MEASUREMENT APPARATUS, LITHOGRAPHIC APPARATUS, AND ARTICLE MANUFACTURING METHOD

Abstract

To provide a technique advantageous in improving the robustness against noise so as to measure the position of a measurement target with high accuracy.SOLUTION: A measurement apparatus that measures position information of a measurement target is provided. The apparatus includes a scope configured to generate an image by capturing an image of the measurement target, and a processor configured to obtain position information of the measurement target based on the image. The processor is configured to generate a plurality of image components using a statistical technique from a plurality of images generated by the scope, output the plurality of generated image components, perform processing based on the plurality of image components, and determine the position information based on a result of the processing.SELECTED DRAWING: Figure 11

Description

[Technical Field]

[0001] The present invention relates to a metrology apparatus, a lithography apparatus, and an article manufacturing method. [Background technology]

[0002] Lithography processes for manufacturing articles such as semiconductor devices may use lithography apparatuses, such as imprint apparatuses and exposure apparatuses. The lithography apparatus may transfer a pattern from an original onto a shot area of ​​a substrate. The imprint apparatus contacts a mold with an imprint material disposed on the shot area of ​​the substrate and hardens the imprint material, thereby forming a pattern made of the cured imprint material on the shot area. The exposure apparatus projects the pattern from the original onto a shot area of ​​a substrate coated with a photosensitive material, thereby forming a latent image of the pattern from the original onto the photosensitive material. The latent image is converted into a physical pattern by a development process. Such lithography apparatuses require a technique for measuring the relative positions of marks on the substrate and marks on the original with high precision in order to align the shot area of ​​the substrate with high precision.

[0003] Patent Document 1 discloses a method for estimating an alignment correction value using machine learning. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 4601492 Summary of the Invention [Problem to be solved by the invention]

[0005] As patterns to be formed on substrates become finer, there is a demand for even higher accuracy in position measurement.

[0006] However, images of the object being measured contain noise caused by various factors, which hinders highly accurate position measurement.

[0007] The present invention provides an advantageous technique for improving robustness against noise so that the position of a measurement object can be measured with high accuracy. [Means for solving the problem]

[0008] According to one aspect of the present invention, a measurement device for measuring position information of a measurement object includes a scope that captures an image of the measurement object and generates an image, and a processor that determines position information of the measurement object based on the image, wherein the processor generates a plurality of image components from a plurality of images generated by the scope using a statistical method, outputs the generated plurality of image components, performs processing to determine a component related to a measurement error based on the plurality of image components, and determines the position information based on the image generated by the scope and the component related to the measurement error. the processing includes generating, from the plurality of images, the plurality of image components and information indicating the sizes of the plurality of image components, using the statistical method; calculating a correlation coefficient between the sizes of the plurality of image components and a value related to the measurement error; and evaluating, based on the correlation coefficient, an influence of each of the plurality of image components on the measurement error. A measuring device is provided, characterized in that: [Effects of the Invention]

[0009] According to the present invention, it is possible to provide an advantageous technique for improving robustness against noise so that the position of a measurement object can be measured with high accuracy. [Brief explanation of the drawings]

[0010] [Figure 1] FIG. 1 is a diagram illustrating an example of the operation of the imprint apparatus. [Figure 2] FIG. 1 is a diagram illustrating an example of the configuration of an imprint apparatus. [Figure 3] FIG. 1 is a diagram illustrating an example of the configuration of an article manufacturing system. [Figure 4] 4A and 4B are diagrams illustrating alignment mark images and alignment waveforms. [Figure 5] 10A and 10B are diagrams illustrating a method for calculating the position of an alignment mark. [Figure 6] FIG. 1 is a diagram illustrating a moiré measurement system. [Figure 7] 10A and 10B are diagrams illustrating signal waveforms obtained from image data of alignment marks. [Figure 8] 10A and 10B are diagrams illustrating signal waveforms obtained from image data of alignment marks. [Figure 9] 1A and 1B are diagrams illustrating the asymmetry of alignment marks; [Figure 10] 10A and 10B are diagrams illustrating examples of asymmetry of a plurality of alignment marks. [Figure 11] FIG. 10 is a diagram illustrating processing for an alignment image. [Figure 12] 10A and 10B are diagrams for explaining processing on an alignment image. [Figure 13] 10A and 10B are diagrams illustrating a process of performing correction in alignment. [Figure 14] FIG. 1 is a diagram illustrating the configuration of an exposure apparatus. [Figure 15] FIG. 1 is a diagram illustrating the configuration of a measurement device. [Figure 16] 10A and 10B are diagrams illustrating the configuration of an illumination aperture stop in the positioning device. [Figure 17] FIG. 2 is a diagram illustrating the configuration of an alignment mark. [Figure 18] 10A and 10B are diagrams for explaining the dependence of a signal waveform (measurement direction) obtained from image data of an alignment mark on optical parameters. [Figure 19] 10A and 10B are diagrams for explaining the optical parameter dependency of a signal waveform (non-measurement direction) obtained from image data of an alignment mark. [Figure 20] 10A and 10B are diagrams illustrating examples of signal waveforms obtained from image data of alignment marks in alignment sample shot areas. [Figure 21] 1A to 1C are diagrams illustrating a method for manufacturing an article. DETAILED DESCRIPTION OF THE INVENTION

[0011] Hereinafter, embodiments will be described in detail with reference to the accompanying drawings. Note that the following embodiments do not limit the scope of the invention claimed. Although multiple features are described in the embodiments, not all of these multiple features are necessarily essential to the invention, and multiple features may be combined arbitrarily. Furthermore, in the accompanying drawings, the same reference numerals are used to designate the same or similar components, and redundant explanations will be omitted.

[0012] First Embodiment In the following first embodiment, an imprint apparatus will be described as an example of a lithography apparatus, but imprint apparatuses and exposure apparatuses have much in common with regard to the alignment technology between a shot area on a substrate and an original. Therefore, the alignment technology described below can also be applied to exposure apparatuses. Therefore, an exposure apparatus will be described as the second embodiment.

[0013] 2(a) schematically shows the configuration of the imprint apparatus IMP according to the first embodiment. The imprint apparatus IMP performs an imprint process in which the imprint material IM on the shot area of ​​the substrate S is brought into contact with the pattern area MP of the mold M, and the imprint material IM is cured, and then the cured imprint material IM is separated from the mold M. This imprint process forms a pattern made of the cured imprint material IM on the substrate S.

[0014] The imprint material is a curable composition (sometimes referred to as an uncured resin) that cures upon application of curing energy. Examples of curing energy include electromagnetic waves and heat. Electromagnetic waves can be, for example, light with a wavelength selected from the range of 10 nm to 1 mm, such as infrared light, visible light, and ultraviolet light. The curable composition can be a composition that cures upon irradiation with light or heat. Among these, photocurable compositions that cure upon irradiation with light contain at least a polymerizable compound and a photopolymerization initiator and may further contain a non-polymerizable compound or solvent, as necessary. The non-polymerizable compound is at least one selected from the group consisting of sensitizers, hydrogen donors, internal mold release agents, surfactants, antioxidants, and polymer components. The imprint material can be arranged on the substrate in the form of droplets, or in the form of islands or films formed by connecting multiple droplets. The viscosity of the imprint material (at 25°C) can be, for example, 1 mPa·s to 100 mPa·s. Examples of materials that can be used for the substrate include glass, ceramics, metals, semiconductors, and resins. If necessary, a member made of a material different from the substrate may be provided on the surface of the substrate. Examples of the substrate include a silicon wafer, a compound semiconductor wafer, and quartz glass.

[0015] In this specification and drawings, directions are indicated in an XYZ coordinate system with the horizontal plane as the XY plane. Generally, the substrate S is placed on the substrate holder 102 so that its surface is parallel to the horizontal plane (XY plane). Therefore, hereinafter, the mutually orthogonal directions in a plane along the surface of the substrate S are referred to as the X-axis and Y-axis, and the direction perpendicular to the X-axis and Y-axis is referred to as the Z-axis. Furthermore, hereinafter, directions parallel to the X-axis, Y-axis, and Z-axis in the XYZ coordinate system are referred to as the X-direction, Y-direction, and Z-direction, respectively. Furthermore, rotation around the X-axis, rotation around the Y-axis, and rotation around the Z-axis are respectively indicated as θX, θY, and θZ. Positioning refers to controlling the position and / or orientation. Alignment can include controlling the position and / or orientation of at least one of the substrate and mold.

[0016] The imprint apparatus IMP may include a substrate holding unit 102 that holds the substrate S, a substrate driving mechanism 105 that drives the substrate holding unit 102 to drive the substrate S, a base 104 that supports the substrate holding unit 102, and a position measurement unit 103 that measures the position of the substrate holding unit 102. The substrate driving mechanism 105 may include a motor such as a linear motor. The imprint apparatus IMP may include a sensor 151 that detects the substrate driving force (alignment load) required for the substrate driving mechanism 105 to drive the substrate S (substrate holding unit 102) during alignment. The substrate driving force during alignment, which is performed while the imprint material IM on the substrate S is in contact with the pattern region MP of the mold M, corresponds to, for example, a shear force acting between the substrate S and the mold M. The shear force is a force that mainly acts in the planar direction of the substrate S and the mold M. The substrate driving force during alignment correlates with, for example, the magnitude of the current supplied to the motor of the substrate driving mechanism 105 during alignment, and the sensor 151 can detect the substrate driving force based on the magnitude of the current. The sensor 151 is an example of a sensor that measures the influence (shear force) that the mold M receives during pattern formation. Furthermore, a drive request (command value) that the control unit 110, which will be described later, issues to the substrate driving mechanism 105 is called a stage control value.

[0017] The imprint apparatus IMP may include a mold holding unit 121 that holds a mold (mold) M, a mold driving mechanism 122 that drives the mold holding unit 121 to drive the mold M, and a support structure 130 that supports the mold driving mechanism 122. The mold driving mechanism 122 may include a motor such as a voice coil motor. The imprint apparatus IMP may include a sensor 152 that detects a release force (separation load) and / or a pressing force. The release force is the force required to separate the mold M from the cured product of the imprint material IM on the substrate S. The pressing force is the force with which the original M is pressed to bring the original M into contact with the imprint material IM on the substrate S. The release force and pressing force are forces that act primarily in a direction perpendicular to the planar direction of the substrate S and the mold M. The release force and pressing force are correlated, for example, to the magnitude of the current supplied to the motor of the mold driving mechanism 122, and the sensor 152 can detect the separation force and pressing force based on the magnitude of the current. The sensor 152 is an example of a sensor that measures the influence (mold release force and / or pressing force) that the mold M receives during pattern formation. In addition, a drive request (command value) that the control unit 110, which will be described later, issues to the mold drive mechanism 122 is also called a stage control value.

[0018] The substrate driving mechanism 105 and the mold driving mechanism 122 constitute a driving mechanism that adjusts the relative position and relative attitude of the substrate S and the mold M. Adjustment of the relative position of the substrate S and the mold M by the driving mechanism includes driving for contact of the mold with the imprint material on the substrate S and separation of the mold from the hardened imprint material (pattern of the hardened product). The substrate driving mechanism 105 can be a driving mechanism having multiple degrees of freedom (for example, three axes of X, Y, and θZ, or preferably six axes of X, Y, Z, θX, θY, and θZ). The mold driving mechanism 122 can also be a driving mechanism having multiple degrees of freedom (for example, three axes of Z, θX, and θY, or preferably six axes of X, Y, Z, θX, θY, and θZ).

[0019] The imprint apparatus IMP may include a mold transport mechanism 140 that transports the mold M, and a mold cleaner 150. The mold transport mechanism 140 may be configured to transport the mold M to the mold holding unit 121, or to transport the mold M from the mold holding unit 121 to an original stocker (not shown) or the mold cleaner 150. The mold cleaner 150 cleans the mold M with ultraviolet light, a chemical solution, or the like.

[0020] The mold holding unit 121 may include a window member 125 that forms a pressure-controlled space CS on the back surface of the mold M (the surface opposite to the pattern region MP in which the pattern to be transferred to the substrate S is formed). The imprint apparatus IMP may include a deformation mechanism 123 that controls the pressure in the pressure-controlled space CS (hereinafter referred to as cavity pressure) to deform the pattern region MP of the mold M into a convex shape toward the substrate S, as schematically shown in FIG. 2(b). The imprint apparatus IMP may also include an alignment scope 106, a curing unit 107, an imaging unit 112, and an optical member 111.

[0021] The imprint apparatus IMP includes an alignment scope 106. The alignment scope may also be called an alignment measurement instrument. The alignment scope 106 can generate image data by illuminating an alignment mark (hereinafter simply referred to as "mark") on the substrate S (first member) and an alignment mark on the mold M (second member) and capturing an optical image formed by the two alignment marks. The alignment scope 106 or the control unit 110 can detect information about the relative position between the marks by processing the image data obtained by capturing the image. The alignment scope 106 can be positioned by a driving mechanism (not shown) according to the position of the alignment mark to be observed. Hereinafter, the image data generated by capturing the image using the alignment scope 106 will also be called an alignment image. Furthermore, the results measured using the alignment scope 106 will also be called alignment measurement values.

[0022] An example of an alignment image observed by the alignment scope 106 can be image data generated by capturing an optical image formed by the reflected light from each of the first mark and the second mark. Another example of an alignment image can be image data generated by capturing a moire (interference fringes), which is an optical image formed by the first mark and the second mark.

[0023] The curing unit 107 irradiates the imprint material IM with energy (e.g., light such as ultraviolet light) for curing the imprint material IM via the optical member 111, thereby curing the imprint material IM. The imaging unit 112 captures images of the substrate S, mold M, and imprint material IM via the optical member 111 and the window member 125. Image data obtained by imaging by the imaging unit 112 is also called a spread image.

[0024] The imprint apparatus IMP may include a dispenser 108 that places the imprint material IM on the substrate S. The dispenser 108 dispenses the imprint material IM so that the imprint material IM is placed on the substrate S, for example, according to a drop recipe that indicates the placement of the imprint material IM. The imprint apparatus IMP may include a control unit 110 that controls the substrate driving mechanism 105, the mold driving mechanism 122, the deformation mechanism 123, the mold transport mechanism 140, the mold cleaner 150, the alignment scope 106, the curing unit 107, the imaging unit 112, the dispenser 108, and the like. In an embodiment, the control unit 110 may include a processor and memory that perform image processing on images generated by the alignment scope 106. The memory stores programs for controlling each unit, programs for performing image processing, and various data. The control unit 110 can be configured, for example, by a PLD (abbreviation for Programmable Logic Device) such as an FPGA (abbreviation for Field Programmable Gate Array), or an ASIC (abbreviation for Application Specific Integrated Circuit), or a general-purpose computer incorporating the program 113, or a combination of all or part of these.

[0025] FIG. 3 illustrates the configuration of an article manufacturing system 1001 for manufacturing articles such as semiconductor devices. The article manufacturing system 1001 may include, for example, one or more lithography apparatuses (imprint apparatuses IMP and / or exposure apparatuses). The article manufacturing system 1001 may also include one or more inspection apparatuses 1005 (e.g., an overlay inspection apparatus, a foreign particle inspection apparatus) and one or more processing apparatuses 1006 (etching apparatus, film deposition apparatus). The article manufacturing system 1001 may also include an error amount calculation apparatus 1007 that calculates an alignment error amount. These apparatuses are connected to a control device 1003, which is one of external systems, via a network 1002 and can be controlled by the control device 1003. Examples of the control device 1003 include an MES and an EEC. The error amount calculation apparatus 1007 may be configured, for example, by a PLD such as an FPGA, an ASIC, a general-purpose computer with a program installed, or a combination of all or part of these. In one example, the error amount calculation device 1007 may be a server called an EdgeServer, etc. In another example, the error amount calculation device 1007 may be incorporated into a control unit of the imprint apparatus IMP or the exposure apparatus, or into the control device 1003, etc. A system including a lithography apparatus such as the imprint apparatus IMP or the exposure apparatus and the error amount calculation device 1007 may be understood as a lithography system.

[0026] The alignment scope 106 and the control unit (processor) 110 of the imprint apparatus IMP can constitute a measurement device that measures or detects position information of a measurement target. From another perspective, the imprint apparatus IMP includes a measurement device that measures or detects position information of a measurement target. The measurement device may be, for example, a measurement device that measures or detects the position information of a diffraction grating that constitutes an alignment mark. diffractionThe measurement device can measure position information of the measurement object in a first direction, i.e., a measurement direction. The measurement device can be further configured to measure position information of the measurement object in a second direction (non-measurement direction) different from the first direction (e.g., a direction perpendicular to the first direction). The processor can determine provisional position information of the measurement object based on the image data, and further determine a correction value related to alignment and correct the provisional position information with the correction value, thereby determining the position information. The measurement device can further include a model for obtaining the correction value based on the feature amount. The measurement device can also include a machine learning unit that generates the model through machine learning.

[0027] The lithography method may include a measurement method for measuring position information of a measurement object, a measurement method for measuring an alignment error between a shot area on a substrate and a mold, and an alignment method for aligning the shot area on the substrate and a mold. In the lithography method, the amount of alignment error is obtained as a correction value from image data of the inspection object. Here, the inspection object may be a mark (optical image of the mark), or an optical image (e.g., moire) formed by a first mark and a second mark.

[0028] 1 shows, as one embodiment of a lithography method, a lithography method that is performed in an imprint system that includes an imprint apparatus IMP. The operations shown in FIG.

[0029] In step S101, a substrate S is transported from a transport source (for example, an intermediary between a pretreatment device and an imprint device IMP) onto the substrate holding unit 102 by a substrate transport mechanism (not shown). In steps S102 to S106, imprint processing (pattern formation) is performed on a shot area selected from a plurality of shot areas on the substrate S. In step S102, a dispenser 108 places an imprint material IM on a shot area to be imprinted, out of the plurality of shot areas on the substrate S. This processing can be performed by discharging the imprint material IM from the dispenser 108 while the substrate S is driven by the substrate driving mechanism 105.

[0030] In step S103, the substrate S and the mold M are driven relatively by at least one of the mold driving mechanism 122 and the substrate driving mechanism 105 so that the pattern region MP of the mold M comes into contact with the imprint material IM above the shot area to be imprinted. In one example, the mold M is driven by the mold driving mechanism 122 so that the pattern region MP of the mold M comes into contact with the imprint material IM above the shot area to be imprinted. In the process of bringing the pattern region MP of the mold M into contact with the imprint material IM, the deformation mechanism 123 can deform the pattern region MP of the mold M into a convex shape toward the substrate S. At this time, the cavity pressure is controlled, and the value thereof is accumulated. Furthermore, in the process of bringing the pattern region MP of the mold M into contact with the imprint material IM, imaging is performed by the imaging unit 112, and the captured image (spread image) is accumulated.

[0031] In step S104, alignment between the shot area of ​​the substrate S and the pattern area MP of the mold M can be performed. Alignment can be performed by measuring the relative position between the alignment mark of the shot area and the alignment mark of the mold M using the alignment scope 106, so that the relative position falls within a tolerance range of the target relative position. During alignment, the substrate S and the mold M can be driven relatively by at least one of the mold driving mechanism 122 and the substrate driving mechanism 105. Alignment can involve alignment correction, as described below. For example, the target drive amount between the alignment mark of the shot area and the alignment mark of the mold M is determined based on the alignment mark position measured from the alignment mark image and the alignment error amount calculated using the alignment error amount calculation method described below. This alignment error amount can be reflected in the target relative position for all measured relative positions during alignment, or only in the final stage when the relative position is within a predetermined distance. The trained model used to calculate the alignment error amount is acquired in advance from an error amount calculation device, etc. Furthermore, if an abnormality in the amount of alignment error is detected, a separate process described below can be performed. In addition, in order to calculate a model for calculating the amount of alignment error in the error amount calculation device, the observed images of the alignment mark images in step S104 or data obtained from the observed images are accumulated and transmitted to the error amount calculation device.

[0032] Here, an example of a method for measuring the position of an alignment mark will be described. Fig. 4(a) shows an alignment mark image 401 for measuring the position in the X direction, and Fig. 4(b) shows an alignment waveform 406 obtained from the alignment mark image 401. The substrate S may have an alignment mark for generating the alignment mark image of Fig. 4(a) and an alignment mark for measuring the position in the Y direction, which is rotated 90 degrees from this alignment mark.

[0033] Mold M also has two types of alignment marks. In step S104, the relative positions (X direction and Y direction) of substrate S and mold M are calculated by measuring these alignment mark positions 402. In another example, diffraction gratings may be formed as alignment marks on substrate S and mold M, and moire, which is interference fringes that occur when these are superimposed, may be observed as alignment mark images. In this example, alignment scope 106 can be configured with a simple optical system.

[0034] Figure 5 shows an example of a method for calculating the position of an alignment mark using the alignment scope 106. Below, a method for measuring an alignment mark position 402 will be described using the alignment mark image 401 in Figure 4(a) as an example. The alignment mark position 402 is the center position of the alignment mark image in the measurement direction of the alignment mark (the X direction in the case of Figure 4(a)). In this example, the measurement direction 404 is the X direction, and the non-measurement direction 405 is the Y direction.

[0035] In step S501, the control unit 110 acquires an alignment mark image 401 by capturing an image of the alignment mark with the alignment scope 106. In step S502, the control unit 110 generates (calculates) an alignment waveform 406 based on the alignment mark image 401. For example, among the multiple pixels that make up the measurement area 403 of the alignment mark image 401 obtained as a digital image, the pixel values ​​in the non-measurement direction 405 (Y direction) are integrated at each position in the measurement direction 404 (X direction). This generates the alignment waveform 406.

[0036] In step S503, the control unit 110 calculates the alignment mark position 402 based on the alignment waveform 406. One example of a calculation method is to use the center of gravity of the alignment waveform 406 as the alignment mark position 402. Other examples include a method of calculating the alignment mark position by calculating the phase of the alignment waveform using a Fourier transform or the like, or a method of calculating the alignment mark position using a pattern matching method.

[0037] Returning to FIG. 1 , in step S105, the curing unit 107 irradiates the imprint material IM between the substrate S and the pattern region MP of the mold M with energy for curing the imprint material IM. This hardens the imprint material IM, forming a cured product of the imprint material IM. In step S106, the substrate S and the mold M are driven relatively by at least one of the mold driving mechanism 122 and the substrate driving mechanism 105, so that the cured product of the imprint material IM and the pattern region MP of the mold M are separated. In one example, the mold M is driven by the mold driving mechanism 122, so that the cured product of the imprint material IM and the pattern region MP of the mold M are separated. When the cured product of the imprint material IM and the pattern region MP of the mold M are separated, the pattern region MP of the mold M can also be deformed into a convex shape toward the substrate S. Furthermore, the imaging unit 112 captures an image, and the state of separation between the imprint material IM and the mold M can be observed based on the captured image.

[0038] In step S107, the control unit 110 determines whether the imprint processing of steps S102 to S106 has been performed on all shot areas of the substrate S. If the imprint processing of steps S102 to S106 has been performed on all shot areas of the substrate S, the control unit 110 proceeds to step S108, and if there are any unprocessed shot areas, the control unit 110 returns to step S102. In this case, the imprint processing of steps S102 to S106 is performed on a selected shot area from the unprocessed shot areas.

[0039] In step S108, the substrate S is transported from the substrate holding unit 102 to a destination (e.g., an intermediary unit to a post-processing device) by a substrate transport mechanism (not shown). When a lot consisting of multiple substrates is processed, the operation shown in Fig. 1 is performed for each of the multiple substrates.

[0040] In an imprinting apparatus, it is important to reduce alignment errors between the mold pattern portion and the shot area to form a pattern in the shot area on the substrate with high accuracy. In this embodiment, the magnitude of the alignment mark position error calculated from the alignment mark image is referred to as the "alignment error amount" (or simply "error amount"). The alignment error amount can be calculated, for example, by obtaining the difference (AB) between the alignment measurement value (A) and the overlay deviation amount (B) between the inspection mark on the base layer of the substrate S and the inspection mark on the layer formed thereon by the imprinting apparatus IMP. Alignment mark position errors can occur when the position is calculated from an inaccurate alignment waveform obtained due to noise in the alignment mark image 401. Noise can be generated by various factors. Below, several specific examples of noise generation are described.

[0041] Fig. 6 is a conceptual diagram of a moiré measurement system. Fig. 6(d) shows the principle of measuring relative position information between a shot area of ​​substrate S and a mold M based on moiré fringes, which are optical images formed by a first mark provided in the shot area of ​​substrate S and a second mark provided in mold M. Fig. 6(d) shows a first mark 3a provided in the shot area of ​​substrate S and a second mark 2a provided in mold M. The alignment scope 106 has an illumination optical system that illuminates the marks, and the illumination optical system has a pupil plane P. IL1, IL2, IL3, and IL4 indicate illumination light from poles formed on pupil plane P.

[0042] Illumination lights IL1 and IL2 are used to measure the relative position in the X direction between the shot area of ​​the substrate S and the mold M. As illustrated in FIG. 6(a), when measuring the relative position in the X direction, illumination lights IL3 and IL4, which are not used to measure the relative position in the X direction, can generate scattered light at the edges of the first mark 3a and the second mark 2a. This scattered light can become flare and be mixed into the moiré fringe signal (moiré fringe image data). FIG. 6(c) illustrates the signal intensity distribution in the X direction of the moiré fringe signal in FIG. 6(a) (the light intensity distribution on the light-receiving surface of the image sensor of the alignment scope 106). It can be seen that the scattered light from the edges of the first mark 3a and the second mark 2a causes large peaks on the left and right ends of the signal intensity distribution. Of the four periods of the moiré fringe signal, the two periods on the left and right ends are affected by the scattered light, which affects the measurement accuracy of the relative position. The same is true for measuring the relative position in the Y direction; illumination light IL1 and IL2 not used for measuring the relative position in the Y direction may generate scattered light at the edges of the first mark 3b and the second mark 2b. This scattered light may then become flare light and be mixed into the moiré fringe signal. The above explains how the light intensity distribution in the measurement direction may be affected by flare, but by a similar principle, the light intensity distribution in the non-measurement direction may also change due to the influence of flare. Changes in the light intensity distribution in the non-measurement direction may then reduce the relative position or position measurement accuracy in the measurement direction.

[0043] 7(a) and 8(a) illustrate signal waveforms obtained by calculating the sum of the signal values ​​of pixels located at the same position in the measurement direction (X direction) among the pixels constituting image data obtained using the alignment scope 106. The signal waveforms in FIGS. 7(a) and 8(a) can be understood as signal waveforms in the measurement direction. FIGS. 7(b) and 8(b) illustrate signal waveforms obtained by calculating the sum of the signal values ​​of pixels located at the same position in the non-measurement direction (Y direction) among the pixels constituting image data obtained using the alignment scope 106. The signal waveforms in FIGS. 7(b) and 8(b) can be understood as signal waveforms in the non-measurement direction. The examples in FIGS. 8(a) and 8(b) are more affected by flare light than the examples in FIGS. 7(a) and 8(b). The signal waveform in the measurement direction illustrated in FIG. 8(a) is more distorted than the signal waveform in the measurement direction illustrated in FIG. 7(a), which can result in an error 901 in the measurement result in the measurement direction. Furthermore, the signal waveform in the non-measurement direction shown in Figure 8(b) shows greater distortion and greater variation in signal values ​​than the signal waveform in the non-measurement direction shown in Figure 7(b). In other words, it can be seen that the signal waveform in the non-measurement direction has a correlation with the signal waveform in the measurement direction, i.e., the measurement result in the measurement direction. Therefore, by calculating the feature amount of image data related to the non-measurement method and correcting the provisional position information of the measurement object in the measurement direction obtained from the image data based on the feature amount, it is possible to determine the position information of the measurement object with high accuracy.

[0044] 9 and 10, an example of the relationship between the optical parameters of the alignment scope 106, the step structure, and the alignment accuracy will be described. FIG. 9(a) shows a plan view of an example alignment mark AM as seen from the Z direction. Here, the measurement direction is the X direction, and in this case, the alignment mark AM is represented as a single mark extending in the Y direction. FIGS. 9(b) and 9(c) show cross-sectional views of this alignment mark AM along the XZ plane. The alignment mark AM may have a structure in which a metal material such as tungsten is embedded in an insulating material such as SiO2. Furthermore, a photosensitive resist 2000 is applied to the top of the alignment mark AM. An alignment mark image can be captured by irradiating the alignment mark with light and obtaining reflected light.

[0045] In semiconductor processes, CMP (Chemical Mechanical Polishing) is sometimes used as a technique for planarizing the substrate surface. In this case, the alignment mark AM is polished by this process, which can cause its microscopic shape to change. Figure 9(b) shows a state in which the surface shape of the alignment mark AM has been polished to an ideal shape (so-called dishing). Here, the alignment mark AM is polished symmetrically with respect to a center line C extending in the Y direction. However, in actual CMP processes, the polishing conditions (polishing direction, polishing material, etc.) can cause deviations from the ideal state. Figure 9(c) shows a state in which the polishing state deviates from the ideal. Here, the alignment mark AM is polished asymmetrically with respect to the center line C, with the lowest position shifted by ΔX from the center in the X direction.

[0046] FIG. 10(a) shows a plan view of another example of an alignment mark AM as viewed from the Z direction. While the alignment mark AM in FIG. 9(a) is a single mark extending in the Y direction, the alignment mark AM in FIG. 10(a) is multiple marks extending in the Y direction. In the example of FIG. 10(a), the alignment mark AM is four marks extending in the Y direction. FIGS. 10(b) and 10(c) show cross-sectional views of the alignment mark AM along the XZ plane, similar to those in FIGS. 9(b) and 9(c). In the examples of FIGS. 10(b) and 10(c), in addition to the dishing phenomenon described above, portions that are not marks (i.e., between marks) are also eroded (so-called erosion). FIG. 10(b) shows a case in which such a phenomenon occurs symmetrically with respect to a center line C extending in the Y direction and passing through the center of the four marks in the X direction. 10(c) shows a state in which asymmetric erosion has occurred with respect to the center line C. The amount of this erosion phenomenon can vary depending on the density (e.g., line width, pitch) of the multiple alignment marks AM, the material, and the polishing conditions (e.g., polishing direction, polishing material).

[0047] As such, noise can be superimposed on alignment mark images due to various factors, which can cause alignment errors. However, not all noise necessarily causes errors. There are noises that are more likely to cause errors and noises that are less likely to cause errors. This is caused by the characteristics of the device's mechanisms, processing equipment, and processing methods, one of which is the characteristics of the measurement method.

[0048] In response to this, a measurement method can be considered in which the alignment waveform is converted into amplitude and phase values ​​for each frequency using frequency analysis such as Fourier transform, and the mark position is calculated based only on the phase of a specific frequency. This measurement method is robust against noise other than the measurement frequency, but may be sensitive to noise at the measurement frequency, even if it is so small that it cannot be detected visually.

[0049] Identifying only the noise that is affecting alignment errors among a wide variety of noises can efficiently improve alignment accuracy. For example, it becomes possible to correct alignment errors according to the magnitude of the specific noise, or to adjust, monitor, replace, or improve the design of the mechanisms, processing equipment, or processes that are causing alignment errors.

[0050] The processing of the alignment image in this embodiment will be described with reference to FIGS.

[0051] In step S201, the control unit 110 acquires a measurement value of one shot area on the substrate S obtained by measuring the substrate S with an overlay inspection device (a201 in FIG. 12). The information acquired here is the measurement result of the overlay accuracy at at least one point belonging to each shot area on the substrate. The measurement value indicates, for example, the amount of overlay deviation between (the overlay inspection mark of) the substrate's base layer and (the overlay inspection mark of) the imprinted layer. The amount of alignment error can be found by calculating the difference between the measurement value of the overlay inspection device and the final measurement value of the imprint device (the relative position between the alignment mark of the shot area and the alignment mark of the mold M).

[0052] In step S202, the control unit 110 acquires image data of the alignment mark image in one shot area of ​​the substrate S measured by the overlay inspection device (a202 in FIG. 12). The alignment mark image is the alignment mark image acquired in the above-mentioned step S104, and can be transmitted from the imprint apparatus to the error amount calculation device at any timing after the end of step S104.

[0053] Here, it is planned to acquire multiple alignment mark images with different alignment marks and / or measurement conditions, and the corresponding alignment error amounts. Therefore, in step S203, the control unit 110 determines whether acquisition of the planned image data has been completed. If image data to be acquired remains, the process returns to step S201 and is repeated to acquire other image data. If acquisition of the planned image data has been completed, the process proceeds to step S203. The above-mentioned "multiple different alignment mark images" can be, but are not limited to, images of alignment marks on multiple substrates. For example, the "multiple different alignment mark images" may be images of alignment marks in different shot areas on a single substrate, or images of alignment marks located at different coordinates in a single shot area. Furthermore, the "multiple different alignment mark images" may be acquired by capturing and measuring the position of the alignment mark under multiple measurement conditions with different light intensities and wavelengths. Furthermore, the "multiple different alignment mark images" may be acquired at any timing in the imprint sequence. Such timing can be, for example, immediately before or after the imprint material has hardened. Since the substrate S measured by the external overlay inspection device is in a state after the imprint material has hardened, using the substrate S in a hardened state can eliminate variations that occur when the imprint material hardens.

[0054] Through this process, a set of alignment mark images (X1, X2, X3, ..., X n ) (n is the number of acquired images) and the error amount (E1, E2, E3, ..., E n Here, the image of the alignment mark with width w [pixel] and height h [pixel] is obtained as X=(x 11 ,x 12 ,…,x hw ) is expressed as a vector with each pixel value as one element.

[0055] In step S204, the control unit 110 generates multiple image components (and information indicating their sizes) from all of the acquired alignment mark images using a statistical method (a204 in FIG. 12). The image components may include characteristic components in the image (such as signals and regular noise). One example of a statistical method is principal component analysis. Other examples of statistical methods include statistical analysis methods and dimension reduction methods that use multiple data, such as autoencoders and independent component analysis. The following describes a method for generating multiple image components using principal component analysis. By using principal component analysis, the alignment mark image group is transformed as follows: (X1,X2,X3,…,X n ) =C1(y 11 ,y 12 ,y 13 ,…,y 1n ) +C2(y 21 ,y 22 ,y 23 ,…,y 2n ) +C3(y 31 ,y 32 ,y 33 ,…,y 3n ) + … +C m (y m1 ,y m2 ,y m3 ,…,y mn ) where C1,C2,C3,…,C m is X1,X2,X3,…X n C1,C2,C3,…,C are vectors of the same size and can be treated as images. m are orthogonal to each other. 11 ,y 12 ,y 13 ,... are scalar values.

[0056] The above equation is X p , and the image component C q and the size of the image component y qpWhen there are several noises in the alignment mark image, each noise is divided into image components C1, C2, C3, ..., C m It is expected that m will appear as one of the following. m represents the number of decomposed image components, and its maximum value is n. p and q are arbitrary numbers.

[0057] In principal component analysis, the larger q is, the larger the image component size (y q1 ,y q2 ,y q3 ,…,y qn ) variance becomes smaller, and y qp The amount of information contained in C is small. Also, it can be calculated in order from image component C1. If it is determined that the amount of information is too small and the derivation of the correlation described later is unnecessary, C q The calculation may be interrupted midway.

[0058] In step S205, the control unit 110 outputs the generated multiple image components (and information indicating their sizes). The output data may be stored in a memory within the control unit or an external storage device, and / or displayed on a display unit (not shown). Then, in step S206, processing is performed based on the output multiple image components. The processing based on the multiple image components may include an operation by the user to identify noise that is causing an alignment error based on the displayed data.

[0059] Alternatively, the processing based on a plurality of image components may include processing for identifying noise causing alignment errors, which is executed by the control unit 110. A specific example of the content of such processing will be described below.

[0060] The control unit 110 calculates the correlation between the size of each of the plurality of image components and the value related to the measurement error. Specifically, the control unit 110 calculates the correlation between the size of the image component (y q1 ,y q2 ,y q3 ,…,y qn ) and the error amounts (E1, E2, E3, ..., En ) is calculated (a205 in FIG. 12). The control unit 110 can then perform processing to evaluate the influence of each of the multiple image components on the measurement error based on the calculated correlation coefficient. For example, the control unit 110 may select an image component C having a correlation coefficient higher than a predetermined value (e.g., 0.6), q can be identified as the noise component that is affecting the measurement error (the noise component that is causing the alignment error).

[0061] Alternatively, a combination of several image components (C q ,C r A multiple correlation coefficient between the magnitude of the noise components (...) and the amount of error may be calculated. Then, a combination of image components for which the correlation coefficient is higher than a predetermined value may be calculated, and image components included in that combination may be identified as noise components that have a large effect on the measurement error.

[0062] In the above example, the amount of error was obtained using an overlay inspection device, and the noise component causing the alignment error was identified based on that amount of error. Alternatively, the amount of error can be obtained from device data such as alignment measurement values, and the noise component causing the alignment error can be identified based on that amount of error.

[0063] In the above example, a method for generating multiple image components by principal component analysis of the alignment mark image has been described. Alternatively, multiple signal waveform components may be generated by applying a statistical method such as principal component analysis to the signal waveform obtained from the alignment mark image (alignment waveform 406 in FIG. 4).

[0064] In the above example, the measurement values ​​of the overlay inspection device for all shot areas and the alignment mark image are acquired, and principal component analysis is performed from the data. However, this is not limiting. For example, semiconductor exposure apparatuses and imprinting apparatuses employ a so-called global alignment method, in which alignment measurement is performed on a predetermined number of alignment sample shot areas among multiple shot areas on a substrate, and shot arrangement information (including linear components, higher-order components, etc.) is obtained through statistical processing of the results. To improve productivity, the shot areas measured by the overlay inspection device are often measured on a predetermined number of inspection sample shot areas rather than all shot areas on the substrate. Furthermore, the above-mentioned alignment sample shot areas and the inspection sample shot areas may not coincide. As a result, it is not possible to obtain data that corresponds one-to-one to the alignment image and the measurement values ​​of the overlay inspection device. However, in such cases, the shot arrangement of the entire substrate may be calculated from the measurement results of the inspection sample shot areas, and predicted values ​​of the measurement values ​​of the overlay inspection device in the alignment sample shot areas may be calculated. This makes it possible to obtain data equivalent to the alignment mark image and the measurement values ​​of the overlay inspection device. This makes it possible to perform the above-mentioned principal component analysis.

[0065] The above steps S201 to S206 are pre-processing for identifying image components including noise components that affect measurement errors. After this pre-processing, in step S207, the measurement object is imaged using a scope, and measurement processing is performed to obtain position information of the measurement object based on the results of processing based on the above-mentioned multiple image components.

[0066] (Alignment correction method) As described above, the control unit 110 determines the position information by calculating tentative position information of the measurement object based on the acquired image and correcting the tentative position information with a correction value based on a value related to the measurement error (alignment error amount). A method for correcting alignment using identified noise components will be described below. In this embodiment, a method is described in which multiple image components are generated by principal component analysis, the error amount is predicted from the magnitude of the image component with the highest correlation with the error amount by linear regression, and alignment correction is performed based on the predicted error amount. Other methods such as those described above may also be used to generate multiple image components. Furthermore, a regression method based on machine learning using SVM, gradient boosting, neural networks, etc. may also be used to predict the error amount. Furthermore, the error amount may also be predicted using multiple image components, such as by selecting several highly correlated components or by using a combination of image components with the highest multiple correlation coefficient.

[0067] In one example, a model for obtaining correction values ​​based on the feature quantities of the image is created. The creation procedure is basically the same as the example in FIG. 11. m are stored in the memory. After step S205, the control unit 110 also stores the error amounts (E1, E2, E3, ..., E n ) and the component C that has the highest correlation q (y q1 ,y q2 ,y q3 ,…,y qn ) the following regression equation is established: (E'1,E'2,E'3,...,E' n )=a×(y q1 ,y q2 ,y q3 ,…,y qn )+b

[0068] Thereafter, the control unit 110 uses the least squares method to find a and b that minimize the error between E and E', and stores the found values ​​in memory.

[0069] The model can be generated by machine learning, for example, with the error amount calculation device 1007 functioning as a model generation device. A specific example is as follows: First, a new layer (pattern) is formed under the same conditions in multiple shot areas of a substrate using an imprint device IMP. Then, an external overlay inspection device measures the amount of overlay misalignment between the base layer (overlay inspection mark) in each shot area and the newly formed layer (overlay inspection mark). Next, the error amount calculation device 1007 acquires the measured amount of overlay misalignment for each shot area and calculates the difference between the amount of overlay misalignment and the final measurement value when a new layer is formed in that shot area as the amount of alignment error. Then, the error amount calculation device 1007 performs machine learning using the feature amounts of the mark images in each shot area used to form the new layer as input data for the model and the calculated amount of alignment error as training data. At this time, if an abnormal value is present in the input data and / or training data, it is preferable to perform machine learning by excluding that data.

[0070] Next, the processing executed in the above-mentioned step S104 (alignment) will be described with reference to Fig. 13. In this processing, the amount of alignment error and / or the confidence factor is calculated using the created model.

[0071] In step S1301, the control unit 110 acquires a model for calculating the amount of error stored in memory. Note that the acquisition of the model does not need to be immediately before the next step S1302, and may be before the above-mentioned step S102, etc.

[0072] In step S1302, the control unit 110 acquires information (feature amounts) of the alignment mark image captured in step S104. In step S1303, the control unit 110 calculates the amount of alignment error using the model acquired in step S1301 and the feature amounts acquired in step S1302. In this embodiment, the control unit 110 calculates the amount of alignment error using the acquired image X0, C1, C2, C3, ..., C output in step S205. m For X0=C1y10 +C2y 20 +C3y 30 +…+C m y m0 y such that 10 ,…,y m0 Thereafter, the control unit 110 calculates the image component C having the largest correlation coefficient selected in the process of identifying noise. q for y q0 The prediction error amount E' is calculated using the following formula. The prediction error amount E' is expressed by the following formula. a×y q0 +b=E'

[0073] By applying post-processing to this prediction error, the correction amount can be adjusted. For example, upper and lower limits can be set in advance to keep the value within a certain range, or the scale can be converted by multiplying it by α.

[0074] In step S1304, the control unit 110 uses the calculated amount of alignment error or a value calculated based on the amount of alignment error as a correction amount for alignment measurement.

[0075] Furthermore, as a learning method, the confidence level of the error amount prediction can be calculated by using Bayesian estimation, which performs inference taking uncertainty into account by treating variables as probabilities. The confidence level is an index (information) that indicates the degree to which it can be believed that the estimated registration error amount is highly accurate, and may be understood as likelihood and / or reliability. Examples of prediction models using Bayesian estimation include Gaussian process regression, generalized linear models, and hierarchical Bayesian models. When using a Bayesian estimation model, the model is a function that inputs feature values ​​and outputs a probability distribution of the registration error amount, and internal variables are optimized through learning. The expected value of the probability distribution of the obtained error amount can be used as the inferred value of the error amount, and the variance of the probability distribution can be used as the confidence level.

[0076] This confidence level or a value calculated based on the confidence level can be used to detect an abnormality in the alignment. For example, there is a method of detecting an abnormality when the confidence level falls below a preset threshold. In response to this abnormality detection, the control unit 110 can perform control different from that used for normal alignment.

[0077] A specific example of this control, which differs from normal alignment, will be explained below. Consider a control in which, for each shot area of ​​the substrate, the relative position between the original and the substrate is aligned to a target relative position using the measurement values ​​of one or more alignment marks arranged in the shot area. Here, the designed x-direction positions of the alignment marks in the shot area are denoted by x1, x2, ..., and y-direction positions by y1, y2, .... Also, the alignment measurement values ​​in the x-direction are denoted by d x1 , d x2 ,…, the alignment measurement value in the y direction is d y1 , d y2 , .... Using these, we determine the target relative position s that minimizes the following evaluation formula V: x ,s y ,θ x ,θ y ,β x ,β y where n is the number of alignment marks.

[0078]

number

[0079] where s x ,s y is the shift component of the target relative position, θ x ,θ y is the rotation component, β x ,β y represents the elongation component. The control unit 110 controls the position of at least one of the original and the substrate based on these components.

[0080] At this time, d x1 ,d x2 ,d y1 ,d y2If extremely large abnormal values ​​are included in [ , ... ], each component of the relative position will be strongly influenced by the abnormal value, making it impossible to calculate an accurate value. Therefore, the control unit 110 calculates the certainty of the alignment marks within the shot area. If the certainty of a certain mark is below a threshold, the measurement value of that mark is not used and the relative position is calculated using the measurement values ​​of the remaining marks, making it possible to calculate a relative position that is not influenced by abnormal values. Alternatively, the influence of abnormal values ​​can be reduced without setting a threshold by calculating the target relative position using the following equation, which includes multiplying the measurement value of each mark by a weight w according to the certainty:

[0081]

number

[0082] It is also possible to extend the alignment control time when an abnormality is discovered, and then perform normal alignment if the confidence level increases. This is effective when the alignment mark image is not formed properly because the imprint material is not sufficiently filled in the pattern area, and this is detected as an abnormality. In such cases, the imprint material may be filled over time, and the alignment mark image will be formed properly and the confidence level of the mark will also increase.

[0083] (Method of adjusting measurement conditions) In one example, the control unit 110 can be configured to determine or adjust adjustment parameters for adjusting the measurement device based on the size of each of the multiple image components. Here, the adjustment parameters can include at least one of the position and orientation of the measurement object, the wavelength of the illumination light generated by the scope, the illumination σ value, the NA, and the position and orientation of the optical components that make up the scope. A specific example is shown below.

[0084] Once the above noise components have been identified, high-precision measurements can be achieved by eliminating the main cause of the noise components, in addition to performing alignment correction. For example, the use of a highly coherent light source (wavelength) can generate interference fringes in optical components within the alignment measurement instrument. If these interference fringes are superimposed on the measurement signal, they can cause measurement value errors, and therefore the light source (wavelength) can be identified as a noise component. In such cases, methods to reduce the coherence can be considered, such as selecting a broadband wavelength or, in the case of a semiconductor laser, modulating the drive current to broaden the wavelength. Furthermore, by tilting the optical components generating the interference fringes, for example, by configuring a drive system to tilt them so that they do not affect the measurement value, measurement errors can be reduced, enabling more accurate measurements. Furthermore, if measurement errors are caused by a distorted surface shape of the alignment mark, using another alignment mark within the shot area for measurement can potentially improve the results. Furthermore, in addition to the parameters of the imprinting device, polishing conditions (polishing direction, polishing material, etc.) can be changed, such as the materials used in processes prior to imprinting.

[0085] These adjustment methods can be realized, for example, by transmitting information such as the image components and their sizes output in step S205 to the control device 1003 and issuing parameter change commands to each device. The control device 1003 may automatically determine command values ​​based on the received information, or may determine command values ​​according to instructions from a user. Alternatively, the above adjustment methods can be realized by transmitting the information externally and using parameters calculated by an external computer in each device. The information can also be displayed, and an operator can change the parameters according to the values. Image components and their sizes can also be monitored to maintain quality during mass production. For example, there is a method of sending an external notification when a change occurs.

[0086] Second Embodiment 14 schematically shows the configuration of an exposure apparatus EP according to the second embodiment. The exposure apparatus EP may include an illumination device 1800, a reticle stage RS on which a reticle 1031 (original) is placed, a projection optical system 1032, a substrate stage WS on which a substrate 1403 is placed, a measurement device 1802, and an arithmetic processing unit 1400. A reference plate 1039 is disposed on the substrate stage WS. A control unit 1803 is electrically connected to and controls the illumination device 1800, the reticle stage RS, the substrate stage WS, and the measurement device 1802. In this embodiment, the control unit 1803 may also perform correction calculations and control of the measurement value of the surface height position of the substrate 1403 measured by the measurement device 1802. The control unit 1803 may be configured, for example, by a PLD such as an FPGA, an ASIC, a general-purpose computer with an embedded program, or a combination of all or part of these. For example, the control unit 1803 may include a processor 1803a and a storage unit 1803b that stores programs and data.

[0087] The illumination device 1800 includes a light source unit 1810 and an illumination optical system 1801, and illuminates a reticle 1031 on which a circuit pattern to be transferred is formed. The illumination optical system 1801 may have a function of uniformly illuminating the reticle 1031 and a function of polarized illumination. The light source unit 1810 uses, for example, a laser. The laser may be an ArF excimer laser with a wavelength of approximately 193 nm or a KrF excimer laser with a wavelength of approximately 248 nm, but the type of light source is not limited to an excimer laser. For example, an F2 laser with a wavelength of approximately 157 nm or EUV (Extreme ultraviolet) light with a wavelength of 20 nm or less may also be used.

[0088] The illumination optical system 1801 is an optical system that illuminates an illuminated surface using a light beam emitted from a light source unit 1810, and in this embodiment, it shapes the light beam into an exposure slit of a predetermined shape optimal for exposure, and illuminates the reticle 1031. The illumination optical system 1801 may include lenses, mirrors, an optical integrator, a diaphragm, etc. These are arranged, for example, from the light source side, in the following order: a condenser lens, a fly's-eye lens, an aperture diaphragm, a condenser lens, a slit, and an imaging optical system.

[0089] The reticle 1031 is made of, for example, quartz, and has a circuit pattern to be transferred formed thereon. The reticle 1031 is supported and driven by a reticle stage RS. Diffracted light emitted from the reticle 1031 passes through a projection optical system 1032 and is projected onto a substrate 1403. The reticle 1031 and the substrate 1403 are arranged in an optically conjugate relationship. The pattern on the reticle 1031 is transferred onto the substrate 1403 by scanning the reticle 1031 and the substrate 1403 at a speed ratio that corresponds to the reduction magnification ratio. The exposure apparatus EP is provided with a reticle detection device with an oblique incidence system (not shown), and the position of the reticle 1031 can be detected by the reticle detection device and positioned at a predetermined position.

[0090] The reticle stage RS supports the reticle 1031 via a reticle chuck (not shown) and is connected to a movement mechanism (not shown). The movement mechanism is configured with a linear motor or the like and has multiple degrees of freedom (for example, three axes of X, Y, and θZ, or preferably six axes of X, Y, Z, θX, θY, and θZ), and can move the reticle 1031 by driving the reticle stage RS.

[0091] The projection optical system 1032 has the function of forming an image of a light beam from an object plane onto an image plane, and in this embodiment, forms an image of diffracted light that has passed through a pattern formed on the reticle 1031 onto the substrate 1403. The projection optical system 1032 can be an optical system made up of multiple lens elements, an optical system having multiple lens elements and at least one concave mirror (catadioptric optical system), or an optical system having multiple lens elements and at least one diffractive optical element such as a kinoform.

[0092] The substrate 1403 is an object to be processed, and photoresist is applied onto the substrate. In this embodiment, the substrate 1403 is an object to be detected, in which the position of the mark 1039 on the substrate 1403 is detected by the measuring device 1802. The substrate 1403 is also an object to be detected, in which the surface position of the substrate 1403 is detected by a surface position detecting device (not shown). The substrate 1403 may be a liquid crystal substrate or another object to be processed.

[0093] The substrate stage WS supports the substrate 1403 by means of a substrate chuck (not shown). Like the reticle stage RS, the substrate stage WS is configured with a linear motor or the like, and has multiple degrees of freedom (for example, three axes of X, Y, and θZ, or preferably six axes of X, Y, Z, θX, θY, and θZ) to move the substrate 1403. Furthermore, the positions of the reticle stage RS and the substrate stage WS are monitored by, for example, a six-axis laser interferometer 1081, and the two are driven at a constant speed ratio by a stage control unit 1804.

[0094] 15 shows an example configuration of a measurement device 1802. The measurement device 1802 may include an illumination system that illuminates the substrate 1403 with light emitted from an optical fiber 1061, and an imaging system that forms an image of a mark 1072 provided on the substrate 1403. The illumination system may include illumination optical systems 1062, 1063, and 1065, an illumination aperture stop 1064, a mirror M2, a relay lens 1067, a polarizing beam splitter 1068, a λ / 4 plate 1070, and an objective optical system 1071. The imaging system includes the objective optical system 1071, the λ / 4 plate 1070, a detection aperture stop 1069, a polarizing beam splitter 1068, and an imaging optical system 1074, and is configured to form an image of the light reflected from the mark 1072 on an imaging sensor 1075. The measuring device 1802 obtains the coordinate position of the mark 1072 based on the position information of the substrate stage WS measured by the laser interferometer 1081 and the signal waveform detected for the mark 1072 .

[0095] In the measurement device 1802, light emitted from an optical fiber 1061 passes through illumination optical systems 1062 and 1063 and reaches an illumination aperture stop 1064 located at a position conjugate with the substrate 1403. At this time, the beam diameter at the illumination aperture stop 1064 is sufficiently smaller than the beam diameter at the optical fiber 1061. The light passing through the illumination aperture stop 1064 passes through an illumination optical system 1065, a mirror M2, and a relay lens 1067 and is guided to a polarizing beam splitter 1068. The polarizing beam splitter 1068 transmits P-polarized light parallel to the Y direction and reflects S-polarized light parallel to the X direction. Therefore, the P-polarized light transmitted through the polarizing beam splitter 1068 passes through a detection aperture stop 1069 and a λ / 4 plate 1070, where it is converted into circularly polarized light, and passes through an objective optical system 1071 to Koehler illuminate a mark 1072 formed on the substrate 1403.

[0096] The light reflected, diffracted, and scattered by the mark 1072 passes through the objective optical system 1071 again, then passes through the λ / 4 plate 1070, where it is converted from circularly polarized light to S-polarized light, and reaches the detection aperture stop 1069. Here, the polarization state of the light reflected by the mark 1072 becomes circularly polarized in the opposite direction to the circularly polarized light that irradiated the mark 1072. In other words, if the polarization state of the light that irradiated the mark 1072 was right-handed circularly polarized, the polarization state of the light reflected by the mark 1072 will be left-handed circularly polarized. Furthermore, the detection aperture stop 1069 changes its aperture size in response to a command from the control unit 1803, thereby switching the numerical aperture of the light reflected from the mark 1072. The light that passed through the detection aperture stop 1069 is reflected by the polarizing beam splitter 1068 and then guided to the image sensor 75 via the imaging optical system 74. Therefore, the optical path of the illumination light to the substrate 1403 and the optical path of the reflected light from the substrate 1403 are separated by the polarizing beam splitter 1068 , and an image of the mark 1072 provided on the substrate 1403 is formed on the image sensor 75 .

[0097] The optical fiber 1061 guides light from a light source 1050 configured by a separately installed halogen lamp, metal halide lamp, plasma light source, LED, or the like. A wavelength filter 51 that can change the wavelength to be transmitted is disposed between the light source 1050 and the optical fiber 1061. The wavelength filter 51 is configured to pass a wavelength band selected based on the quality of the image obtained when observing the mark 1072 (for example, contrast and measurement accuracy, which will be described later).

[0098] The illumination aperture stop 1064 has a switching mechanism (e.g., a rotation mechanism) not shown, which allows it to change the shape of the transmitted light source distribution. For example, the illumination aperture stop 1064 can selectively change the size of the opening (so-called illumination σ value), enabling modified illumination, etc. Furthermore, the shape of the opening can also change the image quality of the mark 1072, as will be described later. The illumination aperture stop 1064 has, for example, four openings 1055a, 1055b, 1055c, and 1055d formed on a disk as shown in FIG. 16 , and by rotating the disk, one of these four openings is positioned on the optical axis. In this way, the illumination state can be changed by selecting the opening to be positioned on the optical axis. Note that the mechanism for modifying the illumination state is not limited to the one shown in this example, and those skilled in the art will easily appreciate that similar effects can be obtained using various shapes and combinations.

[0099] As described above, the quality of the image of the mark 1072 can be changed by changing optical parameters such as the wavelength, the illumination aperture stop 1064, and the detection aperture stop 1069. An example of this will be described with reference to FIGS.

[0100] 17 shows an example of mark 1072 in the XY plane. Mark 1072 includes two marks 1052X1 and 1052X2 aligned in the X direction and two marks 1052Y1 and 1052Y2 aligned in the Y direction. Measurement of mark 1072 by measurement device 1802 may result in measurement errors due to process effects such as CMP, etching, and uneven resist application. In particular, in the case of a mark for performing such measurements in two directions, asymmetry in the mark shape, as described below, may occur not only in the measurement direction but also in directions other than the measurement direction.

[0101] 18(A) focuses on only one of the marks 1072 shown in FIG. 17 (e.g., mark 1052X2) and shows a cross section (ZX cross section) of the mark. This mark has a step structure 1054, on which a resist 1053 is applied. The resist 1053 is generally a liquid resist applied to a substrate by spin coating. When the liquid resist 1053 is applied to the mark, it may be applied asymmetrically with respect to the step structure 1054. When the resist is applied in such an asymmetric state, the observed alignment image also becomes asymmetric, resulting in measurement errors.

[0102] 18(B) to 18(E) show examples of signal waveforms of mark images. Here, the horizontal axis represents the position in the X direction, and the vertical axis represents the signal intensity. FIG. 18(B) shows a signal waveform when the optical parameters (illumination light wavelength, illumination σ value) are set to predetermined values. In this signal waveform, the signal intensity difference at the mark edge is small, resulting in low contrast. When the contrast is low, the measurement accuracy decreases, so the control unit 1803 changes the optical parameters to enhance the contrast. FIG. 18(C) shows a signal waveform of a mark image acquired by changing the illumination light wavelength, which is one of the optical parameters used to obtain the signal waveform of FIG. 18(B). In this signal waveform, the signal intensity difference at the mark edge is amplified, but because the coating state of the resist 1053 is asymmetric, the signal intensity between the left and right mark edges becomes asymmetric, resulting in a measurement error.

[0103] FIG. 18(D) shows the signal waveform of the mark image acquired by reducing the illumination σ value, one of the optical parameters used to obtain the signal waveform in FIG. 18(C). By reducing the illumination σ value, the difference in signal intensity at the mark edges is amplified while maintaining the symmetry of the signal intensity between the left and right mark edges, thereby enhancing the contrast. This phenomenon can be adjusted by changing the focus position of the mark 1072. Specifically, by changing the focus position of the mark 1072, the amount of contrast enhancement and the position in the X direction where the enhancement occurs can be changed. Therefore, the measurement device 1802 can perform measurements at the optimal focus position depending on the measurement conditions (contrast, measurement error, etc.).

[0104] Figure 18(E) shows the signal waveform of the mark image acquired by increasing the wavelength of the illumination light, one of the optical parameters used to obtain the signal waveform of Figure 18(B). Because resist 1053 is applied to the mark, the interference conditions between the recesses and protrusions in the step structure 1054 are different, and if a large phase difference occurs, the relationship between the signal intensity of the recesses and the signal intensity of the protrusions changes. In marks used in actual semiconductor processes, rather than the simple step mark of this example, the change in contrast that occurs when the wavelength of the illumination light is changed is often more pronounced. In any case, changing the wavelength depending on the mark will result in a different appearance of the obtained mark image.

[0105] FIG. 19(A) is a plan view (XY plan view) of a mark coated with resist, focusing only on mark 1052X1 of mark 1072 shown in FIG. 17. The mark has a step structure 1054, on which resist 1053 is coated. Resist 1053 is typically applied as a liquid resist by spin coating onto a substrate. When liquid resist 1053 is applied to the mark, it may be applied asymmetrically in the non-measurement direction (Y direction in this figure) relative to step structure 1054, just as it is in the measurement direction. When the resist is applied asymmetrically, the edge shape in the non-measurement direction of the observed alignment image also becomes asymmetric. The degree of this asymmetry is similar to the degree of asymmetry in the measurement direction and corresponds to the magnitude of the measurement error in the measurement direction. Thus, the signal intensity obtained by integrating the non-measurement direction along the horizontal axis (X axis in this figure) is constant when the resist is uniformly applied, but varies significantly when the resist is unevenly applied. Therefore, the signal intensity obtained by integrating in the non-measurement direction can be said to be a feature quantity that can more clearly determine the unevenness of the resist coating state, that is, the degree of asymmetry.

[0106] 19(B) to 19(E) show examples of signal intensity waveforms obtained by integrating the signal intensity in the non-measurement direction of the mark image. Here, the vertical axis represents the position in the Y direction, and the horizontal axis represents the signal intensity. FIG. 19(B) shows a signal waveform obtained when the optical parameters (illumination light wavelength, illumination σ value) are set to predetermined values. In this signal waveform, the signal intensity (contrast) is low. When the signal intensity is low, the measurement accuracy decreases, so the control unit 1803 changes the optical parameters to increase the signal intensity. FIG. 19(C) shows a signal waveform of a mark image obtained by changing the illumination light wavelength, which is one of the optical parameters used to obtain the signal waveform of FIG. 19(B). Although the signal intensity is amplified in this signal waveform, the change in signal intensity due to the asymmetrical coating state of the resist is emphasized, which causes measurement errors.

[0107] Figure 19(D) shows the signal waveform of the mark image acquired by reducing the illumination σ value, one of the optical parameters used to obtain the signal waveform in Figure 19(C). Reducing the illumination σ value enhances the signal intensity at the mark edge, increasing contrast. This phenomenon can be adjusted by changing the focus position of the mark 1072. Specifically, by changing the focus position of the mark 1072, the amount of contrast enhancement and the position in the X direction where enhancement occurs can be changed. Therefore, the measurement device 1802 can perform measurements at the optimal focus position depending on the measurement conditions (contrast, measurement error, etc.). When the focus position is properly adjusted, the influence of resist asymmetry is reduced, resulting in smaller changes in the obtained signal intensity, which can be suitable for alignment.

[0108] Figure 19(E) shows the signal waveform of the mark image acquired by increasing the wavelength of the illumination light, one of the optical parameters used to obtain the signal waveform of Figure 19(B). Because resist 1053 is applied to the mark, the interference conditions between the recessed and protruding portions are different. If a large phase difference occurs, the relationship between the signal intensity of the recessed and protruding portions changes. The signal waveform of Figure 19(E) shows a slight but larger change than the signal waveform of Figure 19(D). For marks used in actual semiconductor processes, rather than the simple step mark of this example, the change in the signal in the non-measurement direction caused by changing the wavelength of the illumination light is often more pronounced. In any case, changing the wavelength depending on the mark will result in a different appearance for the resulting mark image.

[0109] However, in semiconductor processes, due to various factors, there are cases where measurement cannot be performed under the conditions with little distortion as shown in Figure 18(D) or Figure 18(E), or where distortion as shown in Figure 18(C) occurs under any optical conditions. In such cases, high-precision alignment measurement is possible by extracting the noise waveform components that cause measurement position errors from the distortion state of the alignment waveform using principal component analysis, and then calculating and correcting the amount of correction.

[0110] FIG. 20(f) shows multiple shot areas 1080 on a substrate 1073. The multiple shot areas 1080 include alignment sample shot areas SS1 to SS5. A mark 1072 is formed in each alignment sample shot area. Since resist is generally applied by spin coating, the uneven resist application shown in FIG. 18(A) occurs concentrically around the center of the substrate. FIGS. 20(a) to 20(e) show alignment signals in the X direction in this case. The signal waveforms in FIGS. 20(a) to 20(e) are asymmetric when viewed individually, but as a whole they may be line-symmetric with respect to the center line of the substrate, which is parallel to the Y direction. However, individual signal waveforms change depending not only on the step structure of the alignment mark but also on the structure of the periphery of the alignment mark (actual element region), variations in the spin coater, variations in spin coating conditions, etc., so they are not necessarily line-symmetric as a whole. Therefore, as described above, by comparing the measurement values ​​(predicted values) of the overlay inspection device with these acquired alignment images (signals), a correction value can be calculated from the distortion of the waveform, and alignment can be performed using this correction value when exposing the substrate thereafter.

[0111] Furthermore, if alignment measurement is performed under specified optical conditions and principal component analysis is performed, and noise waveform components are detected, it is possible to reduce measurement errors by changing the optical conditions. In this case, the same substrate and the same mark are measured under multiple optical conditions and images are acquired. This is then performed on multiple substrates and multiple marks, and principal component analysis is performed in the same way. The alignment measurement values ​​and images under each optical condition, as well as specific overlay results, are compared, and principal component analysis is performed to determine optical conditions under which noise waveform components are not detected, making it possible to find the optimal optical conditions.

[0112] This principal component analysis may be performed on a so-called "test board" and the results may be used to correct subsequent "production boards," but it may also be possible to continue this principal component analysis on "production boards" all the time and modify the model each time.

[0113] In addition, although the above example has been described as a one-dimensional waveform, it is not limited to this. In the case of a two-dimensional image, it is also possible to perform principal component analysis on information in a non-measurement direction, which is particularly effective for the mark shown in this example that measures two directions.

[0114] For alignment marks in the above-described apparatus configuration, noise components can be identified in the same way as for the alignment mark images and alignment waveforms in the first embodiment.

[0115] <Embodiment of an article manufacturing method> A method for manufacturing an article using the above-described lithography apparatus will now be described. The method includes a transfer step of transferring a pattern of an original onto a substrate using the above-described lithography apparatus, and a processing step of processing the substrate that has undergone the transfer step, and obtains an article from the substrate that has undergone the processing step.

[0116] Below, with reference to FIG. 21 , a method for manufacturing an article using an imprint apparatus, which is an example of a lithography apparatus, will be described. A pattern of a cured product formed using the imprint apparatus is used permanently on at least a portion of various articles, or temporarily when manufacturing various articles. Examples of articles include electrical circuit elements, optical elements, MEMS, recording elements, sensors, and molds. Examples of electrical circuit elements include volatile or non-volatile semiconductor memories such as DRAM, SRAM, flash memory, and MRAM, and semiconductor elements such as LSI, CCD, image sensors, and FPGAs. Examples of molds include molds for imprinting.

[0117] The pattern of the cured product may be used as it is as at least a part of a component of the article, or may be used temporarily as a resist mask, which is removed after etching or ion implantation in a substrate processing step.

[0118] 21, a substrate 1z such as a silicon substrate is prepared, on the surface of which a workpiece 2z such as an insulator is formed, and then an imprint material 3z is applied to the surface of the workpiece 2z by an inkjet method, etc. Here, a state in which multiple droplets of the imprint material 3z have been applied to the substrate is shown.

[0119] In step SB of Fig. 21, an imprinting mold 4z is placed facing the imprinting material 3z on the substrate, with the side on which the concave-convex pattern is formed. In step SC of Fig. 21, the substrate 1z to which the imprinting material 3z has been applied is brought into contact with the mold 4z, and pressure is applied. The imprinting material 3z fills the gap between the mold 4z and the workpiece 2z. In this state, when light is irradiated through the mold 4z as hardening energy, the imprinting material 3z hardens.

[0120] 21, after the imprint material 3z is cured, the mold 4z is separated from the substrate 1z, forming a pattern of the cured imprint material 3z on the substrate 1z. In this cured material pattern, the recesses of the mold correspond to the protrusions of the cured material, and the protrusions of the mold correspond to the recesses of the cured material, i.e., the recess-protrusion pattern of the mold 4z is transferred to the imprint material 3z.

[0121] In step SE of Fig. 21, etching is performed using the cured material pattern as an etching-resistant mask, and portions of the surface of the workpiece 2z where no cured material or only a thin layer remains are removed, forming grooves 5z. In step SF of Fig. 21, the cured material pattern is removed, resulting in an article with grooves 5z formed in the surface of the workpiece 2z. Here, the cured material pattern is removed, but it may also be used as an interlayer insulating film included in a semiconductor element or the like, i.e., a component of an article, without being removed after processing.

[0122] (Other embodiments) The present invention can also be realized by supplying a program that realizes one or more functions of the above-described embodiments to a system or device via a network or a storage medium, and having one or more processors in the computer of the system or device read and execute the program. It can also be realized by a circuit (e.g., ASIC) that realizes one or more functions.

[0123] The invention is not limited to the above-described embodiments, and various changes and modifications can be made without departing from the spirit and scope of the invention. Accordingly, the following claims are appended to apprise the public of the scope of the invention. [Explanation of symbols]

[0124] IMP: imprinting device, S: substrate, M: mold, 110: control unit, 102: substrate holder, 105: substrate driving mechanism, 121: mold holder, 122: mold driving mechanism

Claims

1. A measurement device that measures position information of a measurement object, a scope that captures an image of the measurement object and generates an image; a processor for determining position information of the measurement object based on the image; The processor: generating a plurality of image components from a plurality of images generated by the scope using a statistical method; outputting the generated plurality of image components; performing a process of determining a component related to a measurement error based on the plurality of image components; determining the position information based on an image produced by the scope and a component related to the measurement error; The process comprises: generating the plurality of image components and information indicating the magnitudes of the plurality of image components from the plurality of images using the statistical method; calculating a correlation coefficient between the magnitude of each of the plurality of image components and the value related to the measurement error; evaluating the influence of each of the plurality of image components on the measurement error based on the correlation coefficient; Including, A measuring device characterized by:

2. The measuring device according to claim 1 , wherein the processor outputs the plurality of image components to a display unit.

3. 2. The measurement device according to claim 1, wherein the evaluating step includes identifying, from among the plurality of image components, image components having a correlation coefficient higher than a predetermined value as image components that include noise components that affect the measurement error.

4. The processor: determining tentative position information of the measurement object based on the image; determining the position information by correcting the tentative position information with a correction value based on the value related to the measurement error; 2. The measuring device according to claim 1.

5. 5. The measuring device according to claim 4, further comprising a model for obtaining a value relating to the measurement error based on a feature amount of the image.

6. The measurement device according to claim 5 , further comprising a machine learning unit that generates the model by machine learning.

7. 7. The measurement device according to claim 6, wherein the machine learning unit performs machine learning using the feature as input data for a model and a difference between position information of the measurement object measured by an external inspection device and position information determined by the processor as training data.

8. The measurement device according to claim 1 , wherein the processor determines adjustment parameters for adjusting the measurement device based on the magnitudes of the plurality of image components.

9. 9. The measurement apparatus according to claim 8, wherein the adjustment parameters include at least one of a position and orientation of the measurement object, a wavelength of illumination light generated by the scope, an illumination σ value, an NA, and a position and orientation of optical components that constitute the scope.

10. The measurement apparatus according to claim 1 , wherein the statistical method is one of principal component analysis, autoencoder, and independent component analysis.

11. 11. The measurement apparatus according to claim 1, wherein the measurement object is a mark.

12. 11. The measurement device according to claim 1, wherein the measurement object is a moiré fringe formed by a first mark on a first member and a second mark on a second member, and the position information is relative position information between the first mark and the second mark.

13. A measurement device that measures position information of a measurement object, a scope that captures an image of the measurement object and generates an image; a processor for determining position information of the measurement object based on a signal waveform obtained from the image, The processor: generating a plurality of signal waveform components from a plurality of signal waveforms obtained from a plurality of images generated by the scope using a statistical method; outputting the generated plurality of signal waveform components; performing a process of determining a component related to a measurement error based on the plurality of signal waveform components; determining the position information based on an image produced by the scope and a component related to the measurement error; The process comprises: generating information indicating the magnitude of each of the plurality of signal waveform components using the statistical method; calculating a correlation coefficient between the magnitude of each of the plurality of signal waveform components and the value related to the measurement error; evaluating the influence of each of the plurality of signal waveform components on the measurement error based on the correlation coefficient; Including, A measuring device characterized by:

14. 1. A lithography apparatus for transferring a pattern of an original onto a substrate, comprising: a measuring device according to any one of claims 1 to 13 configured to measure the relative position between the substrate and the original; performing alignment between the substrate and the original based on the output of the measurement device; 1. A lithography apparatus comprising:

15. a transfer step of transferring a pattern onto a substrate using the lithographic apparatus of claim 14; a processing step of processing the substrate that has undergone the transfer step, A method for manufacturing an article, characterized in that an article is obtained from the substrate that has been subjected to the processing step.

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