not automatically possible to determine a global maximum of an image sharpness. Whether this succeeds is e.g. greatly dependent on how good the presettings of focus and stigmation are in a particle beam system. Otherwise, only a local maximum can be determined, which in an unfavorable case may correspond to the setting of a line focus. This ought ideally to be avoided.

Furthermore, US 9,916,964 B1 discloses a method for operating a particle microscope, wherein a sharpness criterion is used for the automatic adjustment of focus and stigmation. Said sharpness criterion is based on an analysis of the different orientations of an intensity gradient at a multiplicity of image positions in a, possibly smoothed, particle-optical image. As an alternative to the analysis of the gradient image, a Fourier-transformed image is analysed with regard to a direction-dependent property and the image sharpness is derived therefrom.

US 9,916,964 B1 specifies several examples for the definition of a sharpness criterion. By way of example, a particle-optical image is analysed with regard to both the directions, in one of which the most intensity gradients are oriented and in the other of which the fewest intensity gradients are oriented. The sum of the absolute values of the intensity gradients in one of the directions or in both directions can be used as a (possibly inverse) sharpness measure.

In computational terms for this purpose, according to US 9,916,964 B1 , a gradient image is determined by means of the Sobel operator. The Sobel operator is a simple edge detection filter which is often applied in image processing, where it is used with the aid of convolution as an algorithm. The latter calculates the first derivative of the pixel brightness values, in conjunction with simultaneous smoothing orthogonally to the derivation direction. An evaluation of the gradient image thus generated takes place by way of a polar diagram in US 9,916,964 B1. In the polar diagram, specific angular portions correspond to a corresponding orientation of intensity gradients in the particle-optical image; data binning in this regard takes place. The radius of a data point in the polar diagram is determined according to the average of the (absolute values) of the intensity gradients in the respective angular portion. An ellipse is fitted to the data points thus obtained, the length and orientation of the semi-major and semi-minor axes of the ellipse being ascertained. The two distinguished directions having firstly the most intensity gradients and secondly the fewest intensity gradients are thus determined in this way. What is considered to be optimum image sharpness is for example if the fitted ellipse assumes the special shape of the circle. An evaluation with a polar diagram may entirely analogously also take place on the basis of a Fourier-transformed image.

What is disadvantageous about the method for determining image sharpness known from US 9,916,964 B1 is the fact that the method can be applied really well only for samples or objects with sufficiently high contrast or edge contrast, i.e. in particular given the existence of edges in the sample in many different directions. That is not the case for semiconductor samples or lithography masks, for example. Instead, for semiconductor samples or lithography masks, there are often only two or a few distinguished directions in which edges exist.

The generation and evaluation of a gradient image generated using the Sobel operator as described in US 9,916,964 B1 also has the disadvantage that the Sobel operator does not have perfect rotational symmetry. It is probably for that reason that US 9,916,964 B1 proposes optionally carrying out smoothing of the recorded image or of the particle-optical image before the gradient image is generated. It is furthermore noted that according to US 9,916,964 B1 exactly one gradient image is analyzed for the sharpness determination. Moreover, the generation and evaluation of a Fourier-transformed image/FFT image as described in US 9,916,964 B1 is comparatively time-consuming in respect of computation time.

WO 2022/269925 A1 discloses a charged particle beam device that makes it possible to perform a high-speed autofocus operation which reduces damage to a sample by eliminating the need for a focus sweep operation or reducing the number of focus sweep operations. A charged particle beam device comprises a charged particle beam optical system that converges/polarizes a charged particle beam and irradiates a sample with the charged particle beam. An image generation processing unit generates an image of the sample by detecting the charged particle beam. A storage unit stores a relation between the focus position of the charged particle beam by the charged particle beam optical system and a feature of the image of the sample. A comparison operation unit determines the shift amount and the shift direction of the focus position of the charged particle beam by comparing information obtained from the image generated by the image generation processing unit and information in the storage unit. A control unit controls the charged particle beam optical system according to a comparison result of the comparison operation unit.

Specifically, WO 2022/269925 A1 makes use of a sharpness distribution of images within an imaging region (FOV). By detecting a direction and degree of bending of the sharpness distribution, it is possible to determine a shift amount and a shift direction of a current focus position and thus to improve focussing. Similarly, an astigmatism can be corrected. WO 2022/269925 A1 does not disclose any details about a sharpness criterion applied and is only suited for a fine adjustment of the charged particle beam device.

US 2005/0072920 A1 discloses algorithms for an automated adjustment of focus and stigmation in single beam electron microscopes. One of the difficulties addressed is that a distinction between imaging errors due to a defocus on the one hand and an astigmatism on the other is difficult to make. Particle-optical images with various different focus and astigmatism settings are recorded and evaluated according to an image sharpness criterion. The general calculation of image sharpness coefficients is described using the Sobel operator as an edge detection filter. A direction-dependent image sharpness coefficient can be determined in this case. US 2005/0072920 A1 teaches to create a graph showing determined image sharpness coefficients as a function of an astigmatism correction current setting. The resulting curve type is analyzed regarding the number of maxima to be found in it. The number of maxima allows a conclusion to be drawn as to whether only a defocus is present or whether astigmatism is also present as an imaging error. Description of the invention

Therefore, the object of the present invention is to specify an improved method for determining the image sharpness of a particle-optical image. The method is intended to work quickly and robustly and also to be usable for particle-optical images of samples or objects with little edge contrast. It is intended in particular also to be usable for particle-optical images of semiconductor samples.

A further object of the invention is to make the improved method for determining the image sharpness or the associated image sharpness criterion usable for an automated adjustment of particle beam systems or particle imaging apparatuses.

The object is achieved by the subject matter of the independent patent claims. Advantageous embodiments of the invention are evident from the dependent patent claims.

The present patent application claims the priority of German patent application No. 10 2024 105 423.9 filed on 27 February 2025, the disclosure of which in the full scope thereof is incorporated in the present patent application by reference.

In accordance with a first aspect of the invention, the latter relates to a method for determining the image sharpness of a particle-optical image, wherein the method comprises the following steps: (a1) providing an image data set of the particle-optical image, wherein the image data set is generated or has been generated by means of a particle beam system which operates with charged particle beams;

(a2) generating two gradient data sets on the basis of the image data set, wherein the first gradient data set describes an intensity gradient of the image data set or of the processed image data set in a first direction and wherein the second gradient data set describes the intensity gradient of the image data set or of the processed image data set in a second direction, wherein the first direction is linearly independent of the second direction and wherein the first direction and the second direction define a reference coordinate system;

(a3) for a plurality N of different rotation angles cpi with i=1..N:

(a3.1) defining a calculation coordinate system Ki rotated by the rotation angle (pi relative to the reference coordinate system;

(a3.2) calculating a gradient data set GDi in the calculation coordinate system Ki on the basis of the two gradient data sets in the reference coordinate system;

(a3.3) calculating a variance Vi on the basis of the values of the gradient data set GDi, wherein the calculation of the variance Vi comprises averaging from a plurality of direction-related variance values;

(a4) determining the minimum variance Vmin from the N values of the variances Vi; and (a5) determining the image sharpness on the basis of the minimum variance Vmin.

In the context of this application, a particle-optical image is understood to mean an image which is generated by means of the detection of particle radiation. A particle detector is used to detect the particle radiation, and it is possible to combine a particle detector with an optical detector. The detected particles can be for example electrons or other charged particles. It is possible for example to detect secondary electrons or backscattered electrons or mirror electrons or mirror ions for the generation of the particle-optical image. The particle-optical images are images in which the intensity of the detected particle radiation is represented as a function of an image position for a pixel. The image sharpness in such an image corresponds to the contrast of the image. An image sharpness determination is thus a contrast determination, in principle. Sharp edges in an image correspond to a high image sharpness. The sharpness of edges can be determined quite generally by way of a gradient in the intensity of the image.

According to the invention, only an image data set of the particle-optical image is provided. It is not necessary for the particle-optical image also to be graphically represented. It is possible for the particle-optical image not to be generated until in the course of the method for determining the image sharpness, but it is likewise possible for the particle-optical image to already exist.

In step (a2), two gradient data sets are generated on the basis of the image data set of the particle- optical image. In this case, the two gradient data sets correspond to a gradient vector image. In this case, the first gradient data set describes an intensity gradient in a first direction and the second gradient data set describes the intensity gradient in a second direction. Illustratively speaking, the two gradient data sets can correspond to two matrices. The first direction and the second direction are linearly independent of one another and the first direction and the second direction define a reference coordinate system. The reference coordinate system can be a Cartesian reference coordinate system, the axes of which can be denoted by x and y as usual. However, this is not mandatory. In principle, in this method step (a2), a respective intensity gradient is determined for each pixel of the image data set or else for a selection of pixels in the image data set. The gradient itself is a vector which here is decomposed computationally into two portions that are linearly independent of one another. This decomposition generates the two gradient data sets, each gradient data set only including absolute values of the vector. The two gradient data sets are generated on the basis of the image data set. That means that both the original image data set of the generated image and a possibly further processed image can form the basis for the generation of the two gradient data sets. The two gradient data sets can be generated on the basis of all the data of the image data set or only a selection of data of the image data set. The next method step (a3) is carried out for a plurality N of different rotation angles (pi with i= 1 ... N: Method step (a3.1) involves defining a calculation coordinate system Ki rotated by the rotation angle (pi relative to the reference coordinate system. In this calculation coordinate system Ki, in step (a3.2), a gradient data set GDi is calculated on the basis of the two gradient data sets in the reference coordinate system. Illustratively speaking, this involves determining the magnitude of the absolute value of the gradient in the direction of the rotation angle (pi. In this case, the portion of the gradient in the direction of the rotation angle (pi can be obtained by projection of the gradient in its entirety, which is included in the two gradient data sets, onto the for example x-direction of the calculation coordinate system Ki. The gradient data set GDi can thus correspond to entries in a matrix.

Method step (a3.3) involves calculating a variance Vi on the basis of the values of the gradient data set GDi. One variance or one number per rotation angle (pi is thus calculated. In this case, however, this single number or variance Vi comprises averaging from a plurality of direction-related variance values of the gradient data set GDi: It is possible for example to determine variance values firstly by row or per row in the gradient data set GDi. Each row describes the same direction in this case. If the structure of the gradient data set GDi is conceived of as a matrix, then the variance is thus determined for each row of the matrix. The variance values obtained row by row are then averaged and the variance Vi is calculated. The averaging can involve for example an arithmetic mean or geometric mean or some other average value. It is also possible to determine a median value. Instead of a row-by-row calculation of variance values, it is also possible to calculate the variance values column by column. Each column in the gradient data set also relates to a fixed direction in the calculation coordinate system Ki. In the programming implementation, however, the row-by-row determination is easier to implement.

The described method steps (a3.1), (a3.2) and (a3.3) are carried out a number of times. Here the rotation angle (pi can in each case be increased incrementally by the same value. However, it is also conceivable for different rotation angles adjacent to one another in the set of rotation angles for which the calculation is carried out not to be spaced uniformly from one another. However, incrementally increasing the rotation angle (pi is easiest in terms of programming.

Method step (a4) involves determining the minimum variance Vmin from the N values of the variances Vi. In this case, advantageously, two variances of the two gradient data sets in the reference coordinate system are also included in the set of variances from which the minimum variance is determined. In other words, a rotation angle (pi can also be 0° and e.g. 90° (in the case of a Cartesian reference coordinate system). Method step (a5) involves determining the image sharpness on the basis of the minimum variance Vmin. This minimum variance is thus a measure of the image sharpness; the image sharpness can also be defined exactly as the minimum variance Vmin. Using the minimum variance Vmin as a measure of the image sharpness has the advantage of ruling out in practice particle-optical images with a line focus as best or sharpest images. This can be clarified illustratively as follows: If a particle-optical image or an associated image data set has a low variance in a first direction corresponding to the rotation angle cp1 , but has a high variance in a second direction corresponding to the rotation angle cp2, then the image more likely fares badly with regard to the image sharpness criterion. By contrast, a particle-optical image which has an average variance Vi in many directions (pi more likely fares well in the case of the sharpness criterion described. An ideal image sharpness is most likely present if the average sharpness is more likely the same over all spatial directions. The variance is then very small and ideally minimal.

The method according to the invention for determining the image sharpness of a particle-optical image is also superior to the Fourier approach known from US 9,916,964 B1 : This is because the sharpness criterion based on a Fourier image as described therein is really good only if the particle- optical image also actually has edges in many different directions. By contrast, the method according to the invention for determining the image sharpness of a particle-optical image also functions very well without this limitation. Illustratively speaking, that is due to the fact that as a result of the rotation of the calculation coordinate system by a plurality of rotation angles (pi, edges which exist in one distinguished direction are considered analytically from a plurality of directions. For this reason, the method according to the invention is also suitable for determining the image sharpness of a particle- optical image which is recorded or has been recorded as an image of a semiconductor sample and/ or a lithography mask. Moreover, an FFT is also more time-consuming than the method according to the invention in terms of computation time.

In accordance with one preferred embodiment of the method, the two gradient data sets in the reference coordinate system correspond to two gradient images. Preferably, the gradient data set GDi in the calculation coordinate system Ki corresponds to a gradient image. This gradient image can be understood as a projection of the gradient vector image into the calculation coordinate system Ki.

In accordance with one preferred embodiment of the invention, the plurality N of rotation angles (pi are generated incrementally by means of the same increment. The value of the increment can be an empirical value. The smaller the increment, the higher the computational complexity of the method. It has been found in practice that the value of an increment of 11.25° is often already sufficient for the determination of the image sharpness according to the image sharpness criterion according to the invention, but the increment can also be chosen to be smaller or larger. In accordance with one preferred embodiment of the invention, the first direction of the reference coordinate system and the second direction of the reference coordinate system are orthogonal to one another. Accordingly, the calculation coordinate system Ki rotated by the angle (pi is also an orthogonal coordinate system. This affords advantages from a computational standpoint.

In accordance with one preferred embodiment of the invention, it holds true that for a maximum rotation angle (pimax < 90°. From an algorithmic viewpoint, it may thus be sufficient to carry out a quarter rotation of the calculation coordinate system, that is to say that a rotation for example over a range of 0° to 180° is not required here. Illustratively speaking, this is due to the fact that the rotation of the coordinate system involves a cross being rotated rather than only a single axis being rotated. The rotation of a cross by 90° can be treated mathematically like the rotation of an axis by 180°, just that the corresponding x- and y-values may need to be firstly divided and then recombined algorithmically.

In accordance with one preferred embodiment of the invention, the method furthermore comprises the following step:

(a6) denoising the image data set substantially without edge smoothing, wherein step (a6) is carried out between method steps (a1) and (a2). Edge smoothing is intended to be avoided in order not to reduce the edge contrast that is important for the calculation of the image sharpness.

In accordance with one preferred embodiment of the invention, denoising the image data set comprises applying a median filtering. In comparison with box filters, median filters have the advantage that individual pixels are replaced, without this causing edge smoothing. In the case of a median filter, the greyscale values of the pixels in a defined vicinity of a pixel are collected and sorted according to size. The median greyscale value of this sorted list is then selected; this value replaces the greyscale value of the current pixel. Unlike a median filter, an average filter is more likely not suitable for denoising the image data set, since it results in edge smoothing.

In accordance with one preferred embodiment of the invention, denoising the image data set comprises binning with an optimized kernel size. Binning involves combining neighbouring data of an image data set, the values of the data being added. Individual outliers in the data set are given lower weighting as a result and a signal-to-noise ratio is improved, such that noise is statistically distributed in the data. In this embodiment of the method according to the invention, determining an optimized kernel size is important. If the kernel size is too large, the resolution of the particle-optical image is reduced too much. If the kernel size is too small, the distribution of noise among the individual bins is not distributed statistically enough. A halving of the resolution and thus a good distribution of noise can already be achieved by way of a kernel size of 2x2; therefore, a kernel size of 2x2 is a preferred kernel size. However, the kernel size can also be larger. In accordance with one preferred embodiment of the invention, denoising the image data set comprises denoising by means of a neural network. This method can be applied even to images having unknown contents. Whereas older routines for denoising images by means of neural networks, during training, relied on providing noisy and non-noisy images of the same object, in the meantime it has become possible to carry out even denoising of totally unknown images by means of neural networks.

It is generally the case that denoising the image data set allows the use of relatively noisy images when determining an image sharpness. Noisy images can be recorded very quickly, which is an enormous advantage particularly when using the method for determining the image sharpness in the course of the automated adjustment of a particle beam system, since in this case a multiplicity of particle-optical images have to be generated by means of the particle beam system. Overall, therefore, an automated adjustment of a particle beam system can be made quicker as a result.

In accordance with a preferred embodiment, a Sobel operator is not used for generating the two gradient data sets. This means that the Sobel operator is neither used for generating the first gradient data set, nor the second gradient data set.

In accordance with one preferred embodiment of the invention, the image data set of the particle- optical image describes a semiconductor sample and/ or a lithography mask. As already explained above, the image of a semiconductor sample or a lithography mask, respectively, normally has only few edges, which moreover are often present only in a distinguished direction or in very few directions. The method according to the invention for determining the image sharpness is however also suitable and very powerful for particle-optical images of this type.

In accordance with one preferred embodiment of the invention, calculating the gradient data set GDi in the calculation coordinate system Ki involves carrying out a projection of the respective gradient of the image data set or of the processed image data set onto both axes of the calculation coordinate system. The projection of the gradient onto both axes has computational advantages and provides for an increase in speed when calculating the sharpness measure. For this reason, it is also possible to limit the maximum rotation angle cpimax to a value of (pi_max< 90°. Values for rotation angles (pi from 90° to 180° are automatically already concomitantly determined by the projection onto the second axis; rotation angles (pi in the range of 180° to 360° likewise need not be explicitly determined since, apart from the sign, they are likewise already known in principle.

In accordance with a further aspect of the invention, the latter relates to a method for the automated adjustment of a particle beam system using the image sharpness criterion described above. The method according to the invention for the automated adjustment of a particle beam system comprises the following steps:

(b1) providing an imaging particle beam system, in particular a particle beam microscope, which operates with charged particles;

(b2) selecting a first parameter P1 k, which influences the image sharpness of images recorded by means of the particle beam system and which is adjustable by means of a first actuating element of the particle beam system;

(b3) for a plurality K of values of the first parameter P1 k with k=1..K:

(b3.1) generating an image data set by means of the particle beam system given the current value of the first parameter P1 k,

(b3.2) determining the image sharpness of the image data set by carrying out the method for determining the image sharpness of a particle-optical image as described above in a number of embodiments;

(b3.3) assigning the image sharpness determined in step (b3.2) to the current value of the first parameter P1 k;

(b4) analysing the image sharpnesses determined in step (b3.3) as a function of the values of the first parameter P1 k;

(b5) determining a maximum value of the image sharpness and the associated value of the first parameter P1opt on the basis of the analysis according to (b4); and

(b6) setting the particle beam system to the value of the first parameter P1opt by means of the first actuating element.

The imaging particle beam system can be of any desired type, in principle. By way of example, a particle microscope can be involved. The imaging particle beam system can be e.g. a scanning electron microscope SEM, a transmission electron microscope TEM, a STEM, a SEM-STEM, a dual beam system or a multi-beam particle microscope. The method according to the invention for the automated adjustment of a particle beam system can thus be applied very broadly.

An imaging particle beam system always also comprises a detection unit for detecting charged particles. This detection unit can be embodied in various ways; the type of detection unit or detectors can be chosen freely, in principle.

The method for the automated adjustment of a particle beam system involves making a plurality of recordings, wherein the first parameter P1k is varied. This first parameter P1 k influences the image sharpness of images recorded by means of the particle beam system and is adjustable by means of a first actuating element associated therewith in the particle beam system. From the images recorded as a function of the first parameter P1k, the image with the greatest image sharpness is determined and the particle beam system is set to the associated value of the first parameter P1opt. This setting of the particle beam system with regard to the first parameter P1 k is independent of other parameters Pik which likewise influence the image sharpness of images recorded by means of the particle beam system. This independence of the influencing factors or parameters Pik is a special feature of the method according to the invention. In principle, it is possible for example to drive a stigmator or deflector excitation or a lens coil current within its respective setting range and, for the particle-optical images recorded during this driving, to ascertain the image sharpness according to the image sharpness criterion which has been described in accordance with the first aspect of the invention. In this case, the stigmator currents, deflector currents or lens coil currents discussed are just one example of the parameters Pik which influence the image sharpness of images recorded by means of the particle beam system. In this case, it is often known that one of the parameters, for example a stigmator excitation, principally describes or influences the stigmation of a particle beam. However, it is also possible for other elements of a particle beam system likewise to have an influence on the stigmation.

In accordance with one preferred embodiment of the invention, determining the maximum value of the image sharpness and the associated value of the first parameter P1opt involves carrying out an interpolation of the image sharpness between values of the first parameter P1 k that are set by means of the first actuating parameter, wherein the optimum value of the first parameter P1opt is determined on the basis of this interpolation. This interpolation takes account of the fact that the step size during a variation of the first parameter P1k is not arbitrarily small. In this respect, it may happen that the optimum value of the first parameter P1opt does not lie exactly at a measurement point. Interpolating constitutes one solution approach here.

In accordance with one preferred embodiment of the invention, a spline interpolation is applied as interpolation method. It has been found that the spline interpolation yields particularly good results. An interpolation by means of fitting to a parabola yields poorer results compared with the spline interpolation.

In accordance with one preferred embodiment of the method according to the invention, the first parameter P1 k influences a working distance WD between an objective lens and a sample surface. The first parameter P1k thus influences the z-position of the focal plane into which the particle beam is imaged by means of the objective lens. This can be done by means of a corresponding variation of the control of the objective lens, but it can also be done in some other way, for example by controlling an additional electrode just in front of a sample or an object, by applying an opposing field to the object, by providing a booster voltage by means of an electrostatic lens or else quite generally by means of any adjustment variable with a direct influence on the position or z-position of the focal plane. The first parameter P1k can alternatively influence a stigmation of a particle beam in a first direction x, or the first parameter P1k can influence a stigmation of a particle beam in a second direction y, which is linearly independent of the first direction x and in particular orthogonal to the first direction x.

This can be achieved for example in each case by means of an electrostatic stigmation unit or by means of a magnetic stigmation unit, the present control of which can correspond to the value of the first parameter P1 k.

Alternatively, the first parameter P1k can influence a deflection of a particle beam towards a lens centre, in particular an objective lens centre. The refractive power of an objective lens typically contributes a large portion of the refractive power for the imaging of the particle source onto the object surface, such that in particular imaging aberrations of an objective lens which arise as a result of the particle beam not passing through the objective lens centrally should be reduced as far as possible.

However, the first parameter P1k can also be selected differently from the way described above in a number of examples. The method according to the invention is not limited here, in principle.

In accordance with one preferred embodiment of the method, method steps (b2) to (b6) are repeated for a second parameter P2k, wherein the second parameter P2k influences the image sharpness of images recorded by means of the particle beam system and wherein the second parameter P2k is adjustable by means of a second actuating element of the particle beam system. In principle, what has already been stated above in connection with the first parameter P1k holds true for the type of the second parameter P2k.

In accordance with one preferred embodiment of the method, method steps (b2) to (b6) are repeated for a third parameter P3k and/or for one further or a plurality of further parameter(s) Pik, wherein the third parameter P3k influences the image sharpness of images recorded by means of the particle beam system and wherein the third parameter P3k is adjustable by means of a third actuating element of the particle beam system, and/or wherein the one further parameter or the plurality of further parameters Pik influence(s) the image sharpness of images recorded by means of the particle beam system and is or are adjustable by means of one further actuating element or by means of a plurality of further actuating elements of the particle beam system. In principle, what has already been explained with regard to the first parameter P1 k also holds true for the nature of the third parameter P3k and for the further parameter or the plurality of further parameters Pik. In accordance with one preferred embodiment of the invention, the first parameter P1 k, the second parameter P2k and the third parameter P3k each describe exactly one of the following features:

- a working distance WD between an objective lens and a sample surface,

- a stigmation in a first direction x, and

- a stigmation in a second direction y, which is linearly independent of the first direction x and in particular is orthogonal to the first direction x.

In this embodiment of the invention, therefore, by means of three parameters P1 k, P2k and P3k, it is possible to attain an optimum image sharpness with regard to the working distance WD and with regard to the stigmation in two directions x, y which are linearly independent of one another. These are the most relevant parameters for the image sharpness setting for many particle beam systems.

In accordance with one preferred embodiment of the invention, one of the parameters Pik which influence the image sharpness of images recorded by means of the particle beam system describes a working distance WD between an objective lens of the particle beam system and a sample surface and the parameter Pik is set to the value Piopt. The method for the super-fine setting of the parameter Pik or its value Piopt can furthermore comprise the following steps:

(b7) negatively detuning the value of the parameter Piopt by an absolute value 6 to a value Pi D 1 ; (b8) carrying out method steps (b3.1), (b3.2) and (b3.3) for the value of the parameter PiD1 ;

(b9) positively detuning the value of the parameter Piopt by an absolute value 6 to a value PiD2; (b10) carrying out method steps (b3.1), (b3.2) and (b3.3) for the value of the parameter PiD2;

(b11) comparing the image sharpnesses respectively determined in steps (b8) and (b10) and ascertaining an inequality of the image sharpnesses respectively determined;

(b 12) replacing the original value Piopt of the parameter by an improved optimum value Piopt_new on the basis of the inequality;

(b13) repeating, in particular repeating a number of times, method steps (b7) to (b12) with the improved optimum value Piopt_new as value of the parameter Pik until a termination criterion for a sufficient equality of the image sharpnesses is satisfied; and

(b 14) setting the particle beam system to the improved optimum value of the parameter Piopt_new by means of the first actuating element. The associated actuating element for the parameter Pik is used for this purpose.

The basic concept of this embodiment variant of the invention is that in the case of an actually optimum setting of the parameter Pik to the actually optimum value Piopt, symmetrically detuning this value will also bring about a symmetrical or identical alteration of the associated image sharpness values. It is then and only then that the preset extremum for the parameter to the value Piopt is also actually optimal. The described method steps for the super-fine setting of a working distance WD or of the focus are particularly helpful in an automated electrical adjustment in which only small changes in the image sharpness take place around the true optimum of the sharpness setting. This may be the case in particular in adjustment processes on the basis of samples or objects which have particularly few edges and a particularly small contrast variation. By way of example, these are in turn the semiconductor samples already mentioned a number of times. The algorithm for super-fine setting then also cannot be replaced by a finer “coarse setting”, i.e. by smaller-stepped variation of the values of the parameter Pik.

In accordance with one preferred embodiment of the invention, the actuating element used in each case to set the parameter Pik during the described super-fine setting varies the working distance WD without using a particle-optical component which generates a magnetic field. This contributes to the accuracy of the method and also to an increase in the speed of the method, since hysteresis effects are avoided.

In accordance with one preferred embodiment of the invention, the actuating element varies the working distance WD electrostatically during the super-fine setting. By way of example, there are particle beam systems comprising an objective lens or an objective lens system which have a magnetic lens portion and an electrostatic lens portion. Here the working distance WD, without adjustment of the magnetic lens portion, can then be varied just by way of an adjustment of the electrostatic lens portion. Alternative electrostatic setting possibilities are for example the setting of a booster voltage and thus of an electrostatic lens. Alternatively, an opposing field of electrostatic nature can be applied to the sample or the object. It is likewise possible to provide an additional electrode just in front of the sample or the object. Generally, any adjustment variable with a direct influence on the z-position of the focal plane is conceivable as manipulated variable or as actuating element. Incidentally, in connection with this patent application, the terms sample and object are each used synonymously.

As already described, various detection units can be used for the automated adjustment of the imaging particle beam system. The method is not tied to a specific type for a detection unit. However, in principle it holds true, of course, that the detector and the properties thereof influence the image sharpness of the particle-optical images determined by means of the detector or the detection unit. It is therefore advantageous for the method according to the invention for the automated electrical adjustment of an imaging particle beam system to comprise optimizing a detector setting of the particle beam system before adjusting the particle beam system with regard to the image sharpness. Moreover, it is possible to optimize a detector setting once again also during the adjustment steps for adjusting the particle beam system with regard to the image sharpness.

In accordance with one preferred embodiment of the invention, optimizing a detector setting involves recording a particle-optical test image, wherein the optimizing involves setting the brightness and the contrast of a detection unit. In this case, the optimizing involves preferably using the following two target stipulations:

- minimizing the brightness and thus the offset value of the detection unit when 0% contrast is present, and

- no cutting off of intensities in the entire contrast range, wherein the contrast is defined from 0% contrast to 100% contrast including the interval limits.

When stipulating such optimization targets, it is possible to use the detection unit with its respectively specific special characteristics with regard to brightness and contrast optimally over the entire range in which it can yield data. Moreover, when setting the detection unit according to the two target stipulations mentioned above, what can be achieved is that quantitative measurements can also be performed by means of the detection unit. This is advantageous for image processing applications, for example. Details concerning the optimization of the detection unit will be discussed even more specifically further below in the section relating to the figures.

In accordance with a third aspect of the invention, the latter relates to a computer program product comprising a program code for carrying out the method for determining the image sharpness of a particle-optical image such as has been described above in a plurality of embodiments. In this case, the program code can be programmed in any programming language.

In accordance with one preferred embodiment of the invention, the latter relates to a computer program product which comprises a program code which is loadable into a controller of a particle beam system and, when the program code is executed, controls a particle beam system such that a method for the automated adjustment of a particle beam system as described above in a plurality of embodiment variants is carried out. The particle beam system is of course an imaging particle beam system.

In accordance with a further aspect of the invention, the latter relates to a particle beam system, configured for carrying out the method for the automated adjustment of a particle beam system and comprising a controller into which a computer program product suitable for this purpose is loaded.

In accordance with a further aspect of the invention, the latter relates to a particle beam system comprising the following: a particle source for generating a particle beam comprising charged particles; at least one focusing lens through which the particle beam passes and which comprises an objective lens which focuses the particle beam at a working distance WD from the objective lens; a first stigmator, through which the particle beam passes, for the stigmation of the particle beam in a first direction x; a second stigmator, through which the particle beam passes, for the stigmation of the particle beam in a second direction y, which is linearly independent of, and in particular orthogonal to, the first direction x; an object stage or object holder configured to hold the object at a distance from the objective lens; a detection unit for detecting interaction particles emanating from the object; and a controller for controlling the particle beam system, wherein the controller is configured to control the at least one focusing lens, the first stigmator and the second stigmator and also the detection unit and to generate an image data set, and wherein the controller is configured to carry out the method for the automated adjustment of a particle beam system.

In this case, the first stigmator and the second stigmator can be combined with one another in terms of component engineering. By way of example, a stigmation unit can comprise a multipole electrode of electrostatic or magnetic nature. Stigmation in two mutually independent directions x, y and focus setting are normally the most important parameters for the optimization of the image sharpness of particle-optical images. They are therefore mentioned explicitly in this embodiment variant. However, this does not, of course, exclude the fact that other particle-optical elements can likewise have an important influence on the image sharpness.

The controller is configured for controlling the imaging particle beam system. The controller itself can in this case be of integral or multipartite and in particular modular construction.

In accordance with one preferred embodiment of the invention, the particle beam system furthermore comprises a deflector unit configured to deflect the particle beam towards the objective lens centre, wherein the controller is configured to control the deflector unit. Such a deflector unit is often also referred to as “wobble” unit.

The particle beam system comprises an object stage or an object holder. In this case, the term object holder should be understood more generally than the term object stage. An object holder can likewise be configured to hold the object at a distance from the objective lens. The object can in particular also be a so-called small net, which can comprise a plurality of test structures. By means of the controller of the particle beam system, a particle beam, upon passing through an opening in the small net, can then be directed at the small net itself with its test structures, instead of at the “normal sample”. A particle beam system-inherent qualification and adjustment of the particle beam system becomes possible as a result. Such particle beam systems with small nets are so-called mask repair systems, for example. Examples in this respect will be explained in even more specific detail further below in the section relating to the figures. In accordance with one preferred embodiment of the invention, the particle beam system is a system from the following list of particle beam systems: a particle microscope, a SEM, a TEM, a STEM, a SEM-STEM, a dual beam system, a multi-beam particle microscope, a mask repair system. In this case, this list should not be understood as limiting for the invention.

The invention will be understood even better with reference to the accompanying figures, in which:

Figure 1 : schematically shows an imaging particle beam system on the basis of the example of a particle microscope;

Figure 2: schematically shows method steps of a method according to the invention for determining the image sharpness of a particle-optical image;

Figure 3: shows data of an image sharpness determined according to the invention as a function of one parameter describing a stigmation of the particle beam, and also associated particle-optical images;

Figure 4: shows data of an image sharpness determined according to the invention as a function of two parameters each describing a stigmation of the particle beam, and also two associated particle-optical images of a semiconductor sample;

Figure 5: schematically shows method steps of a method for determining the image sharpness of a particle-optical image;

Figure 6: schematically shows method steps of a method for the automated adjustment of an imaging particle beam system;

Figure 7: shows data of an image sharpness as a function of a working distance WD and also the interpolation of the data;

Figure 8: illustrates a principle for a super-fine setting of a working distance WD and thus a focus setting;

Figure 9: schematically shows method steps of a method for the super-fine setting of a working distance WD and thus a focus setting;

Figure 10: schematically illustrates method steps of a method for the automated adjustment of an imaging particle beam system during variation of one parameter Pik;

Figure 11 : schematically shows method steps for the automated setting of a detector offset;

Figure 12: schematically shows an iteration starting setting and an iteration result for the method described in Figure 11 ;

Figure 13: schematically shows method steps for the automated setting of a detector amplification;

Figure 14: schematically shows an iteration starting setting and an iteration result for the method described in Figure 13; Figure 15: schematically illustrates method steps of an iterative method for the automated adjustment of an imaging particle beam system during variation of a plurality of parameters Pik and with fixed magnification;

Figure 16: schematically illustrates method steps of a method for the automated adjustment of an imaging particle beam system during variation of a plurality of parameters Pik, which is suitable for a greatly misadjusted particle beam system;

Figure 17: schematically shows a particle beam system according to the invention comprising a double condenser;

Figure 18: schematically shows a particle beam system according to the invention comprising a single condenser;

Figure 19: schematically shows a particle beam system according to the invention on the basis of the example of a device comprising a particle beam column for analysing and/or processing a sample;

Figure 20: schematically shows a shielding element or a so-called small net which can be used as an object for a system-inherent setting of an image sharpness in the case of the particle beam system shown in Figure 19;

Figure 21 : schematically shows a shielding element with a structuring in the region of the net structure; and

Figure 22: schematically shows examples of structuring of the net structure.

Figure 1 schematically shows an imaging particle beam system 100 on the basis of the example of a particle microscope in the form of a scanning electron microscope. The scanning electron microscope 100 comprises a particle source 1 , which generates an electron beam 122, wherein the electron beam 122 passes through a condenser lens 4, an x-y-stigmator 15, a beam deflector 50 and an objective lens 11 , such that the electron beam 122 is focused onto the surface of an object or a sample 13, the sample or the object 13 being held by a sample stage 14. The working distance WD between the lower end of the objective lens 11 and the surface of the sample 13 is likewise depicted.

In the example shown, the condenser lens 4 is a magnetic condenser lens comprising a pole shoe 21 and a coil 23, the excitation of which is effected by means of the controller 20.

The x-y-stigmator is an electrostatic stigmator comprising a plurality of eight electrodes, for example, which are arranged around the electron beam 122, the electrodes being controlled or excited by means of the controller 20. In the example shown, four of these electrodes form an x-stigmator and four other electrodes of this total of eight electrodes form a y-stigmator. Both the x-stigmator and the y-stigmator can generate a quadrupole field by means of their associated four electrodes. Alternatively, the x-y-stigmator can comprise eight coils for generating a magnetic field, each of which is controlled by means of the controller 20 in order to generate a quadrupole field in each case for the x-stigmator or the y-stigmator. The x-y-stigmator thus provides the functions of both the x- stigmator and a y-stigmator combined in one component, in order to influence or to set or to correct an astigmatism of the particle beam 122.

The beam deflector 50 can be a magnetic or an electrostatic beam deflector, which is in turn controlled by means of the controller 20 in order to scan the incidence location of the particle beam 122 across the surface of the object 13. In the example shown, an electron detector 10 is provided in order to detect secondary electrons and backscattered electrons emanating from the incidence point of the electron beam 122 on the object surface 13. The controller 20 is configured to assign measured electron intensities measured by means of the electron detector 27 with the incidence locations of the particle beam 122 on the object surface 13 according to the state of the beam deflector 50, in order to record a particle-optical image of the object 13 or the object surface thereof.

The objective lens 11 comprises a pole shoe 29 and a coil 31 , which can be controlled or excited by means of the controller 20. Furthermore, the objective lens 11 can comprise an electrostatic lens (not illustrated in Figure 1). The condenser lens 4 and the objective lens 11 focus the particle beam 122 in such a way that the minimum beam diameter, that is to say therefore the beam focus, is imaged in a manner focused at the working distance WD from the objective lens 11 , provided that the x-stigmator and the y-stigmator are adapted such that the beam cross-section has a circular cross-section in the region of the beam focus. A sharp particle-optical image can be recorded precisely when the surface of the object 13 coincides with the beam focus, i.e. the object 13 is at the correct distance from the objective lens 11.

The sample stage 14 comprises an actuator (not illustrated), which can likewise be controlled by means of the controller 20, the actuator being configured to set the position of the object 13 or of the object surface in the z-direction or in the direction of the particle beam 122. Therefore, the controller 20 can vary firstly the excitation of the condenser lens 4 and of the objective lens 11 or else the position of the object 13 in the z-position by means of the actuator in order to generate the beam focus exactly on the object surface.

In practice, it is difficult to find the optimum settings for the focus, for the x-stigmator and for the y- stigmator in such a way that the beam spot formed on the object surface 13 has a circular crosssection in conjunction with a minimum diameter of this circle.

As already described above in the description of the prior art, automated adjustment methods for imaging particle beam systems are already known, in principle. Iterative methods exist, for example, in which particle-optical images of a sample or an object are in each case recorded for different settings of focus, x-stigmator and y-stigmator, and the images are then analysed with regard to the image sharpness. For this purpose, it is known to derive a sharpness measure from the absolute values of intensity gradients. Such a method is described in US 9,916,964 B1 , the content of which is fully incorporated by reference in the present patent application.

The present invention now discloses an improved method for determining the image sharpness of a particle-optical image, in which an improved image sharpness criterion is used. The method is quicker and more robust than known methods and it is also usable in particular for particle-optical images of samples or objects with little edge contrast. In particular, it is also usable for particle-optical images of semiconductor samples, which often have hardly any edge contrast or only have edge contrast in a distinguished direction. Furthermore, the associated image sharpness criterion is made usable for an automated adjustment of imaging particle beam systems.

Figure 2 schematically shows method steps of a method according to the invention for determining the image sharpness of a particle-optical image.

Method step S1 involves providing an image data set of the particle-optical image, wherein the image data set is generated or has been generated by means of a particle beam system which operates with charged particle beams.

Step S2 involves generating two gradient data sets on the basis of the image data set, wherein the first gradient data set describes an intensity gradient of the image data set or of the processed image data set in a first direction and wherein the second gradient data set describes the intensity gradient of the image data set or of the processed image data set in a second direction, wherein the first direction is linearly independent of the second direction and wherein the first direction and the second direction define a reference coordinate system. In other words, it is the case that a gradient vector image is generated in this method step. This image can be represented mathematically in the form of two matrices, each matrix describing a gradient data set in one direction. Preferably, the two directions of the reference coordinate system are orthogonal to one another; the first gradient data set describes for example the intensity gradient of the image data set or of the processed image data set in the x-direction, and the second gradient data set accordingly in the y-direction.

A method step S3 involves defining a calculation coordinate system K1 rotated by the rotation angle cp1 relative to the reference coordinate system. Defining the rotation angle cp1 or defining the rotated calculation coordinate system K1 lays the foundation for the following analysis of the intensity gradient in a specific direction. The next method step S4 involves calculating a gradient data set GD1 in the calculation coordinate system K1 on the basis of the two gradient data sets of the reference coordinate system. This method step corresponds, in principle, to a projection onto the axial direction or axial directions in the calculation coordinate system K1 defined by the angle <p1.

Step S5 involves calculating a variance V1 on the basis of the values of the gradient data set GD1, wherein the calculation of the variance V1 comprises averaging from a plurality of direction-related variance values. It is possible, for example, to calculate the averaging in the gradient data set GD1 from variance values determined row by row. That is based on the consideration that along each row in the gradient data set, the variance is determined along the same direction coordinate. This additional averaging provides for additional stability of the method for determining the image sharpness.

Thereafter, the next rotation angle (p2 is then defined, for example by incrementally increasing the angle (p1 by a fixed value. Method steps S3 to S5 are repeated. Then the variable i is increased once again by one and a third rotation angle (p3 is defined and method steps S3 to S5 are repeated. This is done until steps S3 to S5 have been carried out for a total number N of different rotation angles (pi with i=1..N. In other words, N values of variances Vi are then present, wherein for each gradient data set GDi a variance Vi assigned thereto has been calculated. A variance can likewise be calculated for each of the two gradient data sets which define the reference coordinate system.

The next method step S6 involves determining the minimum variance Vmin from the N values of the variances Vi. Of course, it is possible and advantageous also to include the variance of the first gradient data set of the reference coordinate system and the variance of the second gradient data set of the reference coordinate system in the determination of the minimum variance. Therefore, the minimum variance Vmin is then determined from N+2 values of variances. This is reasonable in particular if the first gradient data set of the reference coordinate system is regarded as a starting gradient data set and the second gradient data set is regarded as final gradient data set. Ultimately, however, this also depends on the choice and number of the rotation angles (pi. (pi = 0° corresponds to a gradient data set in the reference coordinate system.

Step S7 involves determining the image sharpness on the basis of the minimum variance Vmin. The minimum variance Vmin is thus a measure of the image sharpness. The fact that the minimum variance Vmin serves as an image sharpness measure can prevent for example a situation in which a particle-optical image in which a line focus is clearly present would be regarded as the sharpest and best image overall. Specifically, an image having a line focus would have a low variance only in one direction, but a high variance in a second direction, for which reason the image would perform badly in the case of the image sharpness measure according to the invention. By contrast, if an image has similar and here more likely average variances in many directions, then such a particle- optical image more likely performs well in the case of the sharpness criterion described.

In accordance with one preferred embodiment of the invention, the maximum rotation angle (pi_max< 90°. This is explained by a skilful mathematical or algorithmic implementation of the method described. Projecting the gradient data set GDi in the directions xi, yi in the calculation coordinate system Ki can involve carrying out the projection onto both axis directions. This is comparable to a situation in which firstly an analysis of the gradient in the direction of the rotation angle (pi and an analysis of the rotation angle (pi + 90° are carried out in the same evaluation step. Projections of a vector onto axes of a coordinate system can therefore be carried out completely in the first quadrant relative to both axes; projections for angles (pi > 90° can then be automatically calculated as well. The same applies, mutatis mutandis, to rotation angles (pi which would otherwise lie in the third quadrant or the fourth quadrant; here it is necessary to observe possibly the other sign during the projection onto the axes of the calculation coordinate system.

Figure 3 shows data of an image sharpness determined according to the invention as a function of one parameter describing a stigmation of the particle beam, and also associated particle-optical images. For different settings of a stigmation Y of a particle beam, the image sharpness was in each case determined on the basis of the minimum variance Vmin. In the present case, the image sharpness value is plotted on the y-axis as IQ (following the English abbreviation for “image quality”). The variation of the stigmation is plotted on the x-axis, specifically in per cent. That is based on the consideration that a stigmation unit in a particle beam system can be set to a value range from not having current or voltage applied at all or else having a maximum value applied. The illustrated percentage indications relate thereto. The illustration shows only a portion of the data obtained, namely between approximately 10% stigmation in the y-direction and 13% stigmation in the y- direction. Nine data points are plotted in the diagram. A stigmation of approximately 11.5% in the y- direction yields the best sharpness value. The associated particle-optical image is likewise illustrated in Figure 3. This image is also that image which a user of a particle beam system would recognize as the sharpest image. Two further particle-optical images are illustrated for comparison, these images corresponding to the stigmations in the y-direction at approximately 2.5% and at approximately 13%. These images are comparatively sharp only in one direction; they are unsharp in another direction. The illustration in Figure 3 thus shows that the proposed method for determining the image sharpness, which determines the image sharpness on the basis of the minimum variance Vmin, also actually functions as described and in particular excludes line foci as sharpest images.

Figure 4 shows data of an image sharpness determined according to the invention as a function of two parameters each describing a stigmation of the particle beam, and also two associated particle- optical images of a semiconductor sample which was used as object during the image recording. Specifically, the stigmation in the x-direction and the stigmation in the y-direction are plotted in the diagram in the form of a chart. Percentage indications are again used here to identify the stigmation. The individual data points are each represented as circles in the diagram or chart. If the content of the respective data circle is shown light in the depiction, then this means a high image sharpness in the sense of the image sharpness criterion according to the invention. Dark circles, by contrast, indicate a lower image sharpness. The illustrated diagram reveals, then, that a particle-optical image having the highest image sharpness has actually been found relatively centrally in the chart. Moving relatively concentrically further outwards in the chart, the image sharpness decreases. Two particle- optical images are again shown by way of example: The particle-optical image which is regarded as the sharpest image in accordance with the image sharpness criterion according to the invention is illustrated on the right and is a sharp particle-optical image for an observer as well. By comparison therewith, the particle-optical image illustrated on the left is distinctly less sharp. What can thus be deduced from this, too, is that the image sharpness criterion according to the invention functions very well, specifically even if a particle-optical image of a semiconductor sample having little edge contrast and, in principle, a poor signal-to-noise ratio is used as test object. The method according to the invention for determining the image sharpness is thus noise-resistant and it is possible to attain a monotonic increase to the maximum of the image sharpness despite very few image structures or edges.

Figure 5 schematically shows method steps of a method for determining the image sharpness of a particle-optical image. Compared with the flow diagram illustrated in Figure 2, here a further method step S8 is provided between steps S1 and S2: Method step S8 involves denoising the image data set so that a processed image data set is generated, for which the further method steps S2 to S7 are carried out. Denoising the image data set takes place substantially without edge smoothing in order as far as possible not to lose any information that is important for the image sharpness criterion described. The image data set is thus denoised, but not smoothed.

The denoising described can be carried out in various ways. One possibility consists in applying a median filtering. Alternatively, binning with an optimized kernel size is possible. A further possibility is denoising the image data set by means of a neural network.

The fact that the method according to the invention for determining the image sharpness of a particle- optical image functions very well even on the basis of an originally noisy image data set allows the method also to be used very well in the course of an automated adjustment of a particle beam system. This is because image recordings required for this can be effected very quickly, possibly with a signal-to-noise ratio not being as good.

Preferably, the Sobel operator is not used for generating gradient data sets. Figure 6 schematically shows method steps of a method for the automated adjustment of an imaging particle beam system. For this purpose, in step S20, firstly a particle beam system which operates with charged particles is provided. The particle beam system is an imaging particle beam system, wherein the type of detector or detection unit can be chosen freely, in principle. Examples of such a particle beam system are, inter alia, a particle microscope, a SEM, a TEM, a STEM, a SEM-STEM, a dual beam system (referred to as “cross beam”), a multi-beam particle microscope, a mask repair system and other systems. The charged particles can be electrons or ions, but also muons and other charged particles.

A further method step S21 involves selecting a first parameter P1 k, which influences the image sharpness of particle-optical images recorded by means of the particle beam system and which is adjustable by means of a first actuating element of the particle beam system. In this case, the first parameter P1k can be chosen freely, in principle; it is advantageous to choose a first parameter P1k such that this parameter P1 k has a great influence on the image sharpness. The parameter P1k can thus be for example currents or voltages which are applied at deflectors, lenses, coils, etc. of the particle beam system. It is possible, for example, that the parameter P1 k therefore influences a stigmation of a particle beam or a focus or a working distance between an objective lens and a sample surface. Moreover, the parameter P1k can influence a deflection of a particle beam towards a lens centre, in particular towards an objective lens centre. This is an important parameter in particular for particle beam columns used in the context of mask repair systems.

In a further method step S22, in the course of a first setting of the first parameter P11 , an image data set is generated by means of the particle beam system.

Method step S23 involves determining the image sharpness of the image data set by carrying out the described method for determining the image sharpness of a particle-optical image (cf. Figures 2 and 5).

Method step S24 involves assigning the image sharpnesses determined in step S23 to the present value of the first parameter P1 k, i.e. firstly to the value of the parameter P11. The value of the parameter P1 k is then changed, for example from the value of the parameter P11 to the value of the parameter P12. Method steps S22, S23 and S24 are repeated. These method steps S22, S23 and S24 are repeated until the parameter P1 k has been caused to traverse a relevant value range. The number of iteration steps may have been defined in advance; it is also possible to define a termination criterion here. Method step S25 involves analysing the image sharpnesses determined in each of steps S24 as a function of the values of the first parameter P1k; this method step thus effects an assignment, which can optionally also be represented graphically.

Method step S26 involves determining a maximum value of the image sharpness and the associated value of the first parameter P1opt on the basis of the analysis according to step S25. Therefore, this method step then corresponds for example to the determination of the maximum of the data points illustrated in Figure 3.

Method step S27 involves setting the particle beam system to the value of the first parameter P1opt by means of the first actuating element. Therefore, by way of example, the y-stigmator is set to the percentage value determined as optimum.

In the course of traversing or varying the first parameter P1 k, a specific step size is used. This does not ensure that the actually best value P1opt of the first parameter P1k is also actually set by means of the actuating parameter. For this reason, it may be reasonable to determine the best parameter P1opt by means of an interpolation on the basis of the measurement data obtained. A spline interpolation has been found to be advantageous. By contrast, fitting to a parabola in the range of maximum image sharpness has not proved worthwhile.

Figure 7 shows by way of example data of an image sharpness as a function of a working distance WD and also the interpolation of the data. In this case, too, the spline interpolation was applied as interpolation method. The actually measured values form the support points for the spline interpolation. If the maximum value of the image sharpness on the interpolated curve deviates from one of the actual measurement points, then the varied parameter, here the working distance WD, can be set to this interpolated value.

Something else is readily discernible in Figure 7: The gradient of the image sharpness is very flat in the region of the maximum of the image sharpness. Little change in image sharpness may make it difficult to carry out good determination of the optimum image sharpness. For this reason, the invention proposes realizing a super-fine setting of an image sharpness optimum in another way as well. Specifically, a focus optimization or working distance optimization by way of a symmetry of the image unsharpness during variation of the focus or of the working distance WD is proposed:

Figure 8 illustrates a principle for a super-fine setting of a working distance WD and thus a focus setting. A parameter P1 describing a working distance WD between an objective lens of the particle beam system and a sample surface is plotted on the x-axis. The image sharpness IQ is plotted on the y-axis. In this case, the curve depicted in the two diagrams in Figure 8 represents the actual profile of the image sharpness IQ as a function of the parameter P1. In Figure 8a, the value P1opt of the parameter P1 is additionally plotted, which designates the best value for the parameter P1 from among the measured data points. In the example shown, this value P1opt does not lie exactly at the maximum of the curve. The curve has moreover the important property that it progresses symmetrically around the maximum. This symmetry is now utilized by the parameter P1 being symmetrically adjusted from the value P1opt by the absolute value cf. The associated image sharpness values are determined. Figure 8a reveals that the two values of the image sharpness IQ that are associated with the values P1opt - cf and P1opt + cf are different. The value P1opt for the parameter P1 is therefore not yet the genuine optimum value for the parameter P1. Instead, the value needs to be shifted from P1opt in the direction of increasing image sharpness.

Figure 8b shows the situation in which the shifted optimum value Piopt_new is situated exactly at the curve maximum: In this case, detuned values for the parameter P1 by the absolute value cf are values for which the same image sharpness IQ is determined: Figure 8b depicts the values Piopt_new - 5 and Piopt_new + 5. The image sharpnesses for these two values of the parameter P1 are identical. This identity is the criterion as to whether the genuine maximum for the parameter P1 has actually been found.

Figure 9 schematically shows method steps of a method for the super-fine setting of a working distance WD and thus a focus setting. In a method step S30, the method starts, wherein the parameter Pi has already been set to the value Piopt. This can be a value of the parameter Pi which corresponds to a data point in the case of the first setting or coarse setting; it can also be a value already improved by interpolation. The parameter Pi influences the image sharpness of images recorded by means of the particle beam system and describes a working distance WD between an objective lens of the particle beam system and a sample surface or an object surface.

Method step S31 involves negatively detuning the value of the parameter Piopt by an absolute value 6 to a value PiD1. Step S32 then involves recording a particle-optical image and determining the image sharpness for the value Pi D 1.

Method step S33 involves positively detuning the value of the parameter Piopt by an absolute value 6 to a value PiD2. In step S34, once again an image data set is generated for the present parameter setting and the image sharpness is determined as described above.

S35 involves comparing the image sharpnesses respectively determined in steps S32 and S34 and ascertaining whether an inequality of the image sharpnesses respectively determined is present. If such an inequality in the image sharpnesses is present, then step S36 involves replacing the original value Piopt of the parameter Pi by an improved optimum value Piopt_new on the basis of the inequality. Illustratively speaking, the value Piopt is slightly shifted in the direction of increasing image sharpness.

Method steps S31 to S35 are repeated, possibly repeated a number of times, specifically in each case with the improved optimum value Piopt_new as value of the first parameter. These repetitions are carried out until a termination criterion for a sufficient equality of the image sharpnesses is satisfied.

S37 then involves setting the particle beam system to the improved optimum value of the parameter Piopt_new by means of the first actuating element.

In this case, detuning the parameter Pi can be carried out in various ways: In principle, any adjustment variable having a direct influence on the z-position of the focal plane can be used for this purpose. It is possible, for example, to use an electrostatic portion of an objective lens for this detuning. Alternatively, it is possible to vary an opposing field present at an object or the sample. It is also possible to vary an additional electrode arranged near the sample. A booster voltage and thus an electrostatic lens can be varied. These are merely examples. It is advantageous, however, if the actuating element for detuning the working distance WD is varied electrostatically. Problems owing to occurrence of hysteresis with the use of magnetic fields are avoided. In addition, the method can be carried out rapidly as a result.

Figure 10 schematically illustrates method steps of a method for the automated adjustment of an imaging particle beam system during variation of one parameter Pik. A first method step S60 involves adapting an adjustment value of the parameter Pik. Then, in method step S61 , an image recording of a particle-optical image is effected in the case of this setting. Specifically, the image recording is effected in the set scanning region of the particle beam system.

Method step S62 involves checking whether the image recorded in step S61 is shifted compared with a particle-optical image recorded previously. Such a shift should be avoided if possible. Therefore, if a shift is ascertained, step S63 involves a position correction of the scanning region by way of correlation and beam shift. Step S61 then involves carrying out an image recording in the newly set scanning region. Step S62 involves checking again whether the recorded image is shifted. If this is the case, readjustment takes place once again in step S63. If it is not possible to ascertain a shift in relation to the preceding image for a different value of the parameter or adjustment value Pij, then in step S64 the image sharpness of the recorded particle-optical image is determined and stored. Step S65 involves checking whether the adjustment value has already reached its maximum adjusted value. If this is not the case, the adjustment value is altered again and the method begins again in step S60 with the new adjustment value. By contrast, if the maximum adjusted value of the adjustment value Pij has been reached, then a spline interpolation with optimized smoothing can be carried out in step S66. Optionally, it is possible also to subtract a linear baseline before the spline interpolation. This is advantageous particularly in the case of small magnifications of the particle beam system.

Method step S67 involves setting the adjustment value or parameter Pij to the maximum of the interpolated image sharpness curve.

Method step S68 involves checking whether this maximum is situated in the marginal range of the adjustment value or of the traversed range for this parameter Pij. If this is the case, then the adjustment value is adapted once again and steps S60 et seqq. are carried out again. However, if the determined maximum is not situated in the marginal range of the sharpness curve, then the method ends with step S69. It is optionally also possible to carry out method steps S60 to S69 once again with a reduced maximum adjusted value of the parameter Pij. As a result, the method steps can be chosen possibly to be finer and the value of the adjustment parameter Pij can be determined more accurately. Modifications of this algorithm in Figure 10 are possible, of course.

Moreover, the described algorithm is also usable, in principle, for the optimization of aperturedeflector adjustment values, i.e. in the case of so-called “wobble”. Instead of the image sharpness, what is stored in this case is an image shift between different recordings with slightly varied high- voltage values.

In the case of the described method for the automated adjustment of a particle beam system which operates with the sharpness criterion according to the invention, it is important, in principle, that the detection unit used for the image recording is set well. Therefore, the method for the automated adjustment of a particle beam system 100 preferably also comprises optimizing a detector setting of the particle beam system 100 before adjusting the particle beam system 100 with regard to the image sharpness. Moreover, it is also possible to readjust or adapt the detector setting during the method according to the invention for the automated adjustment of the particle beam system 100.

In accordance with one preferred embodiment of the invention, the optimizing involves recording a particle-optical test image. This test image can be the recording of a sample or test sample; however, a test structure inherently present can also be involved, for example in the case of a mask repair system which operates with a so-called small net. This will be described in even greater detail further below.

The described optimization can involve setting the brightness and the contrast of a detection unit. In this case, the optimizing can involve using the following two target stipulations: minimizing the brightness and thus the offset value of the detection unit when 0% contrast is present, and no cutting off of intensities in the entire contrast range, wherein the contrast is defined from 0% contrast to 100% contrast including the interval limits.

Figure 11 schematically shows method steps for the automated setting of a detection unit, specifically of a detector offset:

In principle, it holds true that in the case of a detection unit, brightness and contrast can be set for the image or test image recorded by means of the detection unit. In this case, the brightness can be set by way of setting an offset. The contrast, on the other hand, can be set by way of setting the amplification range of the detection unit.

Illustratively, for a graphical representation in which the intensity from 0% to 100% is plotted on the x-axis, and in which the number or counts of the respective intensity are plotted on the y-axis, the following elucidation holds true: A curve having one peak is considered. A change in brightness then describes the shifting of the peak position of the signal along the x-axis. This is set by way of the setting of the offset at the detection unit.

In this representation, the contrast corresponds to compressing or stretching the peak or the signal. The amplification of a detection unit can thus be set by way of compressing or stretching the peak.

It is possible here, in principle, to specify the intensity in %: 0% corresponds to only dark values of the intensity or of the brightness values, and 100% corresponds to only maximum brightness values. Both extreme cases are disadvantageous, which is why efforts are made to utilize a mid range of the brightness values for the signal representation.

The method for the automated setting of a detector offset and thus of the brightness as described by way of example therefore comprises the following steps:

In a first method step S40, the dwell time or recording time is set since, of course, the measured brightness values are dependent on the dwell time or measurement time. In the next method step S41 , the contrast is set to 0%. That means that the signal is maximally compressed. At the same time, in step S41 , the brightness is set to 50%. That means that the peak is shifted to 50% of the brightness values, specifically by means of the setting of the detector offset. Thereafter only the brightness or the offset is varied; the set value for the contrast remains fixed at 0%.

In method step S42, an image recording is then effected. By way of example, a test sample can be used for this purpose.

In method step S43, an average value of the image intensity is then calculated. Illustratively speaking, this therefore involves determining the position of the peak of the signal, which after all was previously set very narrow (owing to contrast=0).

Method step S44 involves checking whether the average image intensity is in the target range or satisfies a stipulation. In the case of brightness values for the intensity of 0 to 255, this may be for example a target range of 2, 3 or 4 as brightness value. If the calculated average value of the image intensity is not in the target range, which will often be the case at the beginning of the iterative method, then the brightness is reduced. Advantageously, the procedure adopted here can be such that the brightness is changed as follows: The average value of the image intensity is subtracted from the desired target value for the image intensity and the result is divided again by ten times the iteration value (i.e. division by 10 after the first iteration step, division by 20 upon the second iteration step, etc.). Instead of the factor 10, it is also possible, of course, to choose a different value, for example 5. Adapting the brightness in the course of the iterative process thus takes place firstly as a function of the difference between the calculated average value of the image intensity and the desired target value for the image intensity and secondly as a function of the iteration i. This has the advantage that the brightness is adapted firstly in large steps and then in steps becoming ever smaller, the target setting thereby being carefully approached, at which the average image intensity is in the target range.

Afterwards, a further image recording is carried out in step S42, the average value for the image intensity is once again calculated in step S43, and in step S44 the query is made again as to whether the calculated average value of the image intensity is in the defined target range. Optionally, further iterations are effected and method steps S45, S42, S43 and S44 are carried out a number of times.

If, when carrying out method step S44, it is then ascertained that the average value of the image intensity is in the target range, then the algorithm ends and the detector offset is set optimally and with no signal loss. Figure 12 schematically shows an iteration starting setting and an iteration result for the method for the automated setting of the detector offset as described in Figure 11 : Figure 12a shows the setting for the iteration starting value: The contrast is set to 0; the signal is extremely sharp or narrow. At the same time, the intensity is set to approximately 50%, i.e. to a mid brightness value.

Figure 12b shows the iteration result for the method described in Figure 11 : The signal has moved entirely to the left by virtue of the setting of the detector offset; nevertheless, no signal is cut off.

Figure 13 schematically shows method steps for the automated setting of a detector amplification. For this purpose, in method step S50, once again firstly the dwell time is set. Ideally, the dwell time is the same as in the method for the automated setting of the detector offset as illustrated in Figure 11.

The next method step S51 involves having recourse to the already optimized setting of the brightness: The brightness is set to the iteration result from Figure 11 and is not changed any more.

In method step S52, the contrast is set to a starting value, for example to 30%. This is done solely by means of setting the amplification of the detection unit. By virtue of the contrast being adjusted from 0 (cf. setting of the detector offset according to Figure 11) to 30%, the signal is widened or stretched, in principle.

In this constellation, in a first iteration, an image recording is then effected in step S53.

In method step S54, the brightness values / counts attained during the image recording are evaluated: By way of example, this can involve the position of the 95th percentile. That means that 95% of the measured counts are smaller than the 95th percentile and, conversely, 5% of the counts are larger than the value of the 95th percentile.

For the 95th percentile p95, step S55 involves querying whether it is in the target range. Given an 8- bit resolution with brightness values of 0 to 255, said target range can be in the range of 197.5 to 202.5, for example. If the 95th percentile p95 is not in the target range, then method step S56 involves adapting the contrast by a value which firstly is dependent on the deviation of the 95th percentile p95 from the previously defined target range and secondly is dependent on the iteration used to carry out the image recording. By way of example, the contrast value can be adapted by (p95-p95_target divided by 20*y7), where i denotes the iteration. The adaptation of the contrast by setting the amplification is thus firstly dependent on the separation between the 95th percentile p95 and the target range and is all the greater the further away the value p95 is from the target range. At the same time, the adaptation of the contrast value or the adaptation of the amplification is carried out more finely with each iteration step i. The relationship with where i denotes the iteration, has generally been found to be advantageous. The factor 20 could also be chosen differently, for example as factor 18 or 22 or 10.

Method steps S56, S53, S54 and S55 are repeated a number of times until, upon the query in step S55, the 95th percentile P95 is in the previously defined target range.

The method for the automated setting of the detector amplification then ends with step S57.

Figure 14 schematically shows an iteration starting setting and an iteration result for the method described in Figure 13: Figure 14a shows the iteration starting setting. In the example illustrated, the starting contrast value is approximately 30%, which corresponds to a position of the peak of the curve at approximately 15% in the example illustrated. Brightness values from 0% intensity to 30% intensity are thus detected overall.

Figure 14b illustrates the iteration result for the method described in Figure 13: 95% of the signals or counts are to the left of the 95th percentile, i.e. are less than p95. 5% of the signals are above that. The signal itself is widened compared with the iteration starting setting in Figure 14a. Moreover, it is the case that now at the right-hand margin, too, in principle no signal is cut off (this is ensured by the choice of the 95th percentile), nor is the intensity range utilized incompletely. At the upper and lower margins, too, represented by the two dashed arrows in Figure 14b, no signal is cut off. The detection unit is thus utilized optimally. Therefore, no signal intensities are cut off also at the lower margin (“0% level”) and also at the upper margin (“100% level”). For this reason, the described method for the automated detector setting of a particle beam system is generally also suitable for quantitative measurements and in particular for intensity comparisons.

The methods for the automated adjustment of an imaging particle beam system that have already been described above can be combined with one another, of course. Figure 15 shows by way of example such a combination of method routines: Figure 15 schematically illustrates method steps of an iterative method for the automated adjustment of an imaging particle beam system during variation of a plurality of parameters Pik and with fixed magnification. The so-called iterative adjustment 500 begins in step S100 with the setting of brightness and contrast, as has been described for example in connection with the routines in Figures 11 to 14.

In method step S101 , in the example shown, the automated setting of the focus is effected, for example by means of a setting of the objective lens current. By way of example, a method as described in connection with Figure 10 can be used for this purpose. In this case, the evaluation of the image sharpness is effected in accordance with the method according to the invention for determining the image sharpness, as has been described in greater detail for example in Figures 2 and 5.

In an analogous manner, method step S102 involves optimizing the stigmation overall, wherein it is possible to set a variation of the stigmation in the x-direction and in the y-direction separately from one another or else in combination (cf. chart in Figure 4).

In the example shown, method step S103 involves optimizing the setting for a beam deflector which deflects a particle beam towards the centre of the objective. Exact central passage through the objective lens centre is concomitantly crucial for the resolution capability. The method described by way of example in Figure 10 can be used once again for this purpose as well.

Method step S104 involves a super-fine setting of the focus. A method that can be used for this purpose is described in Figures 8 and 9, for example.

Parameters that are optimized in the course of the iterative adjustment 500, for focus, stigmator, wobble and, in principle, also for the super-fine setting of the focus, are often not completely independent of one another. It may therefore be reasonable to carry out multiple iterations of method steps S101 to S104. It is possible, in a method step S105, to query the number of iterations already carried out. If the number of iterations previously set has not yet been reached, then method steps S101 to S104 are repeated, possibly a number of times. Alternatively, method step S105 can involve checking a convergence criterion indicating whether or not a repetition of method steps S101 to S104 is necessary. If the method is convergent or if the number of stipulated iterations has been reached, then the method for iterative adjustment 500 ends with method step S106.

The described iterative adjustment 500 with fixed magnification has a multiplicity of relevant applications. These include the following applications, for example: a microscopic application can be preceded by a rapid adjustment. it is possible to carry out automated logging of the present adjustment values for a microscope performance test. a standardization of the adjustment procedure is possible, specifically independently of the respective user of the imaging particle beam system. This also enables better comparison between recordings by means of the imaging particle beam system, even if they are effected by different users. it is possible to carry out an automated high-resolution proof at different operating points (in this case, the operating points can be defined for example by way of the used acceleration voltage, the landing energy, the working distance, used stop settings, etc.). the iterative adjustment 500 can also be used as user assistance in the case of a slow remote connection to the imaging particle beam system. it is possible to automate further microscope applications which rely on an optimally adjusted beam in each case.

The present list should be understood not to be exhaustive.

Figure 16 shows in an exemplary manner one example of a so-called fundamental adjustment 600: Specifically, method steps of a method for the automated adjustment of an imaging particle beam system 100 during variation of a plurality of parameters Pik are schematically illustrated, wherein the method is suitable for a greatly misadjusted particle beam system 100.

A method step S1000 involves resetting the adjustment values. In this case, the adjustment values of various parameters are set to an initial value, which can correspond as it were to the factory setting.

Method step S1001 involves defining the image recording parameters. That may be for example a scanning speed or a noise reduction method to be applied. In this case, the image recording parameters are intended to be chosen such that a sufficient signal-to-noise ratio can be attained during the subsequent image recording.

Method step S1002 involves setting the magnification. This typically starts with a relatively low magnification.

Method step S1003 involves selecting the scanning region as a function of the image sharpness that is present or to be expected there. By way of example, a region is selected which has meaningful edges and is therefore particularly meaningful with regard to the image sharpness criterion. In any case, however, the scanning region must be defined in a reproducible manner.

Method step S1004 then involves carrying out the iterative adjustment 500, as has already been described by way of example in Figure 15. In the course of the fundamental adjustment 600, the iterative adjustment 500 is carried out only by means of one iteration. In other words, for example, a 1 D optimization of the focus, a 1 D optimization of the stigmator, a 1 D optimization of the wobble and the setting of the super-fine focus take place in this case.

Method step S1005 involves querying whether the desired target magnification has been attained. If this is not the case, then method steps S1002 to S1005 are repeated, possibly repeated a number of times. In this case, the magnification is then increased step by step upon each iteration. If the desired target magnification is completed in method step S1005, then the fundamental adjustment ends in method step S1006.

The advantages of the fundamental adjustment 600 can be summarized as follows: The fundamental adjustment 600 offers very good user assistance in the case of a greatly misadjusted imaging particle beam system 100. The fundamental adjustment 600 can be carried out independently of possible presettings. Different parameters are optimized successively, which makes the optimization itself very clear. In many cases, it is possible to determine a global optimum for the image sharpness and to adjust the imaging particle beam system 100 according to the parameter values associated with this optimum image sharpness.

It is pointed out once again that the methods for the automated adjustment of a particle beam system that are presented here should be understood to be merely by way of example. All of them can be based on the method according to the invention for determining the image sharpness of a particle- optical image. However, it is also possible to use the methods for the automated adjustment of an imaging particle beam system possibly with a different image sharpness criterion, even if this may not be regarded as advantageous at the present time.

Several examples of imaging particle beam systems which can be used for the methods according to the invention are additionally described hereinafter. In particular, the described method for the automated adjustment of the imaging particle beam system can be used in these imaging particle beam systems. In this case, it is possible once again to use the method for determining the image sharpness of a particle-optical image according to the invention with its improved image sharpness criterion on the basis of the minimum variance Vmin. The selection of imaging particle beam systems 100 described below should also be understood not to be limiting for the invention.

Figure 17 schematically shows a particle beam system 100 according to the invention on the basis of the example of a particle beam column 100 having a double condenser 4, 8. The particle beam column or the SEM 100 has a beam generator having an electron source 1 , which is designed as a cathode. Moreover, the beam generator has a suppressor electrode 2 and an extractor stop (not illustrated). Furthermore, the SEM 100 is provided with an anode stop 3 that is mounted on one end of a beam guiding tube (not illustrated) of the SEM 100, for example is pressed onto the beam tube via a spacer ring. By way of example, the electron source 1 is designed as a thermal field emitter. However, the invention is not restricted to such an electron source 1. On the contrary, any electron source (or ion source) may be used in principle.

Electrons emerging from the electron source form a primary electron beam. On account of a potential difference between the electron source 1 and the anode stop 3, the electrons are accelerated to a predefinable kinetic energy by way of a predefinable potential. In the exemplary embodiment illustrated here, the potential is 0.1 kV to 20 kV, for example 0.5 kV to 1 kV, in particular 0.6 kV, in relation to an earth potential of a housing of a sample chamber (not illustrated). However, it could alternatively also be at earth potential. In addition, an acceleration voltage of 8 kV can be applied within the particle beam column, by which voltage the charge carriers are decelerated before emerging from the column.

A double condenser lens system for focusing the electron beam, namely a first condenser lens 4 and a second condenser lens 8, is arranged along the particle-optical beam path. In this case, proceeding from the electron source 1 in the direction of an objective lens system 11 , 12, there are arranged firstly the first condenser lens 4 and then the second condenser lens 8. In the illustrated exemplary embodiment, these are two magnetic lenses. A condenser stop or aperture stop 6 is arranged between the first condenser lens 4 and the second condenser lens 8. A first deflection unit 5 is arranged on a first side, facing the electron source 1 , of the condenser stop 6. Furthermore, a second deflection unit 7 is arranged on a second side, facing the second condenser lens 8, of the condenser stop 6. By way of example, both the first deflection unit 5 and the second deflection unit 7 have electrostatic and/or magnetic units that are able to be set using a control variable. In the example shown, the condenser stop 6 is preferably a stop having a single aperture. The condenser stop 6 is used to shape the particle beam or trims said particle beam. It can therefore also be used to set the beam current intensity of the particle beam. Owing to the design of the condenser lens system as a double condenser having the condenser lenses 4, 8, a beam current intensity of the particle beam passing through the condenser stop 6 is able to be set in a continuously variable manner when the double condenser 4, 8 is controlled accordingly.

In the example shown, a third deflection unit 9 is arranged below the double condenser 4, 8. The third deflection unit 9 can have for example electrostatic and/or magnetic units that are able to be set using a control variable. In accordance with one preferred embodiment, the third deflection unit 9 is used as a stigmator.

The objective lens system has a magnetic objective lens 11 and an electrostatic objective lens 12, the latter also being referred to as an end cap. Providing the end cap 12 makes it possible to provide an electrostatic retardation device in the lower region of the beam guiding tube (not illustrated) of the particle beam column 100. Electrons of the primary electron beam are thereby able to be decelerated to a desired energy required for the examination of a sample 13.

The particle beam column 100 or the scanning electron microscope 100 furthermore has a scanning device 50 enabling the primary electron beam to be deflected and scanned over the object 13. In the process, the electrons of the primary electron beam interact with the object 13. The interaction gives rise to interaction particles, which are detected. In particular, as interaction particles, electrons are emitted from the surface of the object 13 - what are referred to as secondary electrons - or electrons of the primary electron beam are backscattered - what are referred to as backscattered electrons.

To detect the interaction particles, a detection system 10 is arranged in the beam guiding tube (not illustrated), which detection system for example has a first detector 10a and a second detector 10b. In this case, the first detector 10a is arranged on the source side along the particle-optical axis Z, while the second detector 10b is arranged on the object side along the optical axis Z in the beam guiding tube (not illustrated). The first detector 10a and the second detector 10b are arranged offset or spaced apart from another in the direction of the optical axis Z of the SEM 100. Both the first detector 10a and the second detector 10b have a respective through-hole 313, 311 through which the primary electron beam is able to pass. The first detector 10a and the second detector 10b are approximately at the potential of the anode stop 3 and of the beam guiding tube (not illustrated). The optical axis Z of the SEM runs through the respective through-openings 313, 311.

The second detector 10b serves mainly to detect secondary electrons. Upon emerging from the object 13, the secondary electrons initially have a low kinetic energy and arbitrary directions of motion. An extraction field is used to accelerate the secondary electrons in the direction of the objective lens 11 , 12. The secondary electrons enter the objective lens 11 , 12 approximately parallel. The bundle diameter of the beam of secondary electrons also remains small in the objective lens 11. The objective lens 11 then has a strong effect on the secondary electrons and produces a comparatively short focus of the secondary electrons with sufficiently steep angles with respect to the optical axis Z, such that the secondary electrons diverge far apart from one another downstream of the focus and impinge on the second detector 10b on the active area thereof. By contrast, only a small proportion of electrons backscattered at the object 13, that is to say backscattered electrons, which have a relatively high kinetic energy in comparison with the secondary electrons upon emerging from the object 13, are captured by the second detector 10b. The high kinetic energy and the angles of the backscattered electrons with respect to the optical axis Z upon emerging from the object 13 have the effect that a beam waist, that is to say a beam region having a minimum diameter, of the backscattered electrons lies in the vicinity of the second detector 10b. A large portion of the backscattered electrons therefore passes through the through-opening of the second detector 10b. The first detector 10a therefore serves essentially to detect the backscattered electrons.

In a further embodiment of the SEM 100, the first detector 10a may additionally be designed to have an opposing field grid (not illustrated). The opposing field grid is arranged on that side of the first detector 10a facing the object 13. With respect to the potential of the beam guiding tube, the opposing field grid has a negative potential such that only backscattered electrons with a high energy pass through the opposing field grid to the first detector 10a. In addition or as an alternative, the second detector 10b may have a further opposing field grid that has an analogous design to the abovementioned opposing field grid of the first detector 10a and an analogous function.

The detector signals generated by the first detector 10a and the second detector 10b are used to generate one or more images of the surface of the object 13. For this purpose, the first detector 10a and the second detector 10b are each connected to a controller 20. The detector signals are processed in the control unit 20 and may be displayed in the form of images, for example, on a monitor. The images themselves are generated or computed here in line with the raster principle. It is furthermore possible for image processing modules or image evaluation modules also to be integrated in the controller 10. By way of example, the controller 20 may have a processor into which is loaded a computer program product comprising a program code that controls the SEM 100 such that the method according to the invention is carried out. This will be explained in even greater detail further below.

In addition to the detectors 10 shown explicitly in Figure 17, the SEM 100 may also have further detectors, for example a chamber detector, which is arranged in the sample chamber. This is also generally suitable for imaging or generating raster images within the context of the invention.

The sample chamber (not illustrated) is under vacuum. To generate the vacuum, a pump (not illustrated) is arranged on the sample chamber. It is thus possible to achieve pressure ranges smaller than for example 10'³ hPa. To ensure these pressure ranges, the sample chamber is vacuum-sealed.

The controller 20 is connected to the components of the particle beam column 100 in a variety of ways in order to control same. Figure 1 schematically shows the most important lines in this respect. It is thereby possible to set for example voltages and currents, and thus also generated lens fields or deflection fields. The same also applies to the cathode voltage, anode voltage, etc.

In the exemplary embodiment shown, elements of the particle beam column 100 can also be supplied with control signals by way of which electrically controllable mechanical adjustment means for certain components or component parts of the particle beam column 100 can be controlled. In the example shown, these component parts are therefore movable and adjustable in a mechanically automated manner. In the overview in Figure 1 , this fact is represented by the double-headed arrows on the left. By way of example, in the case of the particle beam column 100 in Figure 1 , the anode stop 3, an upper pole shoe 40 of the first condenser 4, a lower pole shoe 41 of the first condenser 4, the condenser stop 6, an upper pole shoe 80 of the second condenser lens 8, a lower pole shoe 81 of the second condenser lens 8, the detection system 10 having for example a first detector 10a and a second detector 10b as well as the electrostatic objective lens 12 or electrically controllable mechanical adjustment means assigned thereto, are controllable by way of control signals. Figure 18 shows a further exemplary embodiment variant of a particle beam system according to the invention on the basis of the example of a particle beam column 100. The illustration in Figure 18 differs from the illustration according to Figure 1 in that, instead of a double condenser 4, 8, only a single condenser 4 is provided. For this reason, the condenser stop 6 in Figure 2 is designed as a stop with multiple holes. The respective present condenser aperture is selected in a manner known per se through appropriate control of deflection units 5, 7 and/or through appropriate displacement of the condenser stop 6 in a plane orthogonal to the particle-optical axis Z. In addition, in this exemplary embodiment of the invention, the electrically controllable mechanical adjustment means as already briefly described above are provided as well and are again indicated by the doubleheaded arrows on the left.

Figure 19 schematically shows a device 200 having a particle beam column 100 according to the invention for analysing and/or processing a sample 13. The sample 13 may for example be a lithography mask having a feature size in the range of 10 nm to 100 pm. For example, it may be a transmissive lithography mask for DUV lithography (DUV: "Deep Ultra Violet", operating light wavelengths in the range of 30 to 250 nm) or a reflective lithography mask for EUV lithography (EUV: "Extreme Ultra Violet", operating lightwavelengths in the range of 1 to 30 nm). Processing operations that are performed on the sample 13 with the device 200 may comprise for example etching processes, in which a material is locally removed from the surface of the sample 13, deposition processes, in which a material is locally applied to the surface of the sample 13, and/or similar locally activated processes, such as forming a passivation layer or compacting a layer.

The particle beam column or electron beam column 100 has a vacuum housing 140 that is evacuated for example to a residual gas pressure of 10'⁶ mbar to 10'⁸ mbar. An opening for the electron beam 122a is arranged on the underside. The opening itself is covered by a shielding element 130 that is secured on the opening by way of a holding element 133. By way of example, the holding element 133 comprises multiple screws in order to screw the shielding element 130 to the particle beam column 100.

The shielding element 130 is in planar form and comprises an electrically conductive material. A potential may be applied to the shielding element 130 by way of the controller 20. By way of example, the shielding element 130 may be at earth potential. The shielding element 130 is thus configured to shield an electric field. Such a field to be shielded may be generated for example by charging the sample 13 by way of the particle beam 122a. It may therefore be highly expedient to shield the interior of the particle beam column 100, in particular in the case of samples 13 that are electrically non-conductive or only slightly electrically conductive. Figure 19 illustrates a process gas supply unit 170 by way of example. The particle beam column 100 is illustrated only in parts. However, it may for example be designed as in Figure 1 or Figure 2. The process gas supply unit 170 comprises a process gas reservoir 171 , which is able to introduce process gas PG into the particle beam column 100 by way of a process gas line 173. The introduction of the process gas PG may in this case be regulated by way of a valve 172; the controller 20 of the particle beam column 100 or else a separate controller (not illustrated) may in turn be used for control and regulation purposes.

In addition to the pure shielding function of the shielding element 130, it is known practice to use the shielding element 130 for system qualification purposes as well. For this purpose, the shielding element 130 may have one or more test structures. The controller 20 of the particle beam column 100 makes it possible to direct a particle beam 122b onto the shielding element 130 instead of through the opening 132 in the shielding element 130.

Figure 20 schematically shows such a shielding element 130. The shielding element 130 comprises a net structure 131 and various through-openings, of which the central through-opening is designated with reference sign 132. The hexagonal through-openings in the example shown serve here as a possible passage for the process gas PG and as a possible passage for the particle beam. The shielding element 130 itself continues to serve as a shield. In addition, a test structure 202, 203, 204, 206, M1 , M2, which may be used for system qualification purposes, is provided in some of these through-openings. It is thereby possible in principle to qualify the device 200 for analysing and/or processing a sample or the particle beam column 100 contained therein independently of a specific sample 13 or else independently of a sample stage 14. Instead, the shielding element 132 with its test structures may constitute a fixed reference. The test structures illustrated in Figure 20 may provide different functions for determining present operating parameters and/or process parameters of the device 200. The test structure 202 may for example comprise a topographic structure, various materials M1 , M2 may be combined to form a test structure 203, it is possible to provide certain surfaces 204, 206 for performing particle beam-induced deposition processes and/or particle beam- induced etching processes, etc. It is also possible, for example, to provide a vibration element 208 having an exciter unit 160 and to draw conclusions regarding further operating parameters and/or process parameters of the device 200 on the basis of recorded vibration properties.

In accordance with a further aspect of the invention, however, it is also possible not to install any separate elements as test structures 202, 203, 204, 206, 208, M1 or M2 in the openings 132 in the shielding element 130. Instead, it is possible to use a different type of shielding element 130 for qualification purposes. By way of example, the net structure itself may be structured for this purpose. Figure 21 schematically shows one such new shielding element 130. This in turn has a net structure 131 and, for example, interposed hexagonal openings 132. However, instead of then providing special structures in the openings 132, the net structure 131 itself is structured. This is indicated schematically in Figure 21 by the hatching of the net structure 131. The otherwise very smooth and homogeneous structure of the net structure 131 itself may thereby be used for qualification purposes and/or adjustment purposes. An improved contrast ratio also arises in the region of the net structure 131 as a result of structuring, which significantly improves image evaluation.

Figure 22 schematically shows examples of such structuring on the net structure 131 itself. By way of example, a structure 135 in the form of spaced-apart parallel line markings is shown. In another limb of the net structure 131 , a structure 136 having comparatively large circular individual structures is illustrated. In another limb of the net structure 131 , a set of multiple smaller circles is illustrated as a structure element 137. The structures illustrated here should be understood only to be examples. In addition or as an alternative, it is also possible to use a pattern of randomly arranged and regarding size randomly varying circles or other shapes as a structure. Such randomly/irregularly varying structures are helpful when identifying image aberrations, since the random structures only produce noise in a Fourier transform. They may be produced in various ways. By way of example, it is possible to apply the structures 135, 136, 137 on the net structure 131 directly by way of the device 200, for example with the aid of the process gas PG. It is also possible to modify and/or to remove these structures 135, 136, 137. As an alternative, it is also possible for the structures 135, 136, 137 to have already been applied to the shielding element or its net structure 131 in a separate manufacturing step, for example prior to assembly of the device 200. By way of example, this may be done by vapour deposition and/or etching or by ion-beam or electron-beam lithography methods.

In accordance with one exemplary embodiment variant of the invention, all of the mechanical and/or electrical adjustment methods already described in more detail above are performed not using a separate sample 13, but using a sample inherent to a device or particle beam column 100, such as for example the shielding element 130. It is thereby possible to implement a fixed reference for the adjustment routines and/or other qualification steps independently of a specific sample 13 and independently of a specific sample stage 14 and/or independently of a specific process environment, etc.

It is explicitly pointed out once again at this juncture that the embodiments of the invention that are described above should be understood only to be examples and in no way as restricting the invention.

A method for determining the image sharpness of a particle-optical image with an improved image sharpness criterion is disclosed. For this purpose, for an image data set, intensity gradients in different directions are evaluated. For the gradient images generated relative to different directions, a respective variance Vi per gradient image is calculated, wherein averaging from a plurality of direction-related variance values is carried out internally per gradient image. The minimum variance Vmin, which represents a measure of the image sharpness, is ascertained from the variance values calculated per gradient image. This image sharpness criterion can also be used for an automated adjustment of imaging particle beam systems.

List of reference signs

1 Particle source

2 Suppressor electrode

3 Anode stop

3a Anode aperture

4 First condenser lens

5 First deflection unit

6 Condenser stop

6a Condenser aperture

7 Second deflection unit

8 Second condenser lens

9 Third deflection unit, stigmator

10 Detection system

11 Magnetic objective lens

12 Electrostatic objective lens, end cap

13 Sample, object

14 Sample stage

15 x,y-Stigmator

20 Controller

21 Pole shoe

23 Coil

30 Optical axis

40 Pole shoe

41 Pole shoe

42 Coil

50 Scanning device

80 Pole shoe

81 Pole shoe

82 Coil Particle beam system, particle beam column, scanning electron microscope, SEM

Element to be adjusted of the particle beam column

Electrically controllable mechanical adjustment means

Line

Beam generator

Extractor stop

Particle beam

Shielding element

Small net structure

Through-opening

Holder

Structure on the net structure

Housing

Exciter unit

Process gas supply unit

Process gas reservoir

Valve

Process gas line

Device for analysing and/or processing a sample

Test structure

Vibration element

Test structure

Circle or annulus

Detector hole of a secondary electron detector

Circle

Detector hole of a backscattered electron detector

Maximum

Minimum 317 Sectional line

318 Dark background in a raster image

500 Iterative adjustment

600 Fundamental adjustment

PG Process gas

M1 Test structure

M2 Test structure

Z Particle-optical axis of the particle beam column x,y,z Directions

Claims

Patent Claims

1. Method for determining the image sharpness of a particle-optical image, wherein the method comprises the following steps:

(a1) providing an image data set of the particle-optical image, wherein the image data set is generated or has been generated by means of a particle beam system which operates with charged particle beams;

(a3) for a plurality N of different rotation angles cpi with i=1..N:

(a4) determining the minimum variance Vmin from the N values of the variances Vi; and

(a5) determining the image sharpness on the basis of the minimum variance Vmin. Method according to the preceding claim, wherein the calculation of the variance Vi in method step (a3.3) involves carrying out the averaging in the gradient data set GDi from variance values determined row by row.

3 Method according to either of the preceding claims, wherein calculating the gradient data set GDi in the calculation coordinate system Ki involves carrying out a projection of the respective gradient of the image data set or of the processed image data set onto both axes of the calculation coordinate system.

Method according to any of the preceding claims, wherein the two gradient data sets in the reference coordinate system correspond to two gradient images.

5. Method according to any of the preceding claims, wherein the plurality N of rotation angles (pi are generated incrementally by means of the same increment.

6. Method according to any of the preceding claims, wherein the first direction of the reference coordinate system and the second direction of the reference coordinate system are orthogonal to one another.

7 Method according to the preceding claim, wherein for a maximum rotation angle (pi_max it holds true that: cpimax < 90°.

8 Method according to any of the preceding claims, furthermore comprising the following step: (a6) denoising the image data set substantially without edge smoothing, wherein step (a6) is carried out between method steps (a1) and (a2).

9 Method according to the preceding claim, wherein one of the methods listed below is used in step (a6): denoising by means of a neural network binning with an optimized kernel size applying a median filtering.

10 Method according to any of the preceding claims, wherein a Sobel operator is not used for generating the two gradient data sets.

11 Method according to any of the preceding claims, wherein the image data set describes the particle-optical image of a semiconductor sample and/ or a lithography mask.

12 Method for the automated adjustment of a particle beam system, comprising the following steps:

(b1) providing an imaging particle beam system which operates with charged particles;

(b3) for a plurality K of values of the first parameter P1 k with i= 1..K:

(b3.1) generating an image data set by means of the particle beam system given the current value of the first parameter P1k, (b3.2) determining the image sharpness of the image data set by carrying out the method for determining the image sharpness of a particle-optical image according to any of claims 1 to 11 ;

(b3.3) assigning the image sharpness determined in step (b3.2) to the current value of the first parameter P1k;

(b4) analysing the image sharpnesses determined in step (b3.3) as a function of the values of the first parameter P1k;

13. Method according to the preceding claim, wherein step (b5) involves carrying out an interpolation of the image sharpness between values of the first parameter P1k that are set by means of the first actuating parameter; and wherein the optimum value of the first parameter P1opt is determined on the basis of this interpolation.

14. Method according to the preceding claim, wherein a spline interpolation is applied as interpolation method.

15. Method according to any of Claims 12 to 14, wherein the first parameter P1 k influences a working distance between an objective lens and a sample surface, or wherein the first parameter P1k influences a stigmation of a particle beam in a first direction x, or wherein the first parameter P1 k influences a stigmation of a particle beam in a second direction y, which is linearly independent of the first direction x and in particular is orthogonal to the first direction x, or wherein the first parameter P1 k influences a deflection of a particle beam towards the centre at a lens centre, in particular an objective lens centre.

16. Method according to any of Claims 12 to 15, wherein method steps (b2) to (b6) are repeated for a second parameter P2k, wherein the second parameter P2k influences the image sharpness of images recorded by means of the particle beam system and wherein the second parameter P2k is adjustable by means of a second actuating element of the particle beam system.

17. Method according to the preceding claim, wherein method steps (b2) to (b6) are repeated for a third parameter P3k and/or for one further or a plurality of further parameter(s) Pik, wherein the third parameter P3k influences the image sharpness of images recorded by means of the particle beam system and wherein the third parameter P3k is adjustable by means of a third actuating element of the particle beam system, and/or wherein the one further parameter or the plurality of further parameters Pik influence(s) the image sharpness of images recorded by means of the particle beam system and is or are adjustable by means of one further actuating element or by means of a plurality of further actuating elements of the particle beam system.

18. Method according to any of Claims 12 to 17, wherein the first parameter P1 k, the second parameter P2k and the third parameter P3k each describe exactly one of the following: a working distance between an objective lens and a sample surface, a stigmation in a first direction x, and a stigmation in a second direction y, which is linearly independent of the first direction x and in particular is orthogonal to the first direction x.

19. Method according to any of Claims 12 to 18, wherein one of the parameters Pik which influence the image sharpness of images recorded by means of the particle beam system describes a working distance WD between an objective lens of the particle beam system and a sample surface and wherein the parameter is set to the value Piopt; and wherein the method furthermore comprises the following steps:

(b7) negatively detuning the value of the parameter Piopt by an absolute value 6 to a value PiD1 ;

(b8) carrying out method steps (b3.1), (b3.2) and (b3.3) for the value of the parameter PiD1 ;

(b9) positively detuning the value of the parameter Piopt by an absolute value 6 to a value PiD2;

(b10) carrying out method steps (b3.1), (b3.2) and (b3.3) for the value of the parameter PiD2;

(b 12) replacing the original value Piopt of the parameter Pik by an improved optimum value Piopt_new on the basis of the inequality; (b13) repeating, in particular repeating a number of times, method steps (b7) to (b12) with the improved optimum value Piopt_new as value of the parameter Pik until a termination criterion for a sufficient equality of the image sharpnesses is satisfied;

(b14) setting the particle beam system to the improved optimum value of the parameter Piopt_new.

20. Method according to the preceding claim, wherein the actuating element used in each case to set the value of the parameter Pik varies the working distance WD without using a particle-optical component which generates a magnetic field.

21. Method according to the preceding claim, wherein the actuating element varies the working distance WD electrostatically.

22. Method according to any of Claims 12 to 21 , furthermore comprising the following step:

(c1) optimizing a detector setting of the particle beam system before adjusting the particle beam system with regard to the image sharpness.

23. Method according to the preceding claim, wherein the optimizing according to step (c1) involves recording a particle-optical test image, and wherein the optimizing involves setting the brightness and the contrast of a detector unit, and wherein the optimizing involves using the following two target stipulations: minimizing the brightness and thus the offset value of the detection unit when 0% contrast is present, and no cutting off of intensities in the entire contrast range, wherein the contrast is defined from 0% contrast to 100% contrast including the interval limits.

24. Computer program product comprising a program code for carrying out the method according to any of Claims 1 to 11.

25. Computer program product which comprises a program code which is loadable into a controller of a particle beam system and, when the program code is executed, controls a particle beam system such that a method according to any of Claims 12 to 23 is carried out.

26. Particle beam system, configured to carry out the method according to any of Claims 12 to 23 and comprising a controller into which a computer program product according to Claim 25 is loaded. l. Particle beam system, comprising the following: a particle source for generating a particle beam comprising charged particles, at least one focusing lens through which the particle beam passes and which comprises an objective lens which focuses the particle beam at a working distance WD from the objective lens, a first stigmator, through which the particle beam passes, for the stigmation of the particle beam in a first direction x; a second stigmator, through which the particle beam passes, for the stigmation of the particle beam in a second direction y, which is linearly independent of, and in particular orthogonal to, the first direction x; an object stage or object holder configured to hold the object at a distance from the objective lens; a detection unit for detecting interaction particles emanating from the object; and a controller for controlling the particle beam system, wherein the controller is configured to control the at least one focusing lens, the first stigmator and the second stigmator and also the detection unit and to generate an image data set, and wherein the controller is configured to carry out the method according to any of Claims 12 to 23.

28. Particle beam system according to the preceding claim, furthermore comprising a deflector unit configured to deflect the particle beam towards the objective lens centre, and wherein the controller is configured to control the deflector unit.

29. Particle beam system according to either of Claims 27 and 28, wherein the particle beam system is a system from the following list of particle beam systems: a particle microscope, a SEM, a TEM, a STEM, a SEM-STEM, a dual particle beam system, a multi-beam particle microscope, a mask repair system.