KR20200037860A - Lithography method - Google Patents

Abstract

A method for determining one or more optimized values of operating parameters of a sensor system configured to measure properties of a substrate is disclosed, the method comprising: determining quality parameters for a plurality of substrates; For a plurality of values of operating parameters, determining measurement parameters for a plurality of substrates obtained using a sensor system; Comparing the substrate-to-substrate variation of the quality parameter and the substrate-to-substrate variation of the mapping of measurement parameters; And determining one or more optimized values of operating parameters based on the comparison.

Description

Lithography method

Cross reference to related applications

This application claims priority to EP application No. 17193637.0, filed on September 28, 2017.

Technical field

The present invention relates to a lithographic method for manufacturing a device. More specifically, the present invention relates to a measurement method for alignment of a substrate in a lithography method.

Lithographic methods are used to apply a desired pattern onto a substrate, generally onto a target portion of the substrate. Lithography can be used, for example, in the manufacture of integrated circuits (ICs). In such a case, a patterning device, also called a mask or reticle, can be used to create circuit patterns to be formed on individual layers of the IC. Such a pattern can be transferred onto a target portion (eg, part of a die, including one die or several dies) on a substrate (eg, a silicon wafer). The transfer of the pattern is typically through imaging onto a layer of radiation-sensitive material (resist) provided on the substrate. Generally, a single substrate will contain a network of adjacent target portions that are successively patterned. Conventional lithographic apparatus scans a pattern through a beam of radiation in a given direction (the "scanning" -direction) and a so-called stepper in which each target portion is irradiated by exposing the entire pattern onto the target portion at once, and parallel to this direction. Or a so-called scanner in which each target portion is irradiated by scanning the substrate in antiparallel. It is also possible to transfer the pattern from the patterning device to the substrate by imprinting the pattern on the substrate.

In general, the integrated circuit being fabricated includes a plurality of layers comprising different patterns, each layer being created using an exposure process as described above. To ensure proper operation of the integrated circuit being fabricated, successively exposed layers need to be properly aligned with each other. To achieve this, the substrate is typically provided with a plurality of so-called alignment marks (also called alignment targets), whereby the position of the alignment marks is used to determine or estimate the position of the previously exposed pattern. As such, prior to exposure of the subsequent layer, the position of the alignment mark is determined and used to determine the position of the previously exposed pattern. Typically, in order to determine the position of such alignment marks, alignment sensors are applied which can be configured to, for example, project a radiation beam onto the alignment marks or targets and determine the position of the alignment marks based on the reflected radiation beam. . . In the scanner, the alignment markers are read by the scanner alignment system, which helps achieve good positioning of each field on the substrate when going through the patterning step provided by the scanner. Ideally, the measured position of the alignment mark will match the actual position of the mark.

However, a variety of causes can cause deviations between the measured and actual positions of the alignment marks. In particular, the stated deviation may occur due to deformation of the alignment mark. Such deformation can be caused, for example, by processing of the substrate, for example etching, chemical mechanical polishing (CMP) or layer deposition, which leads to suboptimal marker positioning. As a result, the layer can be projected or exposed in a position that does not match the previously exposed pattern, ie, is not aligned, resulting in a so-called overlay error.

According to one aspect the present invention includes a method for determining one or more optimized values of operating parameters of a sensor system configured to measure properties of a substrate. Such methods include: determining quality parameters for a plurality of substrates; Determining, for a plurality of values of the operating parameter, measurement parameters for the plurality of substrates obtained using the sensor system; Comparing the substrate-to-substrate variation of the quality parameter and the substrate-to-substrate variation of the mapping of the measurement parameter; And determining one or more optimized values of the operational parameters based on the comparison.

The mapping can be a weighted sum, a nonlinear mapping or a trained mapping based on machine learning techniques.

The method can further include determining an optimal set of weighting coefficients for weighting the measurement parameter associated with the first value of the operating parameter and the measurement data associated with the second value of the operating parameter based on the comparison. .

The quality parameter can be an overlay or focus parameter.

The measurement parameter may be an out-of-plane deviation of a position of a feature provided on the plurality of substrates or a position on the substrate.

The operating parameters can be parameters associated with the light source from the sensor system. The operating parameter may be the wavelength, polarization state, spatial coherence state, or temporal coherence state of the light source.

Quality parameters can be determined using a metrology system. The quality parameter can be determined using a simulation model that predicts the quality parameter based on any of context information, measurement data, reconstructed data, and hybrid metrology data.

The optimized value of the operating parameter may include a set of first values associated with the first coordinate of the measurement parameter and a set of second values associated with the second coordinate of the measurement parameter.

The method may further include: determining a third coordinate parallel to the first preferred direction of the mark; Determining a fourth coordinate parallel to the second preferred direction of the mark; Determining a set of third optimized values of operating parameters associated with third coordinates and a set of fourth optimized values of operating parameters associated with third coordinates; Determining a transformation from the third and fourth coordinates to the first and second coordinates; And using the determined transform, converting the determined optimized value of the operating parameter at the third and fourth coordinates to the optimized value of the operating parameter at the first and second coordinates.

The first value of the operating parameter may be optimized independently of the second value of the operating parameter.

In some embodiments, determining one or more optimized values of the operating parameters based on the comparison can be performed for different regions of the substrate. Different zones can include zones proximate the edge of the substrate and zones proximate the center of the substrate. Each zone can include one or more alignment marks applied to the substrate. Each zone may correspond to an individual alignment mark among a plurality of alignment marks applied to the substrate.

In some embodiments, the measurement parameter is a measured position of a mark, the quality parameter is a mark-to-device shift, and an optimized value of the operating parameter is used to adjust the quality parameter to minimize substrate-to-substrate variation. It is decided to optimize. The operating parameters are parameters associated with the radiation source, the radiation from the source is directed to the substrate, and an optimized value of the operating parameters is determined by applying weights to adjust the measurements obtained using the operating parameters. Radiation from a source directed to the substrate can be received by the sensor system after targeting the substrate. Weighting can include the lens heating effect of a lens used to direct radiation to a substrate and / or receive radiation by a sensor system. The method also sub-segments using measurements obtained from substrates with sub-segmented marks subjected to intentional mark-to-device shifts to determine the sensitivity of operating parameters to mark-to-device shifts. The method may further include determining a weight for an operation parameter for measuring the marked mark.

In some embodiments, this method can be used to optimize the operating parameters of the metrology system used to control the processing of the substrate. The sensor system comprises a first sensor system associated with a first measurement system configured to measure a first property of the substrate before processing and a second sensor system associated with a second measurement system configured to measure a second property of the substrate after processing. It can contain. The method may include: for a plurality of values of the operating parameter, determining a first set of measurement parameters for the plurality of substrates obtained using the first sensor system; For a plurality of values of the operating parameter, determining a second set of measurement parameters for the plurality of substrates obtained using the second sensor system; And comparing the substrate-to-substrate variation of the quality parameter with the substrate-to-substrate variation of the mapping of measurement parameters for each of the first set and the second set of measurement parameters. Determining one or more optimized values of operating parameters may include simultaneously optimizing a first set of operating parameters associated with the first measurement system and a second set of operating parameters associated with the second measurement system. And optimization mitigates the substrate-to-substrate variation of the second property. The quality parameter can be an overlay determined from the measured second characteristic of the substrate after processing.

According to a second aspect, the present invention includes a method for determining the state of a semiconductor manufacturing process. Such methods include: determining an optimized value of the operating parameter according to the first aspect of the present invention; Comparing the determined operating parameter with a reference operating parameter; And determining the status based on the comparison.

According to a third aspect, the present invention includes a method of optimizing measurement data from a sensor system configured to measure properties of a substrate. This method includes obtaining overlay data for a plurality of substrates. The overlay represents the deviation between the measured position and the expected position of the alignment marker on the substrate and includes a plurality of measurements of the alignment marker position made by the sensor system, each of the plurality of measurements using different operating parameters of the sensor system. The method also combines weighted adjustments to measurements made by the sensor system for all the different operating parameters to ensure that overlay is minimized, based on the obtained overlay data and for each of the different operating parameters, The method further includes determining a weight for adjusting the obtained measurement using the operation parameter.

The operating parameters can be parameters associated with the radiation source from the sensor system. The operating parameter may be the wavelength, polarization state, spatial coherence state, or temporal coherence state of the light source.

According to another aspect, the present invention includes a method of aligning layers in an integrated circuit wafer. This method includes obtaining a plurality of position measurements of alignment markers on the wafer using a sensor system, each of the plurality of measurements using a different operating parameter. For each of the plurality of alignment mark position measurements, the positional deviation is determined as the difference between the expected alignment mark position and the measured alignment mark position, and the measured alignment mark position is determined based on individual alignment mark position measurements. A set of functions is defined as a possible cause for this positional deviation, and the set of functions includes a substrate deformation function representing deformation of the substrate and at least one mark deformation function representing deformation of one or more alignment marks. The matrix equation PD = M * F is generated, and the vector PD containing the positional deviation is set equal to the weighted combination represented by the weighting coefficient matrix M of the vector F containing the substrate transformation function and at least one mark transformation function. And the weighting coefficient associated with at least one mark deformation function depends on the alignment measure applied. The value for the weighting coefficient of the matrix M is determined based on the overlay obtained for a plurality of substrates, the overlay represents the deviation between the measured position and the expected position of the alignment marker, and the sensor is used with different operating parameters. It includes a plurality of measurements of the alignment marker position made by the system, and the weights adjust the measurements obtained using different operating parameters so that weighted adjustments to the measurements can be combined to minimize overlay. The inverse matrix or the pseudo inverse matrix of the matrix M is determined to obtain a value for the substrate deformation function as a weighted combination of positional deviations. The value of the substrate deformation function is applied to perform alignment of the patterned radiation beam and the target portion.

Exemplary embodiments are described herein with reference to the accompanying drawings:
1 shows a lithographic apparatus according to an embodiment of the present invention.
2 shows some possible alignment measurement results when applying different measurement parameters.
3 shows how different operating parameters of the sensor can be affected when performing measurements on a substrate.
4 is a graph showing how different operating parameters can be affected by mark deformation.
5 shows markers with different types of mark variations.
6A is a flow diagram schematically illustrating a wafer alignment, exposure and overlay measurement process.
6B is a flow diagram schematically showing another wafer alignment, exposure and overlay measurement process.
7A-C are graphs showing how product and mark shifts change for different colors of radiation.
8 is a graph showing how to correct sensitivity for a mark-to-device shift.
9 is a plot showing alignment mark asymmetry across the wafer.
10A is a plot showing an on-product overlay for a wafer map when the active color is near infrared (NIR), and FIG. 10B is an in-product overlay wafer map for the same wafer using 2-color weighting. 10C shows the difference between the plots of FIGS. 10A and 10B.
11A and 11B are two graphs showing how overlay errors change for two orthogonal directions according to different two-color weighting (TCW) combinations, one for the mark at the edge of the wafer and the other Is for the center mark.
12 schematically shows a process for determining OCW for alignment correction using various different colors, models and layouts and determining overlay correction using various frequencies, models and layouts.
13 schematically shows the process of determining the optimal combination for both alignment correction and overlay correction.
14 shows an alignment mark comprising two sets of gratings.
15 is a block diagram illustrating a computer system that can be used to utilize the embodiments described in this document.

In order to help understand the principles applied to the embodiments of the present invention, a lithographic apparatus and how such an apparatus is used will be first described with reference to FIG. 1.

1 schematically shows a lithographic apparatus according to an embodiment of the invention. Such an apparatus is configured to support an illumination system (light fixture) IL, a patterning device (eg mask) MA configured to condition a radiation beam B (eg UV radiation or any other suitable radiation). And a mask support structure (eg, mask table) MT that is configured and connected to a first positioning device PM configured to accurately position the patterning device according to certain parameters. In addition, the apparatus holds a substrate (e.g., a resist coated wafer) W and a substrate table (e.g., connected to a second positioning device PW) configured to accurately position the substrate according to certain parameters. Wafer table) (WT) or "substrate support". The apparatus is configured to project a pattern imparted to the radiation beam B by the patterning device MA on the target portion C of the substrate W (eg, including one or more dies) (eg For example, it further includes a refractive projection lens system (PS).

The illumination system can include various types of optical components, such as refractive, reflective, magnetic, electromagnetic, electrostatic or other types of optical components, or combinations thereof, to direct, shape, or control radiation.

The mask support structure supports the patterning device, ie carries its weight. It holds the patterning device in a way that depends on the orientation of the patterning device, the design of the lithographic apparatus, and other conditions such as, for example, whether or not the patterning device is maintained in a vacuum environment. The mask support structure can hold the patterning device using mechanical, vacuum, electrostatic or other clamping techniques. The mask support structure can be, for example, a frame or a table, which can be fixed or moved as needed. The mask support structure can ensure that the patterning device is in a desired position relative to the projection system, for example. Any use of the term "reticle" or "mask" herein may be considered synonymous with the more general term "patterning device."

The term "patterning device" as used herein should be broadly interpreted as referring to any device that can be used to impart a pattern to a cross-section of a radiation beam to create a pattern in a target portion of the substrate. It should be noted that the pattern imparted to the radiation beam may not exactly match the desired pattern at the target portion of the substrate, for example, if the pattern includes phase-shifting features or so-called assist features. Generally, the pattern imparted to the radiation beam will correspond to a particular functional layer of the device being created in the target portion, such as an integrated circuit.

The patterning device can be transmissive or reflective. Examples of patterning devices include masks, programmable mirror arrays, and programmable LCD panels. Masks are well known in lithography and include mask types such as binary, alternating phase shift and attenuated phase shift, as well as various hybrid mask types. An example of a programmable mirror array employs a matrix arrangement of small mirrors, each of which can be individually tilted to reflect incident radiation beams in various directions. The tilted mirror imparts a pattern to the radiation beam reflected by the mirror matrix.

The term "projection system" as used herein is suitable for other factors such as the use of exposure radiation used or the use of immersion liquid or the use of a vacuum, which is refractive, reflective, reflective and magnetic. It should be interpreted broadly to encompass any type of projection system, including electromagnetic and electrostatic optical systems, or any combination thereof. Any use of the term "projection lens" herein may be considered as synonymous with the more general term "projection system."

As shown, the device is transmissive (eg, employing a transmissive mask). Alternatively, the device may be reflective (eg, adopt a programmable mirror array of the type as mentioned, or adopt a reflective mask).

The lithographic apparatus may be of a type having two (dual stage) or more substrate tables or "substrate supports" (and / or two or more mask tables or "mask supports"). In such "multi-stage" devices, additional tables or supports may be used in parallel, or preparatory steps may be performed on one or more tables or supports while using one or more other tables or supports for exposure.

Further, the lithographic apparatus may be of a type that at least a part of the substrate can be covered with a liquid having a relatively high refractive index, for example water, to fill the space between the projection system and the substrate. In addition, the immersion liquid can be applied to other spaces of the lithographic apparatus, for example between a mask and a projection system. Immersion technology can be used to increase the numerical aperture of the projection system. The term "immersion" as used herein does not mean that a structure such as a substrate must be immersed in liquid, but rather that liquid is positioned between the projection system and the substrate during exposure.

Referring to FIG. 1, the illuminator IL receives a radiation beam from a radiation source SO. For example, when the radiation source is an excimer laser, the radiation source and the lithographic apparatus can be separate entities. In such cases, the radiation source is not considered to form part of the lithographic apparatus, and the radiation beam is a radiation source (SO), for example with the aid of a beam delivery system (BD) comprising a suitable directional mirror and / or beam expander. It is transferred to the illuminator IL from. In other cases, for example when the radiation source is a mercury lamp, the source may be an integral part of the lithographic apparatus. The radiation source SO and illuminator IL may be referred to as a radiation system along with the beam delivery system BD as needed.

The illuminator IL may include an adjuster AD configured to adjust the angular intensity distribution of the radiation beam. Generally, at least the outer and / or inner radial dimensions of the intensity distribution in the pupil plane of the illuminator (generally referred to as outer-σ and inner-σ, respectively) can be adjusted. Also, the illuminator IL may include various other components such as a concentrator IN and a condenser CO. The illuminator can be used to condition the radiation beam to have the desired uniformity and intensity distribution over the cross section.

The radiation beam B is incident on the patterning device (e.g., mask MA) held on the mask support structure (e.g., mask table MT), and is patterned by the patterning device. After going through the mask MA, the radiation beam B passes through the projection system PS, and the projection system PS focuses the beam onto the target portion C of the substrate W. With the aid of a second positioning device (PW) and a position sensor (IF) (e.g., interferometer device, linear encoder or capacitive sensor), the substrate table WT is, for example, in the path of the radiation beam B. It can be accurately moved to position the various target portions (C). Likewise, the first positioning device PM and another position sensor (not explicitly shown in FIG. 1) are in the path of the radiation beam B, for example after mechanical recovery from the mask library, or during a scan. Can be used to accurately position the mask MA. In general, the movement of the mask table MT can be realized with the help of a long-stroke module (schematic positioning) and a short-stroke module (fine positioning) that form part of the first positioning device PM. . Similarly, movement of the substrate table WT or " substrate support " can be realized using long-stroke modules and short-stroke modules that form part of the second positioner PW. In the case of a stepper (as opposed to a scanner), the mask table MT can be connected or fixed only to the short-stroke actuator. The mask MA and the substrate W may be aligned using the mask alignment marks M1 and M2 and the substrate alignment marks P1 and P2. The substrate alignment marks as shown occupy dedicated target portions, but they may be located in the space between the target portions (these are known as scribe-lane alignment marks). Similarly, in a situation where two or more dies are provided on the mask MA, the mask alignment marks can be positioned between the dies.

The illustrated device can be used in at least one of the following modes:

In the step mode, while the entire pattern imparted to the radiation beam is projected onto the target portion C at one time, the mask table MT or the "mask support" and the substrate table WT or "substrate support" are substantially stationary. Is maintained (single static exposure). Then, the substrate table WT or the "substrate support" is shifted in the X and / or Y direction so that different target portions C can be exposed. In step mode, the maximum size of the exposure field limits the size of the target portion C imaged with a single static exposure.

In the scan mode, while the pattern imparted to the radiation beam is projected onto the target portion C, the mask table MT or "mask support" and the substrate table WT or "substrate support" are synchronously scanned ( That is, single dynamic exposure). The speed and direction of the substrate table WT or the "substrate support" relative to the mask table MT or the "mask support" can be determined by the magnification (reduction ratio) and image reversal characteristics of the projection system PS. In scan mode, the maximum size of the exposure field limits the width of the target portion (in the non-scanning direction) in a single dynamic exposure, while the length of the scanning operation determines the height of the target portion (in the scanning direction).

In another mode, the mask table MT or "mask support" remains substantially stationary while maintaining a programmable patterning device, while the pattern imparted to the radiation beam is projected onto the target portion C The table WT is moved or scanned. In this mode, a pulsed radiation source is generally employed, and the programmable patterning device is updated as needed between successive radiation pulses during each scan or during the movement of the substrate table WT or "substrate support". This mode of operation can be easily applied to maskless lithography using a programmable patterning device such as a programmable mirror array of the type described above.

Combinations and / or variations of the use modes described above or entirely different use modes may also be employed.

Embodiments of the present invention will typically be used with a lithographic apparatus as described above, which lithographic apparatus further includes an alignment system (AS) configured to determine the location of one or more alignment marks present on the substrate. The alignment system is configured to perform a plurality of different alignment measurements, so as to obtain a plurality of measured alignment mark positions for the alignment marks considered. In this regard, performing different alignment measurements on a particular alignment mark means performing alignment measurements using different measurement parameters or properties. These different measurement parameters or properties may include using different optical properties, for example to perform alignment measurements. In one example, an alignment system applied to a lithographic apparatus according to the present invention includes an alignment projection system configured to project a plurality of alignment beams having different characteristics or parameters to alignment mark positions on a substrate and alignment positions based on beams reflected from the substrate. It may include a detection system configured to determine.

After the wafer is aligned and patterned during the exposure step, the wafer is calibrated to check the accuracy of the patterning, as described above. With reference to the position of the pattern within the previous layer on the wafer, the deviation between the actual (measured) position of the pattern and the desired position of the pattern is generally referred to as overlay error or simply overlay. The overlay error associated with the process is a good indicator of the quality of the process. Therefore, the overlay can be considered a quality parameter of the process. Overlay error is not the only relevant parameter indicating process quality. Focus error is also important when exposing a substrate (wafer). Overlay errors are typically associated with positional errors in the plane of the substrate and are therefore closely related to the performance of the alignment system. The focus error is associated with a position error perpendicular to the plane of the substrate and other measurement systems in the lithographic apparatus; It is closely related to the performance of the leveling system. The focus error can also be considered a quality parameter of the process.

Quality parameters are generally measured by a metrology system (eg, a scatterometer used to determine overlay errors). However, prediction may be used to derive quality parameters in addition to or alternative to using a metrology system. Context data (e.g., knowledge of which processing device was used to process the substrate of interest) and measurement data not directly related to quality data (e.g., wafer shape data measured to predict overlay error) ), Virtual metrology data representative of directly measured quality parameter data can be reconstructed. Often this concept is called "hybrid measurement"; It is a method of combining various data sources and, if necessary, simulation models to reconstruct measurement data associated with quality parameters of interest (overlay and / or focus error). Alternatively, a simulation model can be used to derive quality parameters based on context data and / or measurement data. For example, a simulation model can be used to mimic a lithography process based on pre-exposure measurements (leveling data, alignment data) and context data (reticle layout, process information). The simulation model itself can generate a map of quality parameter data (in this case the predicted overlay).

Within the meaning of this specification, the alignment system is operated with different operating parameters, including at least the difference in polarization or wavelength (frequency) content of the alignment beam. Thus, the alignment system can determine the position of the alignment mark using different operating parameters (eg, using an alignment beam with different color, ie frequency / wavelength). In general, the purpose of such alignment mark measurement performed by the alignment system is to determine or estimate the position of the target portion (e.g., target portion C shown in Fig. 1) of the next exposure process. The term "color" is commonly used to refer to a beam having a particular measurement parameter or set of measurement parameters. These different “color” beams are not necessarily beams with different colors in the visible spectrum, but can have different frequencies (wavelengths) or other properties, such as polarization.

To determine the position of these target portions, the position of the alignment marks, which can be provided, for example, to the scribe lane surrounding the target portion is measured. When the measured alignment mark position deviates from the nominal or expected position, it can be assumed that the target portion to which the next exposure is to be made also has an off-position. Using the measured position of the alignment mark, the actual position of the target portion can be determined or estimated, so that the next exposure can be performed at an appropriate position, so that the next exposure can be aligned to the target portion.

If the measured alignment mark position deviates from the expected or nominal position, it is possible to treat it as a result of deformation of the substrate. This deformation of the substrate can be caused, for example, by various processes that the substrate undergoes.

When a plurality of measured alignment mark positions are available and the position deviation, i.e., the deviation of the expected alignment mark position, is determined, this deviation can be approximated to a function, for example to describe the deformation of the substrate. This can be, for example, a two-dimensional function describing the deviations (Δx, Δy) as a function of the (x, y) position. Using this function, it is possible to determine or estimate the actual position of the target portion where the pattern needs to be projected.

The alignment position measurement performed by the alignment system can be disturbed by deformation or asymmetry of the alignment mark itself. In other words, due to the deformation of the alignment mark, an out-of-order alignment mark position measurement can be obtained compared to a situation in which the alignment mark is not deformed. If no action is taken, misalignment mark position may be incorrectly determined due to this misalignment mark position measurement. In addition, it has been observed that this type of deviation, ie, the position measurement deviated by the alignment mark deformation, depends on the operating parameters used. For example, when alignment mark positions are measured using alignment beams having different frequencies, this may lead to different results, i.e., different measurement positions for alignment marks.

As such, when the positions of the alignment marks are measured using a plurality of different operating parameters, eg alignment beams with different frequencies, different results are obtained, for example a plurality of different alignment mark positions are based on these measurements. Can be obtained.

As is evident from this, the result of the alignment measurement procedure should be an evaluation of the actual substrate deformation, that is, an evaluation of the actual position of the alignment mark, which can be used to determine the actual position of the target portion for subsequent exposure.

Taking into account the described effect, in particular the effect of the alignment mark deformation, the measured alignment mark position (eg, generally referred to as a “measurement parameter”), ie derived from different measurements (ie using different operating parameters) Alignment mark position is affected by both the (unknown) actual substrate deformation and the (unknown) mark deformation.

Both effects can lead to a deviation between the expected alignment mark position and the measured alignment mark position. As such, when positional deviations are observed, this may be caused by actual substrate deformation or alignment mark deformation or a combination thereof.

2 schematically shows several possible scenarios; It is assumed that three measurements M1, M2, and M3 are performed to determine the position of the alignment mark X. Fig. 2 (a) schematically shows the nominal or expected position E of the alignment mark and the measurement positions M1, M2, M3. Fig. 2 (a) also shows the actual position A of the alignment mark. As can be seen, none of the measurements performed provide an accurate representation of the actual position deviation (E-A).

Thus, the scenario shown in FIG. 2 (a) involves the actual displacement of the alignment mark (the actual alignment mark position A differs from the expected position E) in combination with the mark deformation causing the off-measurement.

Fig. 2 (b) shows an alternative scenario in which a difference is observed in the measurements M1, M2, M3, where the measurement parameter (in this case the measured position) is different from the expected value of the measurement parameter (e.g. position E), but in practice It is assumed that the position A coincides with the expected position E. In this scenario, the measurement will suggest that there is a positional deviation of the alignment mark, but in reality there is no positional deviation, that is, the position of the alignment mark is not affected by the substrate deformation.

Fig. 2 (c) schematically shows a third scenario in which all three measurements M1, M2, and M3 coincide with the actual position A. This scenario can occur when there is no alignment mark deformation affecting the measurement.

As will be apparent from the various scenarios shown, in order to reach a proper evaluation of the actual alignment mark position, it should be possible to distinguish the effect of mark deformation from the influence of substrate deformation.

The present invention provides a method for realizing the separation of these two effects. As an example, the lithographic apparatus may include a processing unit (PU) (see FIG. 1) to perform the necessary operations to separate the two effects. Therefore, such a processing unit (PU) may include a processor, a microprocessor, a computer, and the like.

3 illustrates the basic physical principles of the present invention (often referred to as the “optimal color weighting (OCW)” concept when the operating parameter of interest is the color of the alignment beam). As can be seen from the figure above, in an ideal situation, all colors used for multicolor measurements produce the same alignment position mark 30 for the marker 32 on the geometrically perfect substrate 34, but in practice it is described above. For different reasons different colors result in different position indications 36 relative to the actual (ie not perfect) substrate 38 as shown in the figure below.

4, how different colors can be affected by mark deformation, and as shown in the graph 40, the position error of each color may vary linearly according to the degree of deformation (the upper tilt angle of the mark). Can be assumed. In this case, it may be possible to determine a single color as providing the best indication of the actual mark position. However, as shown in FIG. 5, if there can be multiple different types of mark variations, no single color may provide the best approximation for all types of variations. In practice, it has been found that errors due to mark deformation not only scale differently for different colors (eg, wavelength or polarization), but also depend on the variation in layer thickness and the type of mark being measured. The OCW-based method aims to determine the optimal combination of all different colors used to minimize the effect of marker deformation on the determined marker position.

)이 정렬될 위치를 규정하도록 허용한다. '가중치'(wi)가 각각의 색상(xi)에 대해 추가되어, 프로세스에 대해 로버스트한 정렬된 위치(

)를 규정하기 위한 xi의 선형 조합에 도달하게 된다.Due to processing variations (PV) involving mark deformation, variations in the aligned position within the wafer and per wafer (PV) are shifted with respect to the color i . OCW solutions are far from the best single color, but all colors (

). 'Weight' ( wi ) is added for each color ( xi ), so that it is a robust aligned position for the process (

) To arrive at a linear combination of xi to qualify.

Thus, embodiments of the present invention solve the problem that the alignment marks are deformed by wafer-to-wafer process variation (PV), resulting in overlay errors in the product. OCW solutions involve:

· OCW position is specified by a linear weighted combination of alignment positions.

· Minimize process sensitivity of y to process variation by taking an optimal linear combination to minimize wafer-to-wafer overlay errors.

· The optimum weight for each color / polarization is determined using training using overlay data.

Preferably, overlay data is obtained from measurements made on wafers that have undergone similar processing, and both measurement and processing are performed using the same or similar equipment.

)를 결정하는 데에 사용되는 수학적 원리는 다음과 같다.Color weight based on overlay data (

The mathematical principle used to determine) is:

)에 걸친 가중된 합계이다.OCW position y is M measured color positions (

).

Given N measured marks,

를 최소화하기 위해 가중치를 최적화한다.· Decorrected overlay

Optimize weights to minimize.

(Reversed overlay = overlay-applied wafer alignment).

)는 다음의 식으로 구할 수 있다:· Then the color weight (

) Can be found by the following equation:

Regular OCW

,

와 같은 좌표들의 세트일 수 있다.

,

좌표의 세트는 선형 좌표일 수 있고, 즉 이러한 좌표는 두 개의 축(

축과

축)으로 표현되며, 이들 축은 서로 평행하지 않은 상이한 방향을 가진다.

와

축의 방향은 각각

와

좌표의 방향으로 지칭될 수 있다.

,

좌표는 직교 좌표 또는 직교 정규 좌표일 수 있다.

와

의 축은 마크와 독립적으로 정렬될 수 있다. OCW는 이전에 획득된 정렬 및 오버레이 데이터에 대해 트레이닝될 수 있다. 색상 가중치 계수가

와

방향에 대해 독립적으로 트레이닝되어 적용될 수 있다. 대안적으로 색상 가중치 계수는 조합된

와

에 대해 트레이닝될 수 있지만, 독립적인 트레이닝을 통해 오버레이 성능이 향상된다.As described above, OCW (Optimal Color Weighting) determines the optimal color weighting factor for alignment recipes to achieve minimal overlay variation of the pattern on the wafer. OCW can be determined at multiple locations on the mark. The position on the mark can be described using a two-dimensional representation, for example two-dimensional coordinates.

,

It may be a set of coordinates such as.

,

The set of coordinates can be linear, i.e. these coordinates are two axes (

Axis

Axis), and these axes have different directions that are not parallel to each other.

Wow

Each axis direction

Wow

It can be referred to as the direction of the coordinates.

,

The coordinates may be Cartesian coordinates or Cartesian regular coordinates.

Wow

The axis of can be aligned independently of the mark. OCW can be trained on previously acquired alignment and overlay data. Color weight coefficient

Wow

The direction can be independently trained and applied. Alternatively, the color weight coefficients are combined

Wow

Can be trained on, but overlay performance is improved through independent training.

Mathematically, one implementation of the determination of color weights for two independent directions can be as follows:

및

는 오버레이 성능을 최적화하도록 결정되어, 그 결과 OCW 결정된 위치

및

가 된다. 예를 들어 공칭 마크 위치, 웨이퍼 로드 및 웨이퍼 변형이 가중치 계수에 의해 영향을 받지 않도록 하기 위해, 색상 가중치에 대해 하나 이상의 추가 제약이 가해질 수도 있다. 이는 모든 색상 가중치의 합이 1이 되어야 한다는 요건, 즉

와

의 두 독립적인 방향 모두에 대해 가중치의 합이 100 %가 되어야 한다는 요건을 추가함으로써 달성될 수 있다.Weighting coefficient in the above equation

And

Is determined to optimize overlay performance, resulting in OCW determined location

And

Becomes For example, one or more additional constraints may be imposed on the color weights to ensure that the nominal mark position, wafer load and wafer deformation are not affected by the weighting coefficient. This means that the sum of all color weights should be 1, i.e.

Wow

This can be achieved by adding the requirement that the sum of the weights for both independent directions of should be 100%.

와

방향으로의 색상 가중치는 독립적으로 계산되지만, 위에서

와

에 대한 계산 세트의 표기법은 행렬 형식의 단일한 표기법으로 조합될 수 있다:In the above implementation

Wow

The color weight in the direction is calculated independently, but from above

Wow

The notation of the set of calculations for can be combined into a single notation in matrix form:

,

은 고유한 가중치 행렬(

)을 얻게 되고, 여기서 각각의

는

와

방향 좌표 양자 모두에 대한 색상 가중치를 포함한다. 상기 계산에 의해 기술되는 OCW의 구현예에서, 각각의 가중치 행렬

는 대각 행렬이고, 이는 주된 대각선에 위치하지 않은 요소가 0임을 의미한다. 위의 행렬 방정식에서 알 수 있는 바와 같이,

의 계산은

에 의존하는 항을 포함하지 않으며, 마찬가지로

의 계산은

에 의존하는 항을 포함하지 않고, 따라서 이러한 OCW의 구현에서 색상 가중치의 계산은

와

방향에 대해 독립적이다.Each color in the matrix notation above

,

Is a unique weighting matrix (

), Where each

The

Wow

Includes color weights for both direction coordinates. In the implementation of OCW described by the above calculation, each weight matrix

Is a diagonal matrix, which means that elements not located on the main diagonal are zero. As can be seen from the matrix equation above,

The calculation of

Does not contain dependent terms, and likewise

The calculation of

It does not contain terms that depend on, so the calculation of color weights in these OCW implementations

Wow

Independent of direction.

Segment OCW

,

좌표와 정렬되지 않은 경우, OCW는 상이한 각도들에 대해 상이한 효과들을 초래할 수 있고, OCW 결과는 상이한 웨이퍼들에 대해 일관성이 적어지며, 그 결과 웨이퍼-대-웨이퍼 (오버레이) 성능의 안정성을 감소시킨다.The alignment mark can include a structure having one or more preferential directions. For example, the mark may be a sieve BF mark, as shown in FIG. 14, comprising two gratings, the direction of which may not be aligned to the coordinates used for OCW. Sub-segmentation of the body BF mark, ie its pitch and direction

,

If not aligned with the coordinates, OCW can result in different effects for different angles, and the OCW result is less consistent for different wafers, resulting in reduced stability of wafer-to-wafer (overlay) performance. .

,

좌표와 정렬되지 않은 우선적인 방향(예컨대, 마크 구조체에 있어서 지배적인 방향)을 갖는 경우, 새로운 대안적인 좌표 세트를 사용하는 OCW를 수행하여 색상 가중치를 결정하는 것이 바람직할 수 있으며, 여기서 새로운 좌표 방향은 마크의 하나 이상의 우선적인 방향과 일치한다. 예를 들어, 체형 BF 마크의 경우, 도 14에 도시된 격자 방향은 새로운 좌표

,

를 결정하기 위해 우선적인 방향으로 사용될 수 있다. 따라서, 일부 구현예에서, OCW를 수행하는 것은 새로운 좌표 세트

,

를 결정하는 것을 포함할 수 있고, 여기서

,

방향은 마크의 우선적인 방향, 예를 들어 체형 BF 마크의 피치 방향에 정렬될 수 있다. 새로운 좌표

,

는 종전의 좌표

,

와 독립적으로 선택될 수 있다. 세그먼트별 OCW 라 지칭될 수 있는 이러한 구현예에서, 새로운 좌표는 위에서 정규 OCW 방법에 대해 설명된 바와 같이 OCW를 수행하기 위해 사용된다. 종전의 좌표 세트

,

에서 하나 이상의 결정된 OCW 위치 및 색상 가중치의 수식이 필요한 경우, 색상 가중치가 결정된 후에 새로운 세트

,

로부터 이전 세트

,

로의 좌표 변환이 수행될 수 있다.Alignment mark

,

If it has a preferential direction that is not aligned with the coordinates (e.g., the dominant direction in the mark structure), it may be desirable to determine the color weight by performing an OCW using a new alternative set of coordinates, where the new coordinate direction is Coincides with one or more preferential directions of the mark. For example, in the case of a body type BF mark, the grid direction shown in FIG. 14 is a new coordinate.

,

It can be used in a preferential direction to determine. Thus, in some implementations, performing OCW is a new set of coordinates.

,

It may include determining, where

,

The direction can be aligned with the preferred direction of the mark, for example the pitch direction of the body BF mark. New coordinates

,

Is the former coordinates

,

And can be independently selected. In this implementation, which may be referred to as segment-by-segment OCW, the new coordinates are used to perform OCW as described above for the regular OCW method. Previous coordinate set

,

If a formula of one or more determined OCW positions and color weights is needed, the new set after the color weights are determined

,

From previous set

,

Coordinate transformation to can be performed.

The mathematical principle used to determine color weights based on overlay data using segment-specific OCW is as follows:

방향에 대해 상대적인, 새로운 방향

및

의 법선의 각도를 φ₁ 및 φ₂ 라 한다. 각도 φ₁ 및 φ₂ 는 동일하지 않을 수도 있고, 서로간에 180 °의 각도를 형성하지 않을 수도 있으며, 즉

과

방향은 평행하지 않을 수도 있다. 각도 φ₁ 및 φ₂ 는 직교할 수도 있고, 서로 간에 다른 각도를 형성할 수도 있다.Positive of coordinates

New direction, relative to direction

And

The angle of the normal of is called φ ₁ and φ ₂ . The angles φ ₁ and φ ₂ may not be the same, and may not form an angle of 180 ° between each other, i.e.

and

The direction may not be parallel. The angles φ ₁ and φ ₂ may be orthogonal, or may form different angles from each other.

The relationship between the new and old coordinates can be expressed as follows:

과

를 사용하여 위에서 설명한 방법으로 수행되는데, 여기서

과

에 대한 색상 가중치는 서로 독립적으로 계산된다.OCW is a new set of coordinates

and

Is performed in the manner described above, where

and

The color weights for are calculated independently of each other.

로

과

를 표현하기 위해, 새로운 좌표계로부터 종전의 좌표계로의 변환이 다음 식에 따라 수행된다:Coordinate set

in

and

In order to represent, the conversion from the new coordinate system to the old coordinate system is performed according to the following equation:

This leads to the following equation.

좌표로 표현되는

는 다음과 같다.From this

Expressed in coordinates

Is as follows.

로 두 방향에 대해 독립적으로 결정된다. 새로운 좌표

로 표현될 때 OCW 위치

및

가 서로 독립적이라는 것은,

가

가중치 또는

위치에 의존하지 않으며,

가

가중치 또는

위치에 의존하지 않음을 의미한다. 결정된 OCW 위치가 종전의 좌표

로 표현될 때(여기서,

및

는

및

함수로 표현됨), 최적화된 위치

및

양자 모두는

와

두 방향에서 그리고 두 색상 가중치

과

로 색상의 가중된 조합으로 표현될 수 있다. 좌표

에 대해 가중치 합의 제약이 충족되는 경우, 좌표

로 표현된 해당 색상 가중치에 대한 제약도 충족된다: When using segment-by-segment OCW, the color weight is the new coordinate

Is determined independently for both directions. New coordinates

OCW position when expressed as

And

Is independent of each other,

end

Weight or

Does not depend on location,

end

Weight or

This means that it does not depend on location. The determined OCW position is the previous coordinate

When expressed as (here,

And

The

And

Expressed as a function), optimized position

And

Both are

Wow

Weight in two directions and two colors

and

It can be expressed as a weighted combination of colors. location

If the weighted sum constraint is satisfied, the coordinates

Constraints for the corresponding color weights expressed as:

방향이 0 °이고

방향이 90 ° 인 것으로 기술될 수 있다. 이러한 특정 예의 경우, 위에서 설명한 세그먼트별 OCW 알고리즘에 따르면, 좌표

와

로 표현되는 색상 가중치 행렬이 다음과 같이 표현될 수 있다:An example of such segmental OCW is provided below for a body-shaped BF mark with a preferred direction with angles φ ₁ = -45 ° and φ ₂ = 45 °. The previous coordinates are

Direction is 0 °

It can be described that the direction is 90 °. For this specific example, according to the segment-specific OCW algorithm described above, coordinates

Wow

The color weight matrix represented by can be expressed as:

와

로 표현되는 OCW 위치는 다음과 같이 표현될 수 있다:From these color weight matrices determined for the new coordinates based on the transformed coordinate angles of φ ₁ = -45 ° and φ ₂ = 45 °,

Wow

The OCW position represented by can be expressed as:

Extended OCW

좌표에 기초하는 정규 OCW의 예에서,

와

방향에 대한 색상 가중치

및

는 서로 독립적으로 결정된다. 세그먼트별 OCW에서는, 색상 가중치

및

이

좌표를 사용하여 서로 독립적으로 결정되지만, OCW 위치를 종전의 좌표

로 표현할 때,

및

는 나머지 방향과 관련되는 가중치

및

그리고 색상

및

에 무관하지 않다. 두 방법 모두, 독립적으로 두 방향으로 색상 가중치를 결정함으로써 최적의 색상 가중치를 결정할 때 2의 자유도를 제공한다.

In the example of a regular OCW based on coordinates,

Wow

Color weight for orientation

And

Are determined independently of each other. In segment-specific OCW, color weights

And

this

Determined independently of each other using coordinates, but the previous coordinates of the OCW position

When expressed as

And

Is the weight relative to the rest of the direction

And

And color

And

It has nothing to do with it. Both methods provide two degrees of freedom when determining optimal color weights by independently determining color weights in both directions.

In some implementations of OCW, the degree of freedom used to determine the OCW position is further increased to be greater than 2 for every color. This can be achieved by adding additional coefficients to the color weights to determine the OCW location. Specifically, the increase in degrees of freedom can be determined by adding separate color weight elements to one or more locations of the color weight matrix that are not on the main diagonal. The resulting color weight matrix contains three or more distinct color weights independent of each other. The color weights are independent because the value of one color weight does not depend on any one or more of the other distinct color weights.

및

의 함수로서 상호 연결된다.This approach differs from segment-by-segment OCW, which may have non-zero color weight matrix elements at locations other than the main diagonal, but each color weight matrix element only has two separate independent color weights.

And

It is interconnected as a function of

An implementation of OCW with 3 or more degrees of freedom is an extended OCW, in which two independent additional color weights are added to each color weight matrix to determine the OCW.

과

가 결정된다. 네 가지 별개의 색상 가중치

가 모두 서로 독립적으로 결정될 수 있다. 위의 행렬은 확장된 OCW에서 OCW 위치

,

를 계산하는 데에 사용된다:In the extended OCW, the above color weight matrix is used

and

Is determined. Four distinct color weights

Can all be determined independently of each other. The above matrix is the OCW position in the extended OCW.

,

Used to calculate:

In the extended OCW, a weighted sum constraint may also be applied, ie the following set of equations expressed in matrix form may have to be satisfied by color weights.

In non-matrix form, the extended OCW equation can be expressed as:

와

방향으로 또는

과

방향으로 피처를 가질 수 있으며, 이는 대응하는 및/또는 상관되는 변형에 의해 영향을 받은 것이다. 이러한 경우, 최적화된 색상 가중치 위치가 양 방향의 색상 위치에 의존하도록 하면 보다 정확한 결과를 얻을 수 있으므로, 확장된 OCW에 의해 최적화가 증대 및 개선되고 오버레이가 향상될 수 있다.If a mark comprises one, two or more, or all of the features across multiple directions, formed as part of the same process layer, deformations occurring in those process layers affect the features in some or all of these multiple directions Can be crazy. For example, Mark

Wow

In the direction or

and

It can have features in the direction, which is affected by the corresponding and / or correlated deformation. In this case, if the optimized color weight position is dependent on the color position in both directions, more accurate results can be obtained, and thus the optimization may be enhanced and improved by the extended OCW and the overlay may be improved.

The above method in which linear weighting is applied to measurement parameters (sort data) can be generalized to the mapping of measurement parameters. As mentioned above, this mapping is typically a linear weighted sum of measurement parameters. However, the present invention is not limited to a linear weighted sum, and a trained mapping as used in machine learning algorithms may be used.

The above method for optimal color weighting is not limited to the use of color as an operating parameter of interest, and different polarization modes derive different measurement parameters, for example as measured by an alignment sensor system (which measures the mark position). It can also be used to In addition, the degree of coherence may be considered as an operating parameter (if the degree of coherence is adjustable, temporal and / or spatial coherence can be adjusted, for example, by adjusting the laser characteristics). In addition, different measurement parameters may be considered, for example, if the operating parameter is color and the sensor system is a level sensor, the measurement parameter may be a focus value associated with the substrate to which the level sensor is measured. The quality parameter associated with level sensor measurement is the focus error that occurred during exposure of the substrate.

6A is a flow diagram schematically illustrating a wafer alignment, exposure and overlay measurement process. As shown, the wafer alignment scan in step 601 is performed using a number of different colors (operation parameters of the sensor system). In step 602, a color recipe is used to determine how different color measurements should be applied to determine the wafer marker position for aligning the wafer. In step 603 the wafer (or layer) is aligned by the device using the marker position determined from the previous step. In step 604, adjustments to wafer positioning are made based on data provided from measurements made on the wafer in the previous stage (ie, after the lower layer of the wafer has been processed). In step 605 the wafer is exposed to a processing stage (as described above with reference to FIG. 1). In step 606 overlay measurements are performed and the overlay data is provided to a training data processor (APC). In step 607, the APC evaluates the overlay data to determine any deviation from the expected location, which is used to provide correction for the next wafer / layer alignment.

6B is a flow diagram schematically showing another wafer alignment, exposure and overlay measurement process. The same steps described above for FIG. 6A have the same reference numbers in FIG. 6B. One difference is that in step 602 ', which takes place in the same place as step 602 in Figure 6a, instead of applying the same color recipe each time, the optimal color weight is used to determine the marker position for aligning the wafer. Is that Another difference is that, in step 607 ', more data is used as training data, instead of simply determining the alignment correction determined from the overlay. This data includes alignment measurement data 608 for each color obtained in step 601 and overlay data from a previous wafer measurement (step 606). Any other relevant data, such as stack data 611, can also be used for training data. The training data then provides the wafer positioning alignment correction in step 604, as well as updating (609) the optimal color weights used in step 602 ', and the substrate used in step 603. Used to update 610 the grid model.

As can be seen from FIG. 6B, while learning as the system is used, the weights for OCW measurement and alignment procedures are continuously updated. Thus, the main advantage of the above-described method is that any local device-specific variation in the operating parameters of the employed sensor system can be taken into account and corrected. The more sensor systems and devices used, the better the alignment.

The optimal color weighting (OCW) technique described herein combines alignment information from all wavelengths measured simultaneously and optimizes the set weight to be used for linear combinations of colors, such that the measured alignment position is minimally sensitive to mark deformation. To calculate. However, the properties of the stack over which the marker is etched or the stack covering the mark may change over time. When this change affects the optical properties (eg, refractive index) of the stack (s), the response of the mark to various operating parameters (color, polarization state) can also change accordingly. What this change in stack properties mean is that a particular set of optimal weights to be used for a linear combination of operating parameters may no longer be optimal.

Additionally, the mark deformation can change over time, for example due to a change in the properties of processing equipment (such as CMP tools and deposition equipment). The mark deformation can be, for example, a change in the sidewall angle of the mark and / or a change from the bottom tilt-like deformation to the top tilt deformation when etched into the substrate. The result of the change in mark deformation characteristics is that the previously determined optimal set of weights associated with a linear combination of colors is no longer optimal (eg, causing an over-optimal alignment of the substrate, which can cause overlay quality to be a problem). Yes).

In this specification, it is proposed to periodically determine the optimal set of weights that provide the least amount of overlay variation between substrates. If the calculated substrate-to-substrate variation of the quality parameter based on the determined set of weights deviates significantly from the previously observed wafer-to-wafer variation of these quality parameters, a change in one or more processes occurs within the semiconductor manufacturing process. It is possible. Alternately: if the new set of weights determined based on the newly observed substrate-to-substrate variance of the quality parameter deviates significantly from the previously determined set of weights, the likelihood that one or more process changes have occurred within the semiconductor manufacturing process. There is this.

In one embodiment, the state of the semiconductor manufacturing process comprises: a) determining an optimized value of the operating parameter (eg, a new set of weights associated with the color of the alignment), and b) determining the determined operating parameter as a reference operating parameter (eg For example, it is determined by comparing the previously determined set of weights associated with the color of the alignment), and c) determining the state based on this comparison.

In the case of a previously determined set of weights associated with the color of the alignment sensor, the reference motion parameter may be represented by a vector. For example, when the optimal weight for red is +1 and the optimal weight for green is -1, the reference operation parameter may be represented by vectors <1, -1>. This vector has no component parallel to its orthogonal complement <1,1>. For example, component vectors <1, -1> are associated with the top tilt deformation of the (etched) alignment mark and component vectors <1,1> are associated with the sidewall angle deformation of the (etched) mark. In the case of a process change, the new optimal weight set for red may be 1.2 and 0.6 for green. The new optimized value of the operating parameter can now be expressed as the vector 1.2 * <1, -1> + 0.6 * <1,1>. Certainly the vectors <1,1> are more relevant, indicating that the etched alignment marks (also) were deformed according to the sidewall angle profile. The semiconductor manufacturing process can be monitored by monitoring the vector representation of optimal operating parameters.

In one embodiment, the optimal set of weights is initially determined based on sensitivity to variations in quality parameters (substrate-to-substrate) and variations in operating parameters. Subsequently measured substrates can be further characterized by a set of orthogonal (or orthogonal normal) vectors representing the ratio of operating parameters present within the substrate-to-substrate variation of the measurement data. For example, if the alignment data associated with red shows wafer dependent variation f (w_i) (a function of wafer "w_i") and the alignment data associated with green shows -f (w_i), the vector representation <1, -1> It can be said that it exists in this measurement data. When a process change occurs, variations in the alignment data can change; For example, red can show wafer-dependent variation 3 * g (w_i), while green can show wafer-dependent variation g (w_i), whose vector representation is <3,1>. The vector <3,1> can be represented as projecting 1 * <1, -1,> on <1, -1> and 2 * <1,1,> on <1,1>. (<1, 1> is an orthogonal vector of <1, -1>). Therefore, due to process changes, components <1,1> were introduced in the fluctuation of measurement data that had not existed before. The optimal set of weights can now be optimized to suppress the strongest component (vector with maximum amplitude) observed in the corresponding set of measurement data. It is proposed to periodically project the newly measured operating parameters onto an orthogonal basis corresponding to the original calibration moment of the optimal weight set. If the amplitude distribution changes across the vector, it is possible that a process change has occurred.

In one embodiment, the state of the semiconductor manufacturing process is monitored by: a) obtaining an optimized value of the operating parameter as determined by an embodiment of the invention (the optimized value of the operating parameter is based on basis) as a first vector with individual operating parameters); b) obtaining variation across operating parameters of substrate-to-substrate variation of the measurement data; c) determining a new value of the operating parameter associated with the expected minimum substrate-to-substrate variation of the measurement data (the new value of the operating parameter is expressed as a second vector with individual operating parameters as a basis); And determining a state of the semiconductor manufacturing process based on the comparison of the first vector and the second vector.

In one embodiment, the following steps are performed: a) measurement data for a plurality of substrates and a plurality of operating parameters are obtained; b) a vector set representing a linear combination of motion parameters present in the measurement data is determined, and c) optionally: if a previously determined optimal weight set for the motion parameter is available, the previously determined optimal weight set is The projection of the vector set into the space defined by is subtracted from the vector set, d) the SVD (specific value decomposition) is applied to the vector set, e) the singular values obtained in the previous step are analyzed and ((almost) 0 The vector associated with the phosphorus singular value is particularly important because it represents a combination of motion parameters that do not contain information about mark deformation). f) A so-called “zero kernel” is calculated based on a vector associated with a singular value that is almost zero (the zero kernel is essentially a combination of motion parameters that are not affected by the initial mark deformation and / or initial stack (optical) characteristics. Expressing linear vector space).

In one embodiment, singular values are ranked and all singular values exceeding the threshold are filtered. The zero kernel is determined based on vectors associated with unfiltered singular values.

The change in processing state can be captured by projection of newly determined operating parameter data (associated with one or more substrates) on the determined zero kernel. When the characteristics of the mark deformation and / or the stack characteristics change, the projection of the new operating parameter data to the zero kernel changes, so the zero kernel can be used in a method of monitoring and / or determining a change in processing state.

In one embodiment, an initial vector set representing variations in measurement data and / or performance data is determined for a plurality of operational parameters. The vector represents a linear combination of operating parameters associated with reduced substrate-to-substrate variation of measurement and / or quality parameters. The determination procedure of the vector set is repeated for a plurality of different mark variations and / or stack characteristics. As such, the entire vector set describes the optimally selected operating parameter (combination) for a standard set of mark variations and / or stack characteristics. New measurement data are obtained periodically for a new substrate and a number of operating parameters. The newly acquired measurement data is used to obtain a new vector representation associated with new optimal operating parameters. The newly obtained vector representation is projected onto the initial vector set, and the relative weight associated with projection to each vector of the vector set is calculated. Relative weights are then ranked and relative weights below the threshold are considered zero (eg, components below a certain relevance are filtered out). In one embodiment, optimal operating parameters are monitored and the vector representation is decomposed into vectors belonging to the initial vector set. Ranking of components and application of threshold values is then performed. The relative strength of non-zero components can be thought of as the KPI of the semiconductor manufacturing process, how the marks etched from these components (vectors) are affected (e.g. top tilt, sidewall angle change, etc.), As a result, it is possible to estimate which process step has changed. For example, if the relevance of the vector <1, -1> changes significantly, it may mean that the top tilt characteristic of the alignment mark has changed, which is typically associated with drift in the CMP process step.

One application for implementing the above principle is to correct the so-called mark-to-device offset (MTD). This is an effect when the shift of the alignment mark to the nominal is different from the surrounding product features. This effect is caused by the presence of product features having a pitch that is significantly smaller than the alignment mark (i.e., feature width or spacing between features), so the light for exposure passes through different parts of the projection lens. In the case of lens aberrations, for example due to lens heating, this results in a pitch-dependent shift. This effect is not stable per wafer or lot since it depends on the lighting settings on a particular scanner and the history of product features, and therefore cannot be completely corrected by the APC system.

Proposed solutions to this problem include mark design and computational MTD (c-MTD). Mark design is limited by design rules, detectability and aberration sensitivity, while cMTD does not take into account processing impact.

Another method involves the use of sub-segmented marks. Here, additional marks with a finer pitch (similar to the pitch of the product feature) are included on the substrate. So-called sub-segmented marks consist of a coarse pitch mark (used for alignment) and a fine pitch mark (to comply with product design rules). The light for exposure to illuminate the fine pitch mark passes through the same projection lens portion as the light for exposure for product features. The pitch dependent shift or MTD caused by lens aberration results in lyso-induced mark asymmetry. This mark asymmetry results in a difference in alignment position for different colors of the alignment sensor.

The OCW principle can be applied to sub-segmented marks to determine weights for different colors (operation parameters) for sub-segmented marks, but in this case the tolerance for the effect of lens aberration for different colors Can be set. The training data used to determine the color weight is taken from the product overlay data.

It should be noted that, in general, OCW is applied to minimize the effect of process-induced mark asymmetry, and in particular, processing issues are suitable for the expected layer (mainly back-end optical lithography-BEOL). However, MTD is primarily a matter of front-end optical lithography-FEOL, where extreme lighting settings are used.

7 illustrates the MTD shift effect in three scenarios. In Fig. 7 (a), the effect of lens aberration Z on the overlay error (OVL) detected for a smaller pitch of the device (product) feature is represented by ΔD, which is substantially linearly proportional to lens aberration Z, ΔD = m1 + SdZ, where m1 is a constant offset and Sd is the device aberration sensitivity. In Fig. 7 (b), a larger pitch alignment marker shows the shift ΔM at the detected marker position (APD), which in turn is substantially linearly proportional to Z and is independent of illumination radiation (color), thus causing lyso-induced color asymmetry There will be no. In this case ΔM = m2 + SmZ, where m2 is a constant offset and Sm is the main marker aberration sensitivity. Since the illumination radiation is passing through different parts of the projection lens, ΔM does not have the same relationship as ΔD (ie, the gradient of the graph).

In Fig. 7 (c), the effect on the sub-segmented mark is shown. There is a color (wavelength) dependence, which results in a lyso-induced asymmetry (different measurements for different colors). Here, ΔM = m3 + SmZ + K (λ) [Sm-Ss] Z, Ss is segmented mark sensitivity, and K (λ) is stack sensitivity. However, as discussed above, by using the principle of OCW in which different weights are applied to different colors, it is possible to determine color weighted measurements that are very close to the actual overlay error, which takes into account the lens aberration effect that causes the MTD shift. will be.

To correct color weights so that they are not MTD sensitive, the calibration set may include a lens heating effect. If a mark with an intentional MTD shift is used to calculate the sensitivity of the alignment position to the MTD for each color, calibration data may be obtained from measurements performed using a designer segmented mark (DSM). . An exemplary calibration is schematically illustrated in FIG. 8. Another possibility is to compute the sensitivity of different colors using a computational method.

The same principle can be applied to the metrology marks used to measure the overlay, since these marks can also be sub-segmented and will experience similar mark-to-device offsets.

Another problem that can be solved by the OCW principles described herein relates to deformations that may occur across a substrate or wafer. So far, wafer alignment settings such as mark layout, color (s) and mark type are used for the entire wafer. However, mark asymmetry typically varies across wafers in different regions. Using the same color settings for wafer alignment of the entire wafer can result in greater wafer-to-wafer variation because it does not account for changing mark asymmetry. For example, in situations where wafer edge mark asymmetry is large, it is current practice to ignore the mark at the wafer edge if an unacceptably large error occurs.

 Thus, embodiments can provide optimization by the use of OCW such that wafer alignment is applied across the wafer surface area by applying different color weights to different areas or regions of the wafer. Thus, different color weights can reduce overlay errors in areas where the mark asymmetry is greater than the rest of the wafer, or in areas where the mark asymmetry is different from the rest of the wafer. In addition, if accurate color weights are applied per area / area (ie, edge to center), flexibility in optimizing wafer alignment layout is increased.

9 shows an alignment mark asymmetry plot across the wafer. This plot shows the variation between the four colors for the array of alignment marks on the wafer. The larger the arrow associated with the mark, the greater the degree of mark asymmetry. Mark asymmetry is clearly larger at the edge of the wafer. A similar effect can be seen in FIG. 10, where plot (a) shows a product overlay wafer map with active color near infrared (NIR). Plot 10 (b) shows an in-product overlay wafer map for the same wafer using two-color weighting. Plot 10 (c) shows the difference between plots 10 (a) and 10 (b), and it is clear that there is a significant difference between NIR and TCW. This difference is most important in the area distributed around the edge of the wafer. This demonstrates that the effect of mark asymmetry varies across the wafer. To investigate this behavior, TCW analysis was performed on the edge of the wafer and the center of the wafer to determine the best color weights for the two areas on the wafer.

An improvement in wafer alignment performance can be seen by applying two-color weighting (TCW) with reference to only two colors. There are two graphs in Figure 11, one for the mark at the edge of the wafer and the other for the mark at the center. Each graph shows how the overlay error changes for two orthogonal directions (X-overlay and Y-overlay) parallel to the wafer surface as a function of different two-color weighting combinations. In this case, the two colors are green (ie, visible light at approximately 510 nm) and near infrared (NIR). The two-color weights are -1 to 2 for green and 2 to -1 for NIR. The total weight is always 1.

Fig. 11 shows that the optimal color weight (if the overlay error is minimal) is different for the edge and center of the wafer. For the edge of the wafer, the combination of green with weight -1 and NIR with weight 2 provides the best performance, whereas for the center of the wafer, the combination of green with weight -0.4 and NIR with weight 1.4 is the best. Provides performance. The difference between the weights is 20%.

It will be understood that larger improvements can be realized by using more color / color weights.

Applying color weights (ultimately per mark) to different areas of the wafer reduces the effect of mark asymmetry at the edge as well as the center of the wafer. There are different color settings (color, weight) for each zone of the wafer to which this method can be applied. In this way, the user can optimize wafer alignment strategies for different areas of the wafer and perform fine adjustments to wafer alignment to reduce wafer-to-wafer variation during the process.

In the wafer processing method described above, two sets of overlay corrections that affect overlay wafer-to-wafer variation are applied. One correction is due to alignment. Before the wafer is exposed, the alignment marks on the wafer are measured with a scanner alignment sensor and a set of corrections are calculated for the alignment measurements using a predefined alignment model. Then, correction during exposure is applied to the wafer. The remaining corrections are wafer-specific overlay process corrections. After exposure of the wafer, it is sent to an overlay metrology tool to measure the overlay mark. The measured overlay is used to calculate the set of corrections used to set the subsequent exposure. This correction can be done per wafer.

Each of the two correction methods has advantages and disadvantages. Alignment is always wafer-by-wafer and real-time correction, but due to limited measurement time, the number of alignment marks is limited and may be adversely affected by alignment mark asymmetry. Wafer-by-wafer correction has more correction capability-can measure many overlay marks per wafer-correction is usually not done in 'real time': for example, a time filter is used for run-to-run control .

Alignment and wafer-specific overlay correction have the same goal of reducing overlay wafer-to-wafer variation. The setup of the two methods is performed separately: In the case of alignment correction, the setup is based on the optimization of the alignment model, sampling and color; On the other hand, in the case of overlay correction, setup is based on optimization of overlay model, sampling, measurement frequency, etc. However, these independent setups do not take into account the interaction between alignment and overlay. Therefore, the setups may not be optimal.

This is schematically illustrated in FIG. 12. The figure at the top shows the process of determining the OCW for alignment correction using several different colors, models and layouts. The overlay measurement is used to evaluate the optimal combination of color, model and layout, and as described above, an optimal color weight is determined for the alignment correction process. The diagram at the bottom shows the corresponding process for correcting the overlay using various frequencies, models and layouts. Overlay measurements are used to evaluate the optimal combination of frequency, model and layout, and again the optimal color weights are determined for the alignment correction process. The optimal color weight will be different for the two correction procedures.

In an embodiment of the present invention, as shown in Figure 13, the evaluation of the overlay is used to provide one evaluation that determines the optimal combination for both alignment correction and overlay correction. Therefore, by simultaneously evaluating the settings based on the same overlay measurement, a single combination of alignment setting parameters and overlay setting parameters, which is optimal for the combination of alignment and overlay correction, is determined, but only one or the rest of the alignment correction and overlay correction It may turn out to be different from the setting determined for bay.

The OCW (Optimal Color Weighting) method described above is a very effective method of minimizing the impact of processing artifacts (eg, affecting the mark) on the control of the lithographic apparatus. However, it is not necessary to use the OCW method in all cases. a) The wafer-to-wafer quality parameter (e.g. overlay) variation caused by processing may be small or uncorrectable (in this case the processing-induced variation will not be present in the final result) and / or b ) Marks are robust enough for processing artifacts and reading marks (or stacks for level sensor readings) for any selected operating parameter may give similar results. Evaluation of the benefits of OCW may need to be performed for each layer on the substrate that will go through the semiconductor manufacturing process. In one embodiment, for a set of layers of interest, i) a wafer-to-wafer variation of a correctable error associated with a quality parameter, and ii) a wafer-to-wafer variation of measurement data variation across operating parameters is determined do. Layers in which wafer-to-wafer variation of measurement data variation and / or wafer-to-wafer variation of correctable error is less than a certain threshold may be excluded from the OCW framework.

In one embodiment, a layer associated with a substrate comprises: a) a first substrate-to-substrate variation of quality parameters associated with this layer; And b) a second substrate-to-substrate variation of the variation between measurement parameters associated with this layer over the selected operational parameters.

In one embodiment, this layer is selected for application of the OCW algorithm when the first substrate-to-substrate variation and the second substrate-to-substrate variation exceed thresholds.

In one embodiment, the first substrate-to-substrate variation and the second substrate-to-substrate variation consist of the KPI of the semiconductor process. These KPIs are monitored in a timely manner, for example, by displaying them on one plot (the x-axis is the value of the first KPI associated with the first substrate-to-substrate variation, and the y-axis is the second substrate-to-substrate variation. It is the value of the second KPI associated with).

If both the first and second KPIs exceed the threshold, a decision can be made to determine a new OCW recipe by recalculating the optimal operating parameters that are configured to yield the minimum substrate-to-substrate variation of the quality parameters. As the fluctuation of the quality parameter and the variability of the measurement data across the operating parameters are combined, a) the measurement is clearly influenced by the change in processing, and b) the performance (expressed as the quality parameter) is a problem as a result. Can conclude. Thus, recalculation of optimal operating parameters will probably improve performance (eg, reduce the first substrate-to-substrate variation) and is probably meaningful.

Alternatively, the first and second KPIs can be combined into a single KPI. In this case, if a single KPI exceeds the threshold, a decision can be made to determine a new OCW recipe.

If only the second KPI exceeds the threshold, the mark may be affected by a change in processing, but the performance is not significantly reduced. It may be concluded that the current OCW settings (recipe including optimal operating parameter settings) are suitable for controlling the changed processing.

If only the first KPI exceeds the threshold, process induced mark deformation and / or stack property changes are not responsible for the observed changes in quality parameter variability. Therefore, recalculating the optimal operating parameters makes little sense.

Further embodiments of the invention are presented as a list of the numbered clauses below:

1. A method for determining one or more optimized values of operating parameters of a sensor system configured to measure properties of a substrate,

Determining quality parameters for a plurality of substrates;

Determining, for a plurality of values of the operating parameter, measurement parameters for the plurality of substrates obtained using the sensor system;

Comparing the substrate-to-substrate variation of the quality parameter and the substrate-to-substrate variation of the mapping of the measurement parameter; And

And determining one or more optimized values of the operational parameters based on a comparison.

2. The method of claim 1, wherein the mapping is a weighted sum, a nonlinear mapping or a trained mapping based on a machine learning technique, to determine one or more optimized values of operating parameters of the sensor system.

3. The method of claim 1, further comprising determining an optimal set of weighting factors for weighting a measurement parameter associated with a first value of the operating parameter and a measurement parameter associated with a second value of the operating parameter based on the comparison. A method for determining one or more optimized values of operating parameters of a sensor system, comprising.

4. The method according to any one of clauses 1 to 3, wherein the quality parameter is an overlay or focus parameter, one or more optimized values of operating parameters of the sensor system.

5. The sensor system according to any one of clauses 1 to 4, wherein the measurement parameter is an out-of-plane deviation of a location of a feature provided on the plurality of substrates or a location on the substrate. A method for determining one or more optimized values of operating parameters.

6. The method according to any one of clauses 1 to 5, wherein the operating parameter is a parameter associated with the light source from the sensor system.

7. The method according to clause 5, wherein the operating parameter is the wavelength, polarization state, spatial coherence state or temporal coherence state of the light source, to determine one or more optimized values of the operating parameters of the sensor system.

8. The method of any one of clauses 1 to 7, wherein the quality parameter is determined using a metrology system.

9. The provision of any one of clauses 1 to 6, wherein the quality parameter is determined using a simulation model that predicts the quality parameter based on any of context information, measurement data, reconstructed data, and hybrid metrology data. A method for determining one or more optimized values of operating parameters of a sensor system.

10. As a method for determining the state of a semiconductor manufacturing process,

 Determining an optimized value of the operating parameter according to claim 1;

Comparing the determined operating parameter with a reference operating parameter; And

And determining the status based on a comparison.

11. A method of optimizing measurement data from a sensor system configured to measure the properties of a substrate,

Obtaining overlay data for a plurality of substrates, the overlay represents a deviation between the measured position and the expected position of the alignment marker on the substrate and includes a plurality of measurements of alignment marker positions made by the sensor system, the plurality of Each measurement uses different operating parameters of the sensor system-;

Based on the overlay data obtained, and for each of the different operating parameters, use the operating parameters such that weighted adjustments to the measurements made by the sensor system are combined for all of the different operating parameters to minimize overlay. And determining weights for adjusting the obtained measurements.

12. The method of clause 11, wherein the operating parameter is a parameter associated with the radiation source from the sensor system.

13. The method of claim 12, wherein the operating parameter is a wavelength, polarization state, spatial coherence state, or temporal coherence state of the light source.

14. The method of any of clauses 1-9, wherein determining one or more optimized values of the operating parameter based on the comparison is performed for different zones of the substrate.

15. The method of clause 14, wherein the different zones include a zone proximate the edge of the substrate and a zone proximate the center of the substrate.

16. The method of clause 14 or 15, wherein each zone comprises one or more alignment marks applied to the substrate.

17. The method according to clause 14 or 15, wherein each zone corresponds to an individual alignment mark among a plurality of alignment marks applied to the substrate.

18. The provision of any of clauses 1 to 9, wherein the measurement parameter is the measured position of the mark, the quality parameter is a mark-to-device shift, and the optimized value of the operating parameter is substrate-to- A method for determining one or more optimized values of operating parameters of a sensor system, which are determined to optimize the quality parameters to minimize substrate variations.

19. The article of clause 18, wherein the operating parameter is a parameter associated with the radiation source, the radiation from the source is directed to the substrate, and an optimized value of the operating parameter applies weights to adjust the measurements obtained using the operating parameter. By being determined.

20. The method of clause 19, wherein radiation from a source directed to the substrate is received by the sensor system after targeting the substrate.

21. The method of clause 19, wherein weighting comprises a lens heating effect of a lens used to direct radiation to the substrate and / or receive radiation by a sensor system.

22. The clause of any of clauses 18 to 21, having a sub-segmented mark applied with an intentional mark-to-device shift to determine the sensitivity of the operating parameter to the mark-to-device shift. And determining a weight for an operating parameter for measuring the sub-segmented mark using the measurement obtained from the substrate.

23. The article of any of clauses 1-9, in order to optimize the operating parameters of the metrology system used to control the processing of the substrate, the sensor system is configured to measure the first characteristic of the substrate prior to processing. A first sensor system associated with a first measurement system configured and a second sensor system associated with a second measurement system configured to measure a second characteristic of the substrate after processing, the method comprising:

Determining, for a plurality of values of the operating parameter, a first set of measurement parameters for the plurality of substrates obtained using the first sensor system;

For a plurality of values of the operating parameter, determining a second set of measurement parameters for the plurality of substrates obtained using the second sensor system; And

Comparing the substrate-to-substrate variation of the quality parameter and the substrate-to-substrate variation of the mapping of the measurement parameter to each of the first set and the second set of measurement parameters,

Determining one or more optimized values of the operational parameters includes simultaneously optimizing a first set of operational parameters associated with the first measurement system and a second set of operational parameters associated with the second measurement system. And optimization mitigates the substrate-to-substrate variation of the second characteristic, a method for determining one or more optimized values of operating parameters of a sensor system.

24. The method of clause 23, wherein the quality parameter is an overlay determined from the measured second characteristic of the substrate after processing.

25. The method of clause 1, wherein the quality parameter and the measurement parameter are associated with a particular layer associated with a plurality of substrates.

26. The article of clause 25, wherein the specific layer comprises: i) a first substrate-to-substrate variation of the quality parameter associated with the particular layer; And ii) a second substrate-to-substrate variation of the variation between the measurement parameters associated with the particular layer.

27. The method of clause 26, wherein the particular layer is selected when the first substrate-to-substrate variation and the second substrate-to-substrate variation exceed a threshold.

As a method for determining the state of the semiconductor manufacturing process,

Obtaining an optimized value of the operating parameter using a method according to any one of clauses 1 to 27;

Obtaining, for a plurality of values of the operating parameter, measurement parameters for additional substrates obtained using the sensor system;

Determining a new value of the operating parameter associated with the expected minimum substrate-to-substrate variation of the measurement data; And

And determining a state of a semiconductor manufacturing process based on a comparison of the new value with an optimized value of the operating parameter.

29. The sensor of clause 1, wherein the optimized value of the operating parameter comprises a set of first values associated with a first coordinate of the measurement parameter and a set of second values associated with a second coordinate of the measurement parameter. A method for determining one or more optimized values of operating parameters of a system.

30. In accordance with Article 29,

Determining third coordinates parallel to the first preferred direction of the mark;

Determining a fourth coordinate parallel to the second preferred direction of the mark;

Determining a set of third optimized values of operating parameters associated with the third coordinates and a set of fourth optimized values of operating parameters associated with the fourth coordinates;

Determining a transformation from the third and fourth coordinates to the first and second coordinates; And

And using the determined transform, transforming the determined optimized value of the operating parameter at the third and fourth coordinates to an optimized value of the operating parameter at the first and second coordinates.

31. The method of clause 29, wherein the first value of the operating parameter is optimized independently of the second value of the operating parameter.

15 is a block diagram illustrating a computer system 100 that may be helpful in implementing the methods and flows disclosed herein. The computer system 100 includes a bus 102 or other communication mechanism for communicating information, and a processor 104 (or several processors 104 and 105) coupled with the bus 102 to process the information. Computer system 100 utilizes main memory 106, such as random access memory (RAM) or other dynamic storage device, coupled to bus 102 to store information and instructions to be executed by processor 104. The main memory 106 can also be used to store temporary variables or other intermediate information while an instruction to be executed by the processor 104 is being executed.The computer system 100 is static information about the processor 104. And a read-only memory (ROM) 108 or other static storage device coupled to the bus 102 to store the instructions. For this purpose, a storage device 110 such as a magnetic disk or optical disk is provided and coupled to the bus 102.

The computer system 100 may be coupled to a display 112 such as a cathode ray tube (CRT) or flat panel or touch panel display via a bus 102 to display information to a computer user. An input device 114 comprising alphanumeric keys and other keys is coupled to the bus 102 to communicate information and command selection to the processor 104. Another type of user input device is cursor control 116, such as a mouse, trackball, or cursor direction key, for communicating instruction information and command selection to processor 104 and controlling cursor movement on display 112. . Such input devices typically have two degrees of freedom in two axes, the first axis (eg x) and the second axis (eg y), allowing the device to specify a position in the plane. A touch panel (screen) display can also be used as an input device.

According to one embodiment, portions of the process may be performed by computer system 100 in response to processor 104 executing one or more sequences of one or more instructions stored in main memory 106. These instructions can be read from other computer-readable media, such as storage device 110, into main memory 106. When executing the sequence of instructions included in the main memory 106, the processor 104 performs the process steps described herein. In order to execute a sequence of instructions contained in main memory 106, one or more processors in multiple processing devices may be employed. In other embodiments, wired circuitry may be used in place of or in combination with software instructions. Accordingly, the description herein is not limited to any particular combination of hardware circuitry and software.

The term "computer-readable medium" as used herein refers to any tangible medium involved in providing instructions to the processor 104 to be executed. Such media may take many forms, including, but not limited to, non-volatile media, volatile media, and transmission media. Non-volatile media include, for example, optical or magnetic disks such as storage device 110. Volatile media include dynamic memory, such as main memory 106. Transmission media include coaxial cables, copper wiring, and fiber optics, including wires that include bus 102. Transmission media may take the form of sound or light waves, such as those generated during radio frequency (RF) and infrared (IR) data communications. Common forms of computer-readable media include, for example, floppy disks, flexible disks, hard disks, magnetic tapes, and any other magnetic media, CD-ROMs, DVDs, any other optical media, punch cards, paper Tape, any other physical medium with a pattern of holes, RAM, PROM, and EPROM, FLASH EPROM, any other memory chip or cartridge, a carrier wave as described below, or any other computer readable medium.

Various forms of computer readable media may be involved in passing one or more sequences of one or more instructions to processor 104 for execution. For example, instructions may initially be held on a magnetic disk of a remote computer. The remote computer can load the commands into its dynamic memory and send the commands over the telephone line using a modem. A modem local to the computer system 100 receives data from the telephone line and converts this data to infrared signals using an infrared transmitter. An infrared detector coupled to the bus 102 can receive data carried in the infrared signal and place the data on the bus 102. Bus 102 transfers data to main memory 106, and processor 104 retrieves and executes instructions therefrom. Instructions received by the main memory 106 may optionally be stored on the storage device 110 before or after execution by the processor 104.

The computer system 100 preferably further includes a communication interface 118 coupled to the bus 102. Communication interface 118 provides a two-way data communication coupling to network link 120 coupled to local network 122. For example, the communication interface 118 can be an integrated information network (ISDN) card or modem for providing a data communication connection to a corresponding type of telephone line. As another example, the communication interface 118 can be a LAN card for providing a data communication connection to a compatible local area network (LAN). A radio link may be implemented. In any such implementation, communication interface 118 transmits and receives electrical, electromagnetic or optical signals carrying digital data streams representing various types of information.

The network link 120 typically provides data communication over one or more networks to other data devices. For example, the network link 120 can provide a connection to the data equipment operated by the host computer 124 or the Internet service provider (ISP) 126 via the local network 122. ISP 126 now provides data communication services over a worldwide packet data communication network, commonly referred to as "Internet 128". Both the local network 122 and the Internet 128 use electrical, electromagnetic, or optical signals that carry digital data streams. Signals passing through various networks, which carry digital data to or from computer system 100, and signals through communication interface 118 on network link 120 are exemplary forms of carriers carrying information.

Computer system 100 may transmit messages and receive data including program code, via network (s), network link 120, and communication interface 118. In the example of the Internet, the server 130 may transmit the requested code for the application program through the Internet 128, the ISP 126, the local network 122, and the communication interface 118. One such downloaded application may provide lighting optimization of an embodiment, for example. The received code may be executed by processor 104 when received, and / or stored in storage device 110, or other non-volatile storage, to be executed at a later time. In this way, the computer system 100 can obtain the application code in the form of a carrier wave.

Embodiments of the present specification may be implemented in hardware, firmware, software, or any combination thereof. Embodiments of the present disclosure may also be implemented as instructions stored on machine readable media that can be read and executed by one or more processors. The machine-readable medium can include any mechanism for storing or transmitting information in a form readable by a machine (eg, a computing device). For example, a machine-readable medium may include read-only memory (ROM); Random access memory (RAM); Magnetic disk storage media; Optical storage media; Flash memory devices; Electrical, optical, acoustic, or other forms of propagation signals (eg, carrier waves, infrared signals, digital signals, etc.), and the like. Further, firmware, software, routines, and instructions may be described herein as performing specific operations. However, it should be appreciated that this description is for convenience only, and that the operation actually originates from a computing device, processor, controller, or other device executing firmware, software, routines, instructions, and the like.

In the block diagram, the illustrated components are shown as discrete functional blocks, but embodiments are not limited to an organized system as shown in the functionality described herein. The functionality provided by each of the components may be provided by organized software or hardware modules, unlike those shown in the drawings, for example such software or hardware may be intermixed, co-coupled, duplicated, separated, distributed (eg For example, within a data center or geographically), or otherwise. The functionality described herein can be provided by one or more processors of one or more computers executing code stored on a tangible, non-transitory machine-readable medium. In some cases, a third-party content delivery network may host some or all of the information that is delivered across the networks, in which case it is stated that the information (eg, content) is supplied or otherwise provided In, such information can be provided by sending an instruction to retrieve the information from the content delivery network.

Unless expressly stated otherwise, a description utilizing terms such as “processing”, “computing”, “calculating”, “determining”, etc., throughout the specification, as is apparent from the specification, or as a dedicated computer or similar dedicated electronic processing / computing device. It is understood that it refers to the operation or process of a particular device.

The reader should understand that the invention describes several inventions. Rather than separating such inventions into multiple individual patent applications, the applicant grouped these inventions into a single document, as the technical gist associated therewith could have economics in the application process itself. However, the distinct advantages and aspects of these inventions should not be combined. In some cases, the embodiments address all of the deficiencies pointed out herein, but these inventions are useful independently, and some embodiments only solve a subset of these problems, or will be apparent to those skilled in the art having reviewed the specification. It should be understood that it provides other advantages not mentioned. Due to cost constraints, some of the inventions disclosed herein are not currently claimed, and may be claimed in subsequent applications, such as continuing applications, or by amending current claims. Likewise, due to space constraints, the content section and summary of the invention herein should not be considered to include an exhaustive listing of all these inventions or all aspects of these inventions.

The detailed description and drawings are not intended to limit the invention to the specific forms disclosed, and vice versa, the invention is intended to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the invention as defined in the appended claims. It should be understood that it is intended to cover the examples.

Variations and alternative embodiments of various aspects of the present invention will become apparent to those skilled in the art upon reference to this specification. Accordingly, these detailed descriptions and drawings are intended to be illustrative only and should be construed to teach those skilled in the art the general way of practicing the present invention. It should be understood that the forms of the invention shown and described herein are to be regarded as examples of embodiments. As will be apparent to those skilled in the art upon encountering this description of the present invention, elements and materials may replace those illustrated and described herein, and parts and processes may be reversed, reordered or omitted, and specific Features can be utilized independently, and features of embodiments or embodiments can be combined. Elements described herein may be modified without departing from the spirit and scope of the invention as described in the claims that follow. Annotations in this specification are for organizational purposes only and are not intended to be used to limit the scope of the invention.

When used throughout this specification, the word "may" is used in a permissive sense (ie, meaning there is a possibility), rather than in a compulsory meaning (ie, means must). The words "comprising", "comprising", and "includes", and the like mean that they are included, but not limited to. As used throughout this specification, the singular forms “one”, “one” and “that”, etc., include a plurality of indicators unless the context clearly indicates otherwise. Thus, referring to an “an” element or an “a” element, for example, refers to two, even though different terms and phrases are used for one or more elements, such as “one or more”. It includes a combination of the above elements. The term “or”, unless indicated otherwise, is non-exclusive, ie, encompasses both “and” and “or”. Terms that describe a conditional relationship, such as "Y in response to X," "For X, Y is", "X plane, Y is," "If X, Y is", etc. It includes a causal relationship that is a necessary causal condition of a result, a prerequisite is a sufficient causal condition, or a causal condition in which a prerequisite contributes to a result. For example, "state X occurs when condition Y is achieved." It is a generic term for " X occurs only for " and " X occurs for Y and Z ". This conditional relationship is not limited to the result immediately following the precondition being achieved, because some results may be delayed, and in a conditional statement, the precondition is linked to the result, for example It is related to the possibility of occurrence. A statement that a plurality of attributes or functions are mapped to a plurality of objects (eg, one or more processors performing steps A, B, C, and D), unless otherwise indicated, all such attributes or functions are Both being mapped to an object and a subset of attributes or functions mapped to a subset of attributes or functions (e.g., all processors each perform step AD, and processor 1 performs step A) , Processor 2 performs part of steps B and C, and processor 3 performs part of steps C and D). Furthermore, unless stated otherwise, a statement that one value or action "bases on" another condition or value is when the condition or value is the only argument and the condition or value is one of several factors. It covers both. Unless otherwise indicated, statements that "each" instance of a set has some properties should not be construed to exclude cases where some or the same or similar elements of a larger set do not have such properties. That is, each does not necessarily mean each and every.

To the extent that certain U.S. patents, U.S. patent applications, or other documents (e.g., papers) are incorporated and incorporated by reference, the contents of these U.S. patents, U.S. patent applications, and other documents are incorporated herein by reference, and It is incorporated herein by reference in the absence of a conflict between the drawings. In the event of such conflict, any such conflicting content in this U.S. Patent, U.S. Patent Application, and other documents incorporated herein by reference is specifically not incorporated herein by reference. Although specific embodiments of the invention have been described above, it will be understood that such embodiments may be practiced differently than described.

Claims (15)

A method for determining one or more optimized values of operating parameters of a sensor system configured to measure a property of a substrate,
Determining quality parameters for a plurality of substrates;
Determining, for a plurality of values of the operating parameter, measurement parameters for the plurality of substrates obtained using the sensor system;
Comparing the substrate-to-substrate variation of the quality parameter and the substrate-to-substrate variation of the mapping of the measurement parameter; And
And determining one or more optimized values of the operational parameters based on a comparison. The method of claim 1, wherein the mapping is a weighted sum, a nonlinear mapping, or a trained mapping based on machine learning techniques.  The method of claim 1, wherein the quality parameter is an overlay or focus parameter. The method of claim 1, wherein the measurement parameter is an out-of-plane deviation of a position of a feature provided on the plurality of substrates or a position on the substrate, and determines one or more optimized values of operating parameters of the sensor system Way to do. The one or more optimized values of the operating parameters of the sensor system according to claim 1, wherein the operating parameters are parameters associated with the wavelength, polarization state, spatial coherence state or temporal coherence state of the light source from the sensor system. How to decide. The one or more optimized values of operating parameters of a sensor system according to claim 1, wherein the quality parameters are determined using a simulation model and / or a measurement system that predicts the quality parameters based on context information and / or measurement data. How to determine. The sensor system of claim 1, wherein the optimized value of the operating parameter comprises a set of first values associated with a first coordinate of the measurement parameter and a set of second values associated with a second coordinate of the measurement parameter. A method for determining one or more optimized values of operating parameters. As a method for determining the state of the semiconductor manufacturing process,
Determining an optimized value of the operating parameter according to claim 1;
Comparing the determined operating parameter with a reference operating parameter; And
And determining the status based on a comparison. The method of claim 1, wherein determining one or more optimized values of the operating parameters based on the comparison is performed for different zones of the substrate to determine one or more optimized values of operating parameters of the sensor system. Way for. The quality parameter of claim 1, wherein the measurement parameter is a measured position of a mark, the quality parameter is a mark-to-device shift, and an optimized value of the operating parameter is to minimize substrate-to-substrate variation. A method for determining one or more optimized values of an operating parameter of a sensor system, which is determined to optimize. The sensor system of claim 1, wherein the sensor system is configured to measure a first characteristic of the substrate prior to processing to optimize operating parameters of the metrology system used to control the processing of the substrate. A second sensor system associated with a sensor system and a second measurement system configured to measure a second characteristic of the substrate after processing, the method comprising:
Determining, for a plurality of values of the operating parameter, a first set of measurement parameters for the plurality of substrates obtained using the first sensor system;
For a plurality of values of the operating parameter, determining a second set of measurement parameters for the plurality of substrates obtained using the second sensor system; And
Comparing the substrate-to-substrate variation of the quality parameter and the substrate-to-substrate variation of the mapping of the measurement parameter to each of the first set and the second set of measurement parameters,
Determining one or more optimized values of the operational parameters includes simultaneously optimizing a first set of operational parameters associated with the first measurement system and a second set of operational parameters associated with the second measurement system. And optimization mitigates the substrate-to-substrate variation of the second characteristic, a method for determining one or more optimized values of operating parameters of a sensor system. The method of claim 1, wherein the quality parameter and the measurement parameter are associated with a specific layer associated with a plurality of substrates, the specific layer:
i) a first substrate-to-substrate variation of the quality parameter associated with the particular layer; And
ii) a method for determining one or more optimized values of operating parameters of a sensor system, which is selected based on an evaluation of a second substrate-to-substrate variation of variation between the measurement parameters associated with the particular layer. The one or more optimized values of the operating parameters of the sensor system of claim 12, wherein the specific layer is selected when the first substrate-to-substrate variation and the second substrate-to-substrate variation exceed a threshold. How to determine. As a method for determining the state of the semiconductor manufacturing process,
a. Obtaining an optimized value of the operating parameter using the method according to claim 1;
b. Obtaining, for a plurality of values of the operating parameter, measurement parameters for additional substrates obtained using the sensor system;
c. Determining a new value of the operating parameter associated with an expected minimum substrate-to-substrate variation of the measurement data; And
d. And determining a state of a semiconductor manufacturing process based on a comparison of the new value with an optimized value of the operating parameter. A computer program comprising program instructions operable to perform the method according to claim 1 when executed on a suitable device.

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