WO2024185143A1 - 荷電粒子線装置 - Google Patents

荷電粒子線装置 Download PDF

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WO2024185143A1
WO2024185143A1 PCT/JP2023/009147 JP2023009147W WO2024185143A1 WO 2024185143 A1 WO2024185143 A1 WO 2024185143A1 JP 2023009147 W JP2023009147 W JP 2023009147W WO 2024185143 A1 WO2024185143 A1 WO 2024185143A1
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defect
sample
light
image
computer
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French (fr)
Japanese (ja)
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大輔 平野
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Hitachi High Tech Corp
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Hitachi High Tech Corp
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Priority to KR1020257024936A priority Critical patent/KR20250129060A/ko
Priority to JP2025505045A priority patent/JPWO2024185143A1/ja
Priority to PCT/JP2023/009147 priority patent/WO2024185143A1/ja
Priority to TW113105216A priority patent/TWI905659B/zh
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    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01J—ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
    • H01J37/00—Discharge tubes with provision for introducing objects or material to be exposed to the discharge, e.g. for the purpose of examination or processing thereof
    • H01J37/02—Details
    • H01J37/22—Optical, image processing or photographic arrangements associated with the tube
    • H01J37/226—Optical arrangements for illuminating the object; optical arrangements for collecting light from the object
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N23/00—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00
    • G01N23/22—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by measuring secondary emission from the material
    • G01N23/225—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by measuring secondary emission from the material using electron or ion
    • G01N23/2251—Investigating or analysing materials by the use of wave or particle radiation, e.g. X-rays or neutrons, not covered by groups G01N3/00 – G01N17/00, G01N21/00 or G01N22/00 by measuring secondary emission from the material using electron or ion using incident electron beams, e.g. scanning electron microscopy [SEM]
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01J—ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
    • H01J37/00—Discharge tubes with provision for introducing objects or material to be exposed to the discharge, e.g. for the purpose of examination or processing thereof
    • H01J37/02—Details
    • H01J37/22—Optical, image processing or photographic arrangements associated with the tube
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01J—ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
    • H01J37/00—Discharge tubes with provision for introducing objects or material to be exposed to the discharge, e.g. for the purpose of examination or processing thereof
    • H01J37/02—Details
    • H01J37/22—Optical, image processing or photographic arrangements associated with the tube
    • H01J37/222—Image processing arrangements associated with the tube
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01J—ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
    • H01J37/00—Discharge tubes with provision for introducing objects or material to be exposed to the discharge, e.g. for the purpose of examination or processing thereof
    • H01J37/02—Details
    • H01J37/244—Detectors; Associated components or circuits therefor
    • H—ELECTRICITY
    • H01—ELECTRIC ELEMENTS
    • H01J—ELECTRIC DISCHARGE TUBES OR DISCHARGE LAMPS
    • H01J37/00—Discharge tubes with provision for introducing objects or material to be exposed to the discharge, e.g. for the purpose of examination or processing thereof
    • H01J37/26—Electron or ion microscopes; Electron or ion diffraction tubes
    • H01J37/28—Electron or ion microscopes; Electron or ion diffraction tubes with scanning beams

Definitions

  • the present invention relates to a charged particle beam device.
  • SEMs Scanning electron microscopes
  • a defect review SEM is an application device of a scanning electron microscope (SEM).
  • SEM scanning electron microscope
  • a defect review SEM is used to convert defects detected by a semiconductor wafer defect inspection device into high-magnification image information at a level where the defects can be recognized using an SEM. Therefore, defect review SEMs are mainly used together with inspection devices in the production lines of electronic devices such as semiconductors.
  • the wafer defect inspection device detects defects, lists the defect position coordinates as defect information, and outputs it as a file.
  • the inspected wafer and the inspection result file are loaded into the defect review SEM.
  • the review SEM imports a file containing the inspected wafer and its inspection results (defect position coordinate information).
  • the review SEM identifies the exact coordinates of the defect based on the position information in the defect list file (positioning).
  • the review SEM takes and saves a photograph of the defect.
  • Patent Document 1 discloses an optically assisted SEM that obtains images of the material and structural distribution of a sample with nanometer resolution from changes in the electronic state within the sample that occur when illumination light is applied to the sample while the sample is irradiated with an electron beam.
  • Patent Document 2 discloses a technique for improving the visibility of an SEM by controlling the polarization and wavelength of the irradiated light to increase the contrast of the pattern shape of the sample. Non-Patent Documents 1 and 2 will be discussed later.
  • Zhaogang Dong et al. “Ultraviolet Interband Plasmonics with Si nanostructures”, Nano Letters, September 2019 Quan Sun et al. “Direct imaging of the near field and dynamics of surface plasmon resonance on gold nanostructures using photoemission electron microscopy”, Light: Science & Applications, December 2013
  • Patent Documents 1 and 2 describe techniques for increasing the image contrast of the pattern shape of a sample. It is believed that by visually viewing an observation image with increased contrast, it is possible to identify defect shapes, etc. On the other hand, as a prerequisite for viewing a defect image, it is necessary to identify the defect position in the observation image in advance (and, if necessary, to increase the observation magnification of the identified defect position). In other words, since defect position detection and defect observation are separate processes, even if techniques that allow a sample image to be clearly viewed are provided as in Patent Documents 1 and 2, other considerations are required to quickly identify the defect position.
  • Patent Documents 1 and 2 leave room for further study in terms of specific methods for quickly identifying the defect position in an observation image with enhanced contrast.
  • the present invention was made in consideration of the above problems, and aims to provide a charged particle beam device that can quickly identify the location of defects in an observation image of a sample and increase inspection throughput.
  • the charged particle beam device includes a database that describes combinations of light wavelengths and polarization directions that can enhance the contrast in an observation image of a defect in a sample, irradiates the sample with light using at least one of the combinations, generates an observation image for each combination, and detects the defect using the observation image.
  • the charged particle beam device can quickly identify the location of defects in the observation image of the sample, thereby increasing the inspection throughput.
  • Other issues, configurations, advantages, etc. of the present invention will become clear from the description of the embodiments below.
  • 1 shows a conceptual diagram of the electric field enhancement ratio for horizontally polarized light and vertically polarized light.
  • 1 shows a typical conceptual diagram showing ⁇ pixel versus SEM spatial resolution.
  • the LSPR characteristics of normal sized and abnormal sized patterns are shown.
  • 2 shows a typical example of an SEM image of a defective pattern having the characteristics shown in FIG. 1.
  • 1 is a configuration diagram of a charged particle beam device 1 according to a first embodiment.
  • 1 shows an example of a GUI for a light-assisted defect review SEM.
  • 2 shows an operation flowchart of the charged particle beam device 1.
  • 13 shows an SEM image of the hole pattern when the light is turned off.
  • 13 shows an SEM image obtained when illumination light having a wavelength that is non-resonant with the LSPR induced in the hole shape is used. 13 shows an SEM image obtained when illumination light having a wavelength that resonates with the LSPR induced in the hole shape is used. 13 shows an SEM image obtained when illumination light having a wavelength that resonates with the LSPR induced in the hole shape is used.
  • the procedure for finding the condition that maximizes the CNR expressed by the formula (3) will be described below.
  • 1 shows an inspection image of a hot spot where pattern break defects frequently occur. We show that the CNR can be increased by differential processing of optically assisted SEM images. 1 shows a high-resolution SEM image of a circuit pattern including pattern line narrowings. 16 shows a photo-assisted SEM image of the pattern circuit of FIG. 15.
  • the wavelength characteristics of localized surface plasmon resonance are sensitive to nanometer-sized shape changes. For example, consider LSPR occurring in a patterned sample. When the pattern shape changes locally due to a structural defect, the wavelength characteristics of LSPR change, so by irradiating the sample with light having a wavelength that resonates with the pattern as illumination light, the electric field enhancement rate can be changed at the defect position. Since the enhanced electric field increases the intensity of secondary electrons through excited carriers, the signal intensity changes locally at the defect position. In order to identify defects in a pattern by utilizing the local signal intensity change, it is necessary that the change in signal intensity at the defect position is sufficiently larger than the background signal noise. Therefore, by optimizing the spatial resolution of the design pattern so as to minimize the background signal noise, the contrast between the defect-derived signal and the background signal can be improved, making it possible to detect defects in a wide field of view.
  • LSPR localized surface plasmon resonance
  • LSPR has wavelength characteristics and polarization anisotropy. For example, consider LSPR that occurs in a patterned sample in which holes are regularly arranged two-dimensionally. Furthermore, in this specification, polarization is considered only in the in-plane direction of the sample.
  • Excited electrons near the Fermi surface generated by irradiating a sample with light increase the amount of secondary electrons emitted by electron beam excitation. If it is assumed that the amount of secondary electrons emitted per pulse of an electron beam under pulsed light irradiation is proportional to the amount of light energy absorbed by the sample, it is expressed as formula (1).
  • S(x, y) is the amount of amplification of the emitted secondary electrons due to light irradiation at the position (x, y) on the sample surface.
  • ⁇ material is the dielectric constant of the sample.
  • ⁇ 0 is the dielectric constant of the background, which corresponds to the vacuum here.
  • E is the electric field strength.
  • the escape length of the secondary electrons is D.
  • T is the pulse width of the pulsed light, which is sufficiently shorter than the lifetime t decay of the excited electrons.
  • t delay is the difference in the time of incidence of the sample between the light pulse and the electron beam pulse.
  • I p is the irradiated charge of the electron beam.
  • Non-Patent Document 1 It has been reported that in wavelength regions where the real part of the dielectric constant is negative, LSPR occurs due to nanometer-sized structures (Non-Patent Document 1). Such electron excitation due to local electric field enhancement has been confirmed as an increase in intensity in photoelectron emission images (Non-Patent Document 2). Based on this, it is expected that SEM images reflecting the distribution of excited electrons enhanced by LSPR can be obtained by irradiating light.
  • the SEM signal s pixel per pixel when illuminated with light can be expressed by the following formula (2): Note that the integral range is limited to the pixel range of interest.
  • the intensity per pixel of a patterned sample is s pixel pattern
  • the intensity of a pixel containing a defect is s pixel defect
  • the amount of noise per pixel is ⁇ pixel
  • Figure 1 shows a conceptual diagram of the electric field enhancement ratio for horizontally polarized light and vertically polarized light.
  • the electric field enhancement is maximized on the pattern, but there is almost no enhancement at the defect position.
  • the polarization of the illumination is vertical and the wavelength is ⁇ 0 ⁇ , there is almost no change in the enhancement between the pattern position and the defect position. Therefore, for a defective pattern with such wavelength characteristics, it is clear that the numerator on the right-hand side of equation (3) can be maximized by setting the polarization to horizontal and the wavelength to 0 ⁇ .
  • ⁇ pixel is defined as the standard deviation of the signal intensity s pixel pattern in a normal portion of a patterned sample
  • ⁇ pixel can be expressed as follows using a term due to the shape of the sample and a term due to the discreteness of electrons:
  • equation (4) can be minimized, that is, how CNR can be maximized, by appropriately setting the SEM spatial resolution or pixel size.
  • ⁇ struct is the signal variation between pixels caused by the sample pattern, it is maximized when the SEM spatial resolution or pixel size is sufficiently smaller than the spatial scale that characterizes the pattern, and is minimized when it approaches the pattern pitch.
  • Figure 2 shows a typical conceptual diagram of ⁇ pixel versus SEM spatial resolution. It can be seen that noise decreases monotonically with increasing resolution, reaching a minimum near the pattern pitch. The noise level can be minimized by selecting an appropriate spatial resolution and pixel size for the design pattern.
  • This article explains a method for inspecting pattern dimensional abnormalities by utilizing the optically assisted SEM signal intensity that has optical wavelength characteristics.
  • the peak wavelength of the electric field enhancement due to LSPR shifts to shorter wavelengths.
  • Figure 3 shows the LSPR characteristics of a normal-sized pattern and a pattern with an abnormal size.
  • the LSPR characteristics of normal parts where the pattern dimensions are the design median are shown by straight lines, and the LSPR characteristics of abnormal parts where the dimensions have become abnormal due to narrowing are shown by dotted lines.
  • the wavelength at which the LSPR electric field enhancement rates of normal and abnormal parts are equal is ⁇ th.
  • the electric field enhancement of normal parts is greater than that of dimensionally abnormal parts
  • the electric field enhancement of normal parts is smaller than that of dimensionally abnormal parts.
  • Figure 4 shows a typical example of an SEM image of a defective pattern having the characteristics shown in Figure 1.
  • the pixel size of the SEM image is the same as the pattern pitch.
  • the defect is located at the center of the field of view.
  • 104 shows an SEM image without illumination light
  • 105 shows an SEM image with horizontal illumination polarization and wavelength ⁇ 0 ⁇
  • 106 shows an SEM image with vertical illumination polarization and wavelength ⁇ 0 ⁇ .
  • Image contrast corresponds to signal intensity, with black being the weakest and white being the strongest.
  • Images 105 and 106 are very bright compared to image 104. This is because the illumination increases secondary electrons derived from the pattern shape. Focusing on the defect position 104, the defect cannot be confirmed because the resolution of the SEM is coarser than the defect shape. In 105, the defect can be confirmed as a decrease in signal intensity. Focusing on the defect position 106, the signal intensity is the same as the pattern signal, so the defect cannot be recognized. From the above, it can be seen that in a defective pattern having the wavelength characteristics of Figure 1, equation (3) is maximized by setting the polarization horizontal and the wavelength ⁇ 0 ⁇ , so that defects can be inspected from the contrast in signal intensity even if the resolution of the SEM is coarse.
  • the polarization and wavelength characteristics of the LSPR generated in a pattern depend on the material, shape, size, arrangement direction, pitch, and convex/concave duty ratio of the pattern part. Furthermore, the polarization and wavelength characteristics of the LSPR generated in a shape defect are determined by the factors that change the pattern shape. For example, whether to fill the concave or cut the convex, and the direction of the shape change. Therefore, in order to maximize formula (3) and inspect defects, it is necessary to set multiple pairs of polarization and wavelength according to the material and pattern of the wafer loaded into the device and the type of defect to be inspected. It takes a very long time to find such parameters for each loaded wafer, which significantly reduces the inspection throughput.
  • FIG. 5 is a configuration diagram of the charged particle beam device 1 according to the first embodiment.
  • the charged particle beam device 1 is configured as a part-time review SEM.
  • the charged particle beam device 1 is configured as a scanning electron microscope that obtains an observation image of a sample 8 by irradiating the sample 8 with an electron beam 30 (primary charged particles).
  • the charged particle beam device 1 includes an electron optical system, a stage mechanism system, an electron beam control system, a light irradiation system, and a main console 16 (computer).
  • the electron optical system is composed of an electron gun 2, a deflector 3, an electron lens 4, and a detector 5.
  • the stage mechanism system is composed of an XYZ stage 6 and a sample holder 7.
  • the electron beam control system is composed of an electron gun control unit 9, a deflection signal control unit 10, a detection control unit 11, and an electron lens control unit 12.
  • the stage control system is composed of a stage driver 15 and a stage position command unit 22.
  • the light irradiation system is composed of a light source 13, a light control unit 14, and a glass window 27.
  • the main console 16 further includes an image formation system and a data input/output system.
  • the image formation system is composed of an image processing unit 17 and an image signal processing unit 19, which have a detection sampling function synchronized with the optical signal.
  • the data input/output system is composed of an input setting unit 21 for the imaging conditions of the electron beam 30, a human interface 20, an external data input/output unit 25, and a defect database 23.
  • the electron beam 30 accelerated by the electron gun 2 is focused by the electron lens 4 and irradiated onto the sample 8.
  • the deflector 3 controls the irradiation position of the electron beam 30 on the sample 8.
  • the position of the sample 8 is controlled by the XYZ stage 6.
  • the main console 16 controls the XYZ stage 6 via a stage driver 15.
  • the detector 5 detects emitted electrons (secondary charged particles) emitted from the sample 8 by irradiating the sample 8 with the electron beam 30.
  • the input setting unit 21 is a functional unit that allows the user to specify and input the acceleration voltage, irradiation current, deflection conditions, detection sampling conditions, electron lens conditions, XYZ stage position, etc.
  • the light source 13 emits light to be irradiated onto the sample 8.
  • the light source 13 is a laser capable of outputting various spectra in the range from ultraviolet to near infrared, and parameters such as the polarization plane, light intensity, spectrum, output timing, and pulse width can be changed.
  • the light emitted from the light source 13 is irradiated onto the sample 8 placed in a vacuum through a glass window 27 provided in the device housing 26.
  • the light source 13 can be equipped with, for example, a wavelength conversion unit, a polarization control unit, and an intensity control unit.
  • the wavelength conversion unit is a component that can change the light spectrum, and examples include wavelength conversion using an optical parametric amplifier, whitening by self-phase modulation using an optical fiber, and line width narrowing and spectrum shaping using an optical filter.
  • the polarization control unit is a component that can change the polarization plane of light, and examples include a wire grid type and a crystal type that uses the birefringence phenomenon that the material itself has.
  • the intensity control unit can control the light intensity, for example, by a combination of a wave plate and a polarizing beam splitter.
  • the light control unit 14 controls the light parameters that represent the physical characteristics of the light emitted by the light source 13. The user specifies the light parameters to the light control unit 14 via the input setting unit 21.
  • Figure 6 shows an example of the GUI of an optically assisted defect review SEM.
  • the charged particle beam device 1 inputs the defect positions on the wafer on which the defect list output from the defect inspection device is written, performs inspection, and outputs the results.
  • 401 displays the ID of the loaded wafer
  • 402 displays the name of the file containing the defect list input from the outside
  • 406 displays the design pattern of the wafer input from the outside.
  • 403 displays the items set by the user.
  • the type of defect to be inspected is specified, and here, three types of defects, H, I, and V, are the inspection items as an example. The type and number can be changed by the user.
  • the electron section the parameters of the electron gun 2 are set.
  • the setting items include the magnification during defect inspection, the magnification during image capture, and the delay that determines the firing timing of the electron gun relative to the trigger.
  • 404 displays the optical setting items. 404 is automatically determined by the main console 16 according to the material, design pattern, and inspection defect according to the contents of the defect database 23.
  • the optical parameter profiles are created in the number necessary to classify all the specified target defects.
  • the optical profile displays quantities that characterize the illumination, and examples of these include the type of polarization, the angle of the main axis of polarization, the central wavelength, and the output.
  • 405 displays an example of the inspection results.
  • the No column indicates the defect number listed in the defect list in 402.
  • the detection column indicates whether or not a defect has been detected near the coordinates associated with that number, and if so, further indicates the coordinates (X, Y) on the wafer where the defect was detected.
  • the classification column indicates which of the targets set in 403 the detected defect corresponds to.
  • the SEM file column indicates the file name of the SEM image taken at the coordinates (X, Y).
  • FIG. 7 shows a flowchart of the operation of the charged particle beam device 1. Each step in FIG. 7 is explained below.
  • the main console 16 reads the design pattern of the sample 8 (406 in FIG. 6) and a defect list (402 in FIG. 6) that lists defect types and defect positions output by the defect inspection device (S701).
  • the design pattern includes information on design values such as the type, size, and number of shape patterns.
  • the main console 16 sets optimal electronic parameters (spatial resolution and field of view) based on the design pattern (S702).
  • the main console 16 determines a combination of light irradiation parameters (light profile) required to classify defects according to a combination of a design pattern and a defect list. This combination is determined by referring to a defect database 23.
  • the defect database 23 describes, for each combination of a design pattern and a defect type, a candidate light profile (which may be one or more) suitable for detecting the defect type.
  • a defect type that the user specifies as a detection target among those described in the defect list can be input.
  • the main console 16 determines the light profile based on the specified defect type according to the correspondence between the defect type and the light profile described in the defect database 23.
  • the defect database 23 will be described in detail later.
  • steps S704 to S705 The main console 16 repeats the following steps S705 to S711 the number of times equal to the number of defects described in the defect list (S704).
  • the main console 16 moves the specimen 8 to the coordinates of the defect list No. i (S705).
  • step S706 The main console 16 repeats the following steps S707 to S709 the number of times corresponding to the number of light profiles determined in S703.
  • step S707 The main console 16 illuminates the sample 8 using the light profile j and captures an SEM image at a lower magnification than a high-magnification SEM image described later.
  • the main console 16 judges whether the captured SEM image contains a defect. A specific example of the judgment method will be described later together with a specific example of an observation image.
  • the main console 16 may search for defects at and around the defect coordinates described in the defect list. Since an image with a lower magnification than that of S711 is used in S707, defects can be efficiently searched for using a wide field of view.
  • FIG. 7 steps S708 to S709
  • the main console 16 sets a flag indicating that a defect has been detected for that optical profile j (for example, sets the flag value to 1) (S709).
  • the main console 16 classifies the defect type based on the combination of flags for optical profile j. If the observed image does not contain a defect (S708: No), the process returns to S706 and the same process is repeated for the next optical profile (j is incremented by 1).
  • FIG. 7 steps S710 to S712
  • the main console 16 takes a high-magnification SEM image of the coordinates in which the defect was detected (S711).
  • the main console 16 records the result of the defect detection in an inspection result file (a data file describing the contents of the inspection result 405).
  • the main console 16 also records the result of the defect detection.
  • the main console 16 outputs the inspection result file created as described above to an appropriate storage device.
  • Figure 8 shows an SEM image of a hole pattern with the light turned off.
  • the magnification of the SEM image is high.
  • a defect in which two horizontally adjacent holes are connected can be seen in the center of the image.
  • the defect database 23 describes the optical parameters that maximize the signal contrast between such a defective portion and a normal hole pattern portion.
  • Figure 9 shows an SEM image when a wavelength that is non-resonant with the LSPR induced in the hole shape is used for illumination light. It can be seen that the image is brighter overall than in Figure 8. This is because the amount of secondary electron emission from the entire wafer has increased due to photoexcitation. However, because the LSPR does not resonate with the hole shape, there is insufficient contrast in both the defective area and the normal hole pattern. Therefore, it can be seen that the wavelength in this case is not suitable for detecting the defect in Figure 9.
  • Figure 10 shows an SEM image when illumination light with a wavelength that resonates with the LSPR induced in the hole shape is used.
  • the incident polarization is vertical. Localized signal enhancement can be seen at the ends of the pattern in both the defective and normal hole pattern areas.
  • Figure 11 shows an SEM image when illumination light with a wavelength that resonates with the LSPR induced in the hole shape is used.
  • the incident polarization is horizontal. Localized signal enhancement can be confirmed at the ends of the pattern in the normal hole pattern area, but no localized signal enhancement can be confirmed in the defective area.
  • the defect database 23 records the optical profile in association with the defect type. This association can be recorded for each design pattern (hole pattern in Figures 8 to 11). Therefore, in S703, it is possible to select optical profile candidates that are suitable for detecting the defect based on the combination of the design pattern and the defect list.
  • FIG. 12 shows the procedure for investigating the conditions for maximizing the CNR expressed by formula (3).
  • Figures 8, 9, 10, and 11 were integrated by piece for each pattern pitch, and the in-plane distribution of s pixels was evaluated.
  • FIG. 12 shows the in-plane distribution image.
  • 601 is the integral of FIG. 8
  • 602 is the integral of FIG. 9
  • 603 is the integral of FIG. 10,
  • 604 is the integral result of FIG. 11.
  • 604 has a large luminance difference between the defect signal and the pattern signal.
  • formula (3) is maximized.
  • defects whose contrast is anisotropically improved by horizontally polarized illumination are classified as H defects.
  • defects whose contrast is improved by vertically polarized illumination are called V defects
  • defects whose contrast improvement is not polarization dependent are called I defects.
  • a defect database 23 is created by classifying defects occurring in various pattern shapes using a similar method.
  • the defect database 23 holds records describing, for each defect classification, the combination of the defect classification and the polarization direction and wavelength (optical profile) that provides the highest image contrast for that defect.
  • the main console 16 lists the optical profiles described in the defect database 23, and uses each of the listed optical profiles to obtain a low-magnification SEM image of the defect. This makes it possible to detect defects on the SEM image in S707 and S708 using optical profile j, which enhances the contrast of the defect.
  • This defect detection method corresponds to the first principle of increasing CNR.
  • the charged particle beam device 1 can identify the defect position by a local change in signal intensity by selecting optical parameters whose LSPR characteristics change significantly depending on the presence or absence of a defect. This makes it possible to provide a high-performance defect inspection SEM device with improved defect identification and classification functions over a wide field of view. By widening the field of view, the throughput of defect detection can be improved. Furthermore, defects can be automatically detected and classified by using a defect database 23 that describes the polarization direction of illumination light that can enhance the defect contrast.
  • Figure 13 shows inspection images of hot spots where pattern break defects frequently occur.
  • 701 shows a high-resolution SEM image of a normal circuit pattern
  • 702 shows a high-resolution SEM image of a circuit pattern including a pattern break defect.
  • a pattern break defect has occurred in the area circled in 702.
  • 703 and 704 show optically assisted SEM images obtained when light that satisfies the LSPR condition that occurs in the pattern break structure is incident.
  • An increase in signal intensity in the pattern break structure means an increase in the numerator of formula (3), i.e., an increase in CNR.
  • FIG. 14 shows that the CNR can be increased by differential processing of optically assisted SEM images.
  • FIG. 14 shows a differential image between an optically assisted SEM image 703 of a normal pattern and an optically assisted SEM image 704 of a circuit pattern including a pattern break structure. It can be seen that the contrast between the signal of the pattern break structure and the background signal is increased. This is because the background signal ⁇ 2 struct originating from the structure, which is the first term on the right side of formula (4), is reduced. High sensitivity inspection is possible by increasing the CNR of the defect signal generated at the hot spot as much as possible. This defect detection method corresponds to the third principle for increasing the CNR. In steps S707 to S708, the main console 16 can detect pattern break defects using the above principles.
  • the position, short-circuit direction, and short-circuit shape at which a pattern break defect occurs vary from defect to defect, so it is not necessarily easy to classify the types of pattern break defects in advance and identify an appropriate light profile for each type. Therefore, a method using differential images such as those shown in Figures 13 and 14 is useful.
  • pattern break defects tend to occur as short-circuit defects in locations where two normal patterns are placed relatively close to each other with a gap in between.
  • pattern break defects can be detected with high sensitivity in hot spots where pattern break defects occur frequently. Also, as described in embodiment 1, the inspection throughput is high, so pattern break defects can be detected at high speed.
  • ⁇ Third embodiment> an optically assisted SEM apparatus is described which utilizes the pattern line width dependency of the LSPR characteristics to inspect for dimensional anomalies from signal intensity in hot spots where defects that do not satisfy the desired dimensional range occur frequently.
  • Figure 15 shows a high-resolution SEM image of a circuit pattern that includes narrowed pattern line width areas. It can be seen that there are three narrowed pattern line width areas.
  • a narrowed portion here refers to a portion within a linear pattern where the line width is narrower than other portions. Similarly, a portion where the line width is wider than other portions is also a line width abnormality defect.
  • FIG. 16 shows an optically assisted SEM image of the pattern circuit of FIG. 15.
  • 801 is an SEM image when the incident wavelength ⁇ > ⁇ th (see FIG. 3)
  • 802 is an SEM image when the incident wavelength ⁇ th.
  • 801 the signal at the design median line width is enhanced, and in 802, the signal at the narrowed portion is enhanced.
  • 803 is a difference image between 802 and 801. Since the narrowed portion can be identified from the signal intensity, line width abnormalities can be inspected from the signal intensity. Other line width abnormalities can also be inspected using a similar method.
  • the main console 16 can detect line width abnormality defects using the above principles.
  • the present invention is not limited to the above-described embodiment, and includes various modified examples.
  • the above-described embodiment has been described in detail to clearly explain the present invention, and it is not necessary to include all of the configurations described.
  • a part of an embodiment can be replaced with a configuration of another embodiment.
  • a configuration of another embodiment can be added to a configuration of an embodiment.
  • a part of the configuration of each embodiment can be added to, deleted from, or replaced with a part of the configuration of another embodiment.
  • the main console 16 may detect defects by generating an observation image with the spatial resolution as close as possible to the pattern pitch, in accordance with the principle explained in (Principle 2 for increasing CNR: spatial resolution and pattern pitch).
  • the main console 16 may present an observation image of the sample 8 (which may or may not include defects) on the user interface. For example, when an SEM file name is double-clicked on in the user interface of FIG. 6, the observation images exemplified in FIGS. 8 to 11, 13 to 14, 15 to 16, etc. may be presented.
  • the main console 16 and each of the functional units of the main console 16 can be configured by hardware such as a circuit device that implements these functions, or can be configured by a calculation device such as a CPU (Central Processing Unit) executing software that implements these functions. Alternatively, they can be configured by a computer that includes at least one of these.
  • hardware such as a circuit device that implements these functions
  • a calculation device such as a CPU (Central Processing Unit) executing software that implements these functions.

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