System and method to map thickness variations of substrates in manufacturing systems

Abstract

The disclosed implementation particularly describes a system and method that involves scanning a substrate with a light beam and detecting, for each of a set of locations on the substrate, a corresponding value from a set of intensity values ​​associated with the light beam reflected from (or transmitted through) the substrate. The detected intensity values ​​are used to determine the approximate thickness of the substrate.

Description

[Technical Field]

[0001] This specification is broadly about ensuring the quality control of materials manufactured in a substrate processing system. More specifically, this specification concerns the optical inspection of substrate thickness variations during various stages of the manufacturing process. [Previous Technology]

[0002] The manufacture of modern materials often involves various deposition techniques, such as chemical vapor deposition (CVD) or physical vapor deposition (PVD), in which one or more selected types of atoms are deposited on a substrate (wafer) held in a low or high vacuum environment provided by a vacuum deposition chamber. Materials manufactured in this way can include single crystals, semiconductor films, fine coatings, and many other substances for practical applications, such as electronic component manufacturing. Many of these applications rely on the purity of the materials grown in the substrate handling system. The need to maintain the isolation between chamber environments and minimize their exposure to the surrounding atmosphere and contaminants has led to various robotic techniques for sample manipulation and inspection. Improving the accuracy, reliability, and efficiency of these robotic techniques presents numerous technical challenges, and successfully addressing these challenges will promote the continued advancement of electronic component manufacturing. This is particularly relevant given the ever-increasing demands for the quality of chamber-manufactured products. [Summary of the Invention]

[0003] In one embodiment, this disclosure provides a method comprising: scanning a substrate with a first beam; obtaining, for each of a plurality of locations on the substrate, a corresponding one of a first plurality of intensity values ​​associated with a second beam, wherein the second beam is caused by the interaction between the first beam and the substrate; and using the first plurality of intensity values ​​to determine profile data characterizing a change in the thickness of the substrate.

[0004] In another embodiment, this disclosure provides a system configured to scan a substrate, the system comprising: a first light source for emitting a first light beam; a first optical sensor for obtaining, for each of a plurality of locations on the substrate, a corresponding one of a first plurality of intensity values ​​associated with a second light beam, wherein the second light beam is caused by the interaction between the first light beam and the substrate; and a processing device for using the first plurality of intensity values ​​to determine profile data characterizing a change in the thickness of the substrate.

[0005] Furthermore, in another embodiment, this disclosure provides a system comprising: a movable stage for supporting a substrate; a light source for guiding a first light beam to scan the substrate transported on the movable stage; a first optical sensor for obtaining, for each of a plurality of locations on the substrate, a corresponding one of a first plurality of intensity values ​​associated with a second light beam, wherein the second light beam is caused by the interaction between the first light beam and the substrate; and a processing device communicatively coupled to the first optical sensor to generate profile data characterizing changes in the thickness of the substrate.

Implementation Method

[0014] The embodiments disclosed herein provide optical mapping of thickness variations in substrates and wafers attributable to non-uniformity caused by wafer fabrication processes (including polishing, etching, material deposition, and the like) used to smooth, add, and / or remove material. For example, the disclosed embodiments may be able to determine wafer thickness metrology using methods that can be integrated into larger processing tools, such as chemical-mechanical polishing (CMP). For example, wafer metrology may include determining variations in thickness profile caused by deposition and / or etching operations. In some embodiments, deposition may include epitaxial silicon carbide (SiC) deposition, which may occur after CMP. Furthermore, once the thickness variation profile is known, metrology data may indicate how to optimally correct undesired thickness variations and form a surface that is as uniform as possible (or achieve other target thickness variations that may be specified by the technical processes being performed). For example, the thickness variation profile may be used in feedback processes within a processing chamber to further add or remove material from the substrate, such as transparent films or the like, as needed.

[0015] Precise thickness measurement is useful in many technically and commercially advantageous disciplines, including the production of flat semiconductor wafers (e.g., optical flats). During the manufacturing processes of optical flats and semiconductor wafers, thickness non-uniformity can occur within a few micrometers. Furthermore, variations in wafer thickness typically span a low spatial frequency across the wafer. In some embodiments, the target of thickness measurement for semiconductor wafers (e.g., transparent semiconductor wafers) is not their absolute thickness, but rather the thickness variation across the wafer, since the absolute thickness can be controlled within a few micrometers. For example, in some manufacturing operations performed on semiconductor wafers (e.g., CMP operations), the intention may be to produce wafers that are as flat and uniform as possible.

[0016] Therefore, it may be advantageous to obtain information about the thickness variation of the surface (which may be related to surface quality, roughness, etc.) before the manufacturing process is completed, so that processing errors and defects can be corrected while the sample is still inside the processing system. In some embodiments, the target surface may have a complex profile, including numerous ridges, grooves, kinks, trenches, flat regions, circular regions, etc. For example, the thickness profile of the wafer surface can be represented by the dependence of the height (width, depth) of the target surface along a reference surface (e.g., a horizontal or vertical plane) in coordinates, counting from this reference surface. This profile can be characterized as a set of discrete (or quasi-continuous) locations, where the resolution is determined by the spacing (e.g., a) between adjacent locations. The spacing can be preset based on the desired resolution of the target surface imaging.

[0017] Existing techniques for performing precise thickness measurement may include the use of capacitive probes, confocal microscopy, interferometry, and the like, each with its own advantages and disadvantages when applied to a particular use case. For example, interferometry (absolute and differential) can provide good sensitivity for both large and small substrates and has been implemented with varying degrees of success.

[0018] However, in many cases, the optical techniques used to perform thickness metrology (also known as wafer shape metrology) typically require individual measurement of two surfaces to obtain two separate plots; comparing these plots allows for the determination of variations in wafer thickness. This method requires careful setup, where proper operation depends on a reference optical flat, which needs to be held precisely relative to the semiconductor wafer in a very stable environment. Therefore, continuously monitoring and plotting thickness variations is both time-consuming and expensive. This independent and highly optimized setup may not be ideal, especially in cases requiring onboard metrology.

[0019] The present disclosure addresses existing and other disadvantages of the prior art. This document describes a method and setup for efficient optical thickness measurement of substrates. This facilitates compact, stable, and affordable data acquisition, providing highly sensitive and high-resolution information on the effectiveness of technical processes such as deposition (e.g., epitaxial silicon carbide (SiC) deposition, which may occur after CMP), etching, CMP, or any other manufacturing process). Furthermore, this solution can be implemented as an airborne metrology system.

[0020] During the manufacturing processes involving optical flats and semiconductor wafers, thickness non-uniformity can occur in the range of several micrometers. Furthermore, variations in wafer thickness typically span a low spatial frequency across the wafer. Therefore, assuming the wafer of interest is transparent to electromagnetic radiation of a specific wavelength (such as light wavelength), any coherent radiation will undergo multiple internal reflections through the wafer. This phenomenon can be used to implement a standard etalon interferometer, which can be applied to plot thickness variations across the wafer surface.

[0021] The disclosed embodiments relate to a variety of manufacturing techniques using processing chambers (which may include deposition chambers, etching chambers, and the like), such as chemical mechanical polishing (CMP), chemical vapor deposition (CVD), physical vapor deposition (PVD), plasma-enhanced CVD, plasma-enhanced PVD, sputtering deposition, atomic layer CVD, combustion CVD, catalytic CVD, vapor deposition, molecular beam epitaxy, etc. Although the most significant practical effects of the disclosed embodiments are likely to occur in techniques using vacuum deposition chambers (e.g., ultra-high vacuum CVD or PVD, low-pressure CVD, etc.), the same systems and methods can be used in atmospheric pressure deposition chambers for non-invasive monitoring of chamber conditions present during the deposition process.

[0022] Figure 1 illustrates an exemplary embodiment of a manufacturing machine 100 capable of supporting efficient thickness variation measurement of substrates processed therein, according to one embodiment. In one embodiment, the manufacturing machine 100 includes a loading station 102, a transfer chamber 104, and one or more processing chambers 106. The processing chambers 106 may be connected to the transfer chamber 104 via a transfer port (not shown) interface. The number of processing chambers associated with the transfer chamber 104 may vary (for example, three processing chambers are indicated in Figure 1). The transfer chamber 104 may include a robot 108, robot blades 110 for supporting a substrate (e.g., a wafer or a transparent wafer), a plurality of light sources 112 for scanning a substrate 116 (e.g., a target), and an optical sensor 114 located in one of the processing chambers 106. The light sources 112 and the optical sensor 114 may be part of a thickness mapping apparatus 111. The transfer chamber 104 can be maintained at a pressure (temperature) above (or below) atmospheric pressure (temperature).

[0023] Robot 108 can transfer various products and components (e.g., semiconductor wafers, substrates, liquid crystal displays, main photomasks, calibration components) between loading station 102 and processing chamber 106.

[0024] In one embodiment, when the substrate 116 is transferred into one of the processing chambers 106, robot blades 110 of robot 108 support the substrate 116. Robot blades 110 may be attached to an extendable arm sufficient to reach between different chambers. Several light sources 112 may scan the substrate 116 with one or more beams to obtain intensity values ​​caused by reflections from one or more beams from the substrate 116. The substrate 116 may be a wafer, substrate chuck, edge ring, or any other object / tool ​​located in one of the processing chambers 106 (or in the loading station 102, transfer chamber 104, or a port connecting the transfer chamber 104 to the loading station 102 or processing chamber 106). The reflected beams may be received by one or more optical sensors 114. Thickness drawing equipment 111 may include alignment points for proper alignment relative to the substrate 116. The alignment point can be a hole, notch, or dent, and can be centered in a recess or depression of the robot blade 110. The optical sensor 114 of the thickness mapping apparatus 111 may be able to sense visible light or other electromagnetic radiation from the target surface (e.g., reflected from that surface) of the substrate 116. The light detected by the optical sensor 114 can be reflected from the target surface, and the light can be directed by one or more light sources 112. In some embodiments, the light sources 112 may be mounted on the same thickness mapping apparatus 111. In other embodiments, the light sources 112 may be located outside the thickness mapping apparatus 111, for example, mounted inside the transfer chamber 104, loading station 102, or processing chamber 106. The robot blade 110 can transport the substrate to (and retrieve the substrate from) the processing chamber(s) 106 via a slit valve port (not shown), while the covers of the processing chamber(s) 106 remain closed. (Several) processing chambers 106 may contain processing gases, plasma, and various particles used in the deposition process. A magnetic field may be present inside (several) processing chambers 106. The interior of (several) processing chambers 106 may be maintained at temperatures and pressures different from those outside (several) processing chambers 106. The temperatures and pressures inside (several) processing chambers 106 may be similar to those corresponding to actual in-line processing conditions. Although substrate 116 is shown as being supported and moved by the robot blades 110 of robot 108, in other embodiments, a dedicated motion stage or any other suitable movable stage, existing substrate transfer mechanism, or existing motion mechanisms in the process chamber (such as a polishing head or another wafer deployed in a CMP process) may be used to move substrate 116.

[0025] The computing device 118 may include an optical sensor control module 122 and a thickness analysis module 124. The optical sensor control module 122 can control the operation of the optical sensor 114 and (in some cases) (a number of) light sources 112. The thickness analysis module 124 can receive the intensity value measured by the optical sensor 114 and determine the thickness variation plot of the substrate 116.

[0026] In one exemplary embodiment, the electronic module 150 may be able to facilitate wireless thickness variation mapping of a target within the manufacturing machine 100 to determine profile data corresponding to thickness variations of the substrate. The electronic module 150 may include a microcontroller and a memory buffer coupled to the microcontroller. The memory buffer may be used to collect and store data before data is transferred to the computing device 118. In some embodiments, wireless communication circuitry may be used to transfer data. In other embodiments, a wired connection may be used to transfer data between the electronic module 150 and the computing device 118. In some embodiments, data may first be stored (buffered) in the memory buffer before being transferred to the computing device 118. In other embodiments, data may be transferred to the computing device 118 while data is being collected, without being stored in the memory buffer. In some embodiments, the wireless or wired connection may be continuous. In other embodiments, the wireless or wired connection may be established periodically or after a check is completed or some other triggering event (e.g., when the memory buffer is nearly full). The electronic module 150 may further include power supply elements and power-on circuitry. In some embodiments, the power supply element may be a battery. In some embodiments, the power supply element may be a capacitor. The power supply element may be recharged from a power station. The microcontroller may be coupled to one or more optical sensors 114. The optical sensors 114 may include a light source and a light detector. The electronic module 150 may also include an accelerometer to facilitate the accurate extension and angular rotation of the robot blade 110. The electronic module 150 may also include a temperature sensor to detect the temperature near the substrate 116.

[0027] The electronic module 150 may further include wireless communication circuitry, i.e., a radio circuitry system, for receiving wireless commands from the computing device 118 and for transmitting strength values ​​to the computing device 118. For example, in one embodiment, the radio circuitry system may include an RF front-end module and an antenna (e.g., a UHF antenna), which may be an internal ceramic antenna. The battery may be of a high-temperature resistant type, such as a lithium-ion battery, which can be exposed to a chamber temperature of 450 degrees Celsius for a short period, such as one to eight minutes.

[0028] Some components may be located on or thereon on the stationary portion of robot 108. For example, microcontrollers, memory buffers, and RF front-ends may be positioned thereon. Other components of electronic module 150 may be located on or thereon on robot blades 110 of robot 108 and / or on a thickness rendering device supported by the robot blades. The robot blades are movable to support a substrate that can be transported by means of the robot blades. For example, optical sensors 114, accelerometers, and temperature sensors may be positioned thereon. In some embodiments, some components of electronic module 150 may be located on the stationary portion of robot 108 and on the extendable robot blades 110, for example, power supply elements may be positioned thereon. In some embodiments, two separate microcontrollers may be implemented, one located on the stationary portion of robot 108 and the other located on the thickness rendering device 111.

[0029] In some embodiments, a wireless connection manufactured by an RF front-end and antenna can support a communication link between the microcontroller and the computing device 118. In some embodiments, the microcontroller integrated with the robot 108 may have minimal computing capabilities sufficient to transmit information to the computing device 118, where most information processing occurs. In other embodiments, the microcontroller may perform most of the computation, while the computing device 118 may provide computational support for specific processing-intensive tasks. The data received by the computing device 118 may be data obtained from the transfer chamber 104, the processing chamber 106, data collected by the optical sensor 114, data temporarily or permanently stored in a memory buffer, etc. Data stored in the memory buffer and / or transmitted to or from the computing device 118 may be in a raw or processed format.

[0030] In one embodiment, the thickness mapping apparatus may determine and output (using the processing power of the microcontroller and / or computing device 118) profile data characterizing the thickness variation of the substrate based on the intensity values ​​associated with one or more received light beams. Since the substrate is scanned with one or more incident light beams, one or more received light beams may be caused by interaction or by one or more incident light beams on the substrate. The intensity values ​​may originate from one or more locations on the substrate.

[0031] For example, the thickness mapping apparatus 111 may scan the substrate using a first beam from (a plurality of) light sources 112. The thickness mapping apparatus 111 may obtain intensity values ​​associated with a second beam corresponding to one or more locations on the substrate. The second beam may be caused by the interaction between the first beam and the substrate. The interaction may include the substrate reflecting or transmitting the first (incident) beam. Thus, the second beam may be a reflected beam or a transmitted beam. The thickness mapping apparatus 111 may use the obtained intensity values ​​to determine profile data characterizing the thickness variation of the substrate. In some cases, during substrate processing stages (such as deposition, etching, polishing, etc.), a slurry (which may include water droplets and / or other materials used in the processing) may form, which is detrimental to the accuracy of optical measurements and thickness mapping. To remove residual water, in some embodiments, a directional gas source (e.g., a gas jet) such as nitrogen, argon, xenon, air, and the like may be applied to dry the substrate before scanning with the beam to minimize the optical effects of these foreign materials and ensure the accuracy of the determined profile data.

[0032] A plurality of intensity values ​​can be determined for the substrate. In some embodiments where thickness mapping is performed using reflected light, the intensity values ​​may represent the reflectivity of the substrate at various locations. In some embodiments where thickness mapping is performed using transmitted light, the intensity values ​​may represent the transmittance of the substrate at various locations. Because light reflected from the top surface and light reflected from the bottom surface of the substrate may interfere, the reflectivity and / or transmittance may exhibit a series of bright (maximum) and dark (minimum) interference fringes. As described in more detail below, these interference fringes can be used as a reference for determining the thickness (and / or thickness variation) of the substrate. Specifically, the intensity values ​​may include at least a first intensity value from a first location of one or more locations and a second intensity value from a second location of one or more locations. The first intensity value and the second intensity value can be used to identify the thickness variation of the substrate between the first location and the second location.

[0033] Because reflectivity (and / or transmittance) can be a periodic function of substrate thickness, there may be some uncertainty regarding whether the thickness increases or decreases between the first and second positions in some cases. For example, for a given wavelength and angle of incidence, the intensity of the reflected (or transmitted) beam can include numerous interference maxima and minima with respect to the varying thickness of the substrate. Therefore, when a first intensity value (e.g., ) determined at the first position is close to the maximum (or minimum) value of the function, a lower (or higher) second intensity value (e.g., ) may not be able to definitively determine whether the substrate thickness increases or decreases between the first and second positions. In these cases, the thickness mapping device 111 can scan the substrate using an additional beam (e.g., a third beam) from the same or other (a plurality of) light sources 112. The third beam may differ from the first beam in at least one of wavelength (e.g., ) or angle of incidence on the substrate (e.g., ). For example, in one embodiment, there may be two (or more) light sources 112, each producing a beam of a different wavelength. In another embodiment, a single light source 112 may be present, which generates a beam that is split (e.g., by a beam splitter), and each of the split beams may be incident on the substrate at a different angle. In some embodiments, the beams incident on the substrate may have different wavelengths and different incident angles. In either case, the thickness mapping device 111 may obtain a second set of intensity values ​​associated with at least some of one or more locations on the substrate. The fourth beam may be caused by the interaction of the third beam with the substrate and may (similar to the second beam) be a reflected or transmitted beam. To address possible uncertainties regarding whether the thickness increases or decreases, the thickness mapping device may determine and output an overview based on both the first set of intensity values ​​and the second set of intensity values ​​(e.g., and).

[0034] Figure 2A illustrates, according to one embodiment, a small-spot scanning interferometry system 200 with a single light source 204 for plotting thickness variations of a substrate 202. The interferometry system 200 may include a light source 204, a detector 206, and a beam splitter 208. In some embodiments, the thickness variation plotting setup may include an optical head 212 that combines one or more of the light source 204, detector 206, and beam splitter 208. The substrate may be supported by a lifting pin 210. The pin 210 may be used for edge handling of the substrate 202. In some embodiments, the substrate may be a silicon carbide (SiC) wafer.

[0035] The substrate 202 may be irradiated by an incident beam 214 (or other forms of electromagnetic radiation), and a reflected beam 216 may be generated after the interaction between the incident beam 214 and the substrate. In some embodiments, the incident beam 214 may be a collimated beam, a focused beam, a coherent beam, a polarized beam, a pulsed beam, or some other beam. The intensity of the reflected beam 216 may show (e.g., as a function of the substrate thickness) the number of bright and dark fringes caused by the constructive and destructive interference of multiple internal reflections of the beam within the substrate 202. As the incident beam 214 moves relative to the substrate 202 (or the substrate 202 is transported relative to the incident beam 214), even a small change in the substrate thickness may result in a series of alternating fringes—peaks and troughs / valleys—in the intensity of the reflected (or transmitted) beam.

[0036] The spatial frequency of alternating peaks / troughs (e.g., the reverse lateral distance between adjacent stripes) can be determined by the thickness variation of substrate 202 (e.g., the tangent of the angle between the surface and the horizontal direction), the wavelength of the incident beam, and the incident angle of the beam on the substrate. Therefore, by scanning substrate 202 with a beam having a known frequency and a known incident angle, a thickness profile of the substrate can be mapped. For example, substrate 202 can be scanned in various ways. In one embodiment, substrate 202 can be rotated and radially translated such that the entire surface of substrate 202 is scanned in a helical trajectory. In other embodiments, substrate 202 can be fixed while optical head 212 rotates in a helical pattern to scan the entire surface of substrate 202. In other embodiments, raster scanning of substrate 202 can be performed by moving substrate 202 or one or more of optical head 212 in a rectangular pattern.

[0037] As shown in Figure 2A, the optical head 212 may include a light source 204 that emits a light beam with wavelength λ. This light beam may be split into a first beam and a second beam, each having wavelength λ. The first beam may be incident on the substrate 202 at a first incident angle and may interact with the substrate 202. A first detector 206a may detect a first set of intensity values ​​associated with a third beam caused by the interaction of the first beam with the substrate 202. Depending on a selected scanning pattern (e.g., spiral, rectangular, etc.), each intensity value may be associated with a set of positions on the substrate 202. Similarly, the second beam may be incident on the substrate 202 at a second incident angle and may interact with the substrate 202. A second detector 206b may detect a second set of intensity values ​​associated with a fourth beam caused by the interaction of the third beam with the substrate 202. Depending on a selected scanning pattern, each intensity value may be associated with one of the sets of positions on the substrate 202. The first set of strength values ​​and / or the second set of strength values ​​can then be used to determine the thickness profile of the substrate 202.

[0038] In some embodiments where light reflected from substrate 202 is detected, absorber 218 may be positioned opposite (e.g., below) substrate 202 to prevent (or minimize) light transmitted through the substrate from reflecting back onto the substrate and affecting the substrate reflectivity data obtained by detectors 206a and 206b. Absorber 218 may include a specialized anti-reflective material to prevent light from interacting with the underlying substrate support. Alternatively, the back side of the substrate may include a specialized anti-reflective material to prevent light from interacting with the underlying substrate support.

[0039] Figure 2B illustrates, according to one embodiment, a small-spot scanning interferometry system 200 having two light sources 204a and 204b for plotting thickness variations of a substrate 202. The small-spot scanning interferometry system 200 of Figure 2B may be similar to the small-spot scanning interferometry system 200 of Figure 2A, but may have an optical head including multiple (two or more) light sources.

[0040] As shown in Figure 2B, the optical head 212 may include a first light source 204a and a second light source 204b, which can emit light beams having a first wavelength and a second wavelength. The first light beam may be incident on the substrate 202 at a given incident angle (e.g., orthogonal or other small angle) and may interact with the substrate 202. A first detector 206a may detect a first set of intensity values ​​associated with a third light beam caused by the interaction of the first light beam with the substrate 202. According to the scanning pattern, each intensity value may be associated with one of a set of locations on the substrate 202. Similarly, a second light beam may be incident on the substrate 202 at a given incident angle and may interact with the substrate 202. A second detector 206b may detect a second set of intensity values ​​associated with a fourth light beam caused by the interaction of the second light beam with the substrate 202. According to the scan, each intensity value may be associated with that set of locations on the substrate 202. The first set of intensity values ​​and the second set of intensity values ​​may be used to determine the thickness profile of the substrate 202.

[0041] Figure 2C illustrates, according to one embodiment, a small-spot scanning interferometry system 201 having a single light source 204 and a movable mirror for plotting thickness variations of a substrate 202. This small-spot scanning interferometry system 201 may be similar to the small-spot scanning interferometry system 200 in Figures 2A to 2B, and is represented by similar component symbols. As shown in Figure 2C, a beam from the light source 204 can be guided toward a beam splitter 208. The beam splitter 208 splits the beam into a first incident beam 214a and a second incident beam 214b. The first incident beam 214a can be incident on the substrate 202 (e.g., a sample) at a first incident angle. The second incident beam 214a on the sample can be guided toward the sample by a mirror 220. The mirror 220 can be tilted at an angle to set a second incident angle of the second incident beam 214b on the sample. In some embodiments, mirror 220 may be mounted on a tilting stage, and thus the change in slope may alter the angle of incidence of the second beam 214a. Referring to equation (2) (described below), the internal reflection angle β is related to the angle of incidence α on the sample via Schnell's law:

[0042] Therefore, a small change in α will result in a change in the inner reflection angle. This, in turn, will cause a shift in the fringe position, according to equation (1) (described below). Thus, the position of the fringe can be adjusted or changed by making a small change to the incident angle. This small change to the incident angle will only produce a negligible change in the position of the beam on the substrate 202. This allows for the ability to resolve uncertainties in thickness variations. For example, if a thickness variation of the substrate 202 causes the signal in the plateau region of the thickness (i.e., the position where the signal does not change with the position on the sample) to be at its maximum or minimum with respect to the two incident angles, then by slightly shifting the incident angle of the beam, the simultaneous maximum or minimum value of the two signals is broken, thereby resolving the uncertainty condition. As an example, a small change in the incident angle can be easily achieved by using a piezoelectrically mounted mirror.

[0043] In some embodiments, the small-spot scanning interferometry systems 200 and 201 can be combined with a mass metrology system to perform cross-checking of deposition and etching processes. For example, the mass metrology system can provide information on the total mass change of the substrate caused by the processing operation (but does not provide any spatial information), while the thickness change profile can indicate areas of non-uniform thickness caused by the processing operation. Determining the thickness change profile in this way can be used as a feedforward or feedback mechanism for additive or subtractive processes.

[0044] Figure 3 schematically depicts, according to one embodiment, the intensity values ​​and interference fringes for scanning over a substrate region with varying thickness using two light beams. Assuming the substrate is irradiated from above by coherent, collimated radiation, the reflected response may appear as numerous parallel fringes.

[0045] For example, the intensity of the stripe can be given by the following (1) where (2) and where β is the inward reflection angle with respect to the surface normal, h(x,y) is the local thickness, λ is the wavelength of light in vacuum, I0 is the intensity of light incident on the substrate, n is the refractive index of the material, and r2 is the surface reflectivity.

[0046] For a given light beam, the spatial frequency of the interference fringes can be determined by the slope of the thickness variation, the angle of incidence, and the wavelength. For example, dark fringes in the reflectivity may be encountered at a point on the substrate. Therefore, different dark fringes in the reflectivity may correspond to positions where the substrate thickness differs by an integer. Correspondingly, the maximum reflectivity will be encountered at a position where the substrate thickness differs from the position where the dark fringes (minimum) of the reflectivity are located. Therefore, the substrate can be scanned by a first (incident) light beam, and a second (reflected or transmitted) light beam corresponding to the interaction between the first light beam and the substrate can be detected. A first set of intensity values ​​associated with the second light beam and corresponding to each position on the substrate can be obtained (e.g., using detector 206). The first set of intensity values ​​can be used to determine general information characterizing the thickness variation of the substrate.

[0047] Specifically, the intensity value may include a first intensity value at a first location and a second intensity value at a second location. The first intensity value and the second intensity value can be used to determine the variation of the substrate thickness between the first location and the second location. However, as mentioned above, in some cases, especially when the reflection (or transmission) at the platform is close to its maximum or minimum value, there may be some uncertainty about whether the thickness increases or decreases after the platform.

[0048] The platform can be identified based on the equality of a subset of the first set of intensity values. It should be understood that if the difference is within the target accuracy, the two substrates can still be considered to have equal thickness. The target accuracy can represent the desired precision of the manufacturing process. In some embodiments, the target accuracy can represent the resolution of the optical inspection system. For example, if the resolution of the optical inspection system is [value missing], then the locations can be considered to have equal thickness.

[0049] In some cases, a plateau of equal (in the sense described above) thickness may approximate a specific thickness where reflectivity or transmittance has a maximum or minimum value. As the thickness changes, reflectivity or transmittance may decrease or increase, regardless of whether the substrate thickness increases or decreases. To address this uncertainty, an additional scan can be performed using an additional beam with a different incident angle and / or a different wavelength. Generally, even if the reflectivity or transmittance of the first beam is at a peak or trough on the plateau, the additional beam will not approach its maximum or minimum value (assuming the additional beam has a different incident angle and / or wavelength). The additional beam can therefore serve as a disambiguation reference for comparing the reflectivity / transmittance of the first beam.

[0050] More specifically, the substrate can be scanned by an additional beam (e.g., a third beam). The third beam may differ from the first beam in at least one of wavelength or angle of incidence on the substrate. A fourth beam corresponding to the interaction between the third beam and the substrate can be detected. A second set of intensity values ​​corresponding to various locations on the substrate, associated with the fourth beam, can be obtained. The second set of intensity values ​​can be used to further determine profile data characterizing the thickness variation of the substrate. Because the first and third beams have different wavelengths and / or angles of incidence (resulting in different internal reflection angles), the resulting intensity fringes attributed to the first and third beams are different. This provides the ability to remove uncertainty about whether the thickness increases or decreases after scanning the platform.

[0051] For example, when scanning is performed in a direction of increasing thickness, the maximum or minimum intensity of the second beam (e.g., reflected light) is encountered at a (spatial) frequency different from the maximum and minimum intensity of the fourth beam (e.g., reflected light). As shown in Figure 3, in the first region 303 with a positive slope, the interference fringe 301 (solid line) generated by the first beam scan is shifted to the left relative to the interference fringe 302 (dashed line) generated by the third beam scan. In the second region 305, the slope is zero (plateau region) and the intensity of the two beams remains uniform. In the third region 307, the slope is negative and the relative spatial order between the interference fringes 301 and 302 is reversed (where the interference fringe 301 is shifted to the right). For example, due to the reversed relative order of the fringes when scanning with the first and third beams, interference fringes 313 and 315 indicate opposite slopes. In the fifth region 311, after passing another platform in the fourth region 309, the slope is again positive, and compared to the third region 307, the relative spatial order of interference fringes 301 and 302 is reversed. As depicted, interference fringes 317 and 319 indicate opposite slopes due to the reversed relative order of the fringes when scanned with the first and third beams. Similarly, interference fringes 313 and 319 have the same relative order, indicating that the slopes in the first region 303 and the fifth region 311 are the same (e.g., positive).

[0052] Figure 4 illustrates, according to one embodiment, the integration of a machine learning method for manufacturing process control with optical inspection metrology. Figure 4 depicts a substrate 202 processed by a process tool 410, which may be a CMP (or some other polishing equipment). A metrology device (e.g., an optical head 212 (or some other metrology device)) can monitor the real-time state of the substrate 202. For example, the optical head 212 can determine the thickness and profile of the substrate 202 while the process tool 410 alters the state of the substrate, for example, by removing material from the substrate 202. The profile data 420 output by the optical head 212 can be processed by one or more machine learning models 430 (MLMs). The MLM 430 may be or include decision tree algorithms, support vector machines, deep neural networks, or any combination thereof. Deep neural networks may include convolutional neural networks, recurrent neural networks (RNNs) with one or more hidden layers, fully connected neural networks, long short-term memory neural networks, Boltzmann machines, etc. The MLM 430 can be trained to implement specific technical processes, including a specific substrate profile to be created within a specific timeframe, specific surface qualities to be achieved on the substrate, etc. The MLM 430 may use profile data 430, technical process specifications (not shown), current timestamps (e.g., counted from the start of the technical process), and other appropriate data as input. The MLM 430 may output (e.g., in real-time) tool settings 440 for the process tool 410. Time settings may include the pressure applied by the process tool 410 to the substrate 202, the rate at which material is removed from the substrate 202, the rotational speed of the process tool 410, or any other applicable tool settings 440. As processing continues via the process tool 410, the tool settings 440 may change accordingly. For example, when approaching the target profile, the MLM 430 can output tool settings 440 to slow down the material removal rate and relieve pressure on the substrate.

[0053] In some embodiments, the measuring device (e.g., optical head 212) continuously monitors the state of the substrate 202 (e.g., by moving over the substrate 202 in a predetermined pattern). In some embodiments, the measuring device may periodically monitor the state of the substrate 202 at specific times and similar conditions.

[0054] The MLM 430 can be trained using the MLM training engine 450. The training engine 450 may be located on the same manufacturing machine as the process tool 410 and metrology equipment, or on an external server communicatively coupled to the manufacturing machine. In some implementations, the MLM training engine 450 may be located on a server that does not interact with the manufacturing machine, wherein the trained MLM is installed on the manufacturing machine after training is performed. The MLM training engine 450 may use training data 460, which may include information related to similar types of substrates and processed in similar (or identical) technical flows. For example, training data 460 may include dynamic profile data and tool settings implemented during previous processing of similar wafers. Training data 460 may further include annotations indicating correct and incorrect processing. In some implementations, the MLM training engine 450 may train the MLM 430 in real time on the same manufacturing machine where the process tool 410 is located, for example, using self-guided training iterations on a single batch (or multiple batches) of substrates.

[0055] Figure 5 is a flowchart of a method 500 for drawing substrate thickness according to one embodiment. Method 500 can be performed using the systems and components shown in Figures 1 and 2A to 2B, or a combination thereof. Method 500 can be performed using a single photosensor or multiple photosensors. The photosensors can be configured to scan the substrate as depicted in Figures 2A to 2B. In some embodiments, some or all blocks of method 500 can be performed in response to instructions from computing device 118 or microcontroller 152. Microcontroller 152 may include one or more processing devices, such as a central processing unit (CPU), application-specific integrated circuit (ASIC), field programmable gate array (FPGA), digital signal processor (DSP), network processor, or the like. (Several) processing devices are communicatively coupled to one or more memory elements, such as read-only memory (ROM), flash memory, static memory, dynamic random access memory (DRAM), and the like. Microcontroller 152 may be part of a desktop computer, laptop computer, workstation, wearable device (e.g., tablet computer, smartphone, etc.), cloud-based computing service, and the like. In some embodiments, microcontroller 152 is part of a larger network of computing devices. In some embodiments, an external computing device communicating with microcontroller 152 can reconfigure (e.g., change settings, update memory, or otherwise reprogram) microcontroller 152. In some embodiments, thickness drawing method 500 may be performed while the wafer is inside the processing chamber. In some embodiments, method 500 may be performed once the wafer has been removed from the processing chamber. The thickness drawing method may be performed under conditions similar to the actual conditions of the processing chamber during the manufacturing process (e.g., pressure and temperature). Therefore, the manufacturing process can occur at low temperatures or at temperatures below or significantly below room temperature. Alternatively, the manufacturing process can occur at room temperature, above room temperature, or significantly above room temperature. In some embodiments, the pressure inside the chamber can be less than or significantly less than atmospheric pressure, including low-vacuum or high-vacuum conditions.

[0056] Method 500 may include scanning a substrate (block 502) with a first beam. The first beam may be emitted from a laser, a narrowband light source, a broadband light source with subsequently narrowed spectral distribution, a light-emitting diode with narrowed spectral distribution, etc. The first beam may have a first wavelength and be incident on the substrate at a first angle. Scanning the substrate may include moving the first beam relative to the substrate. In some embodiments, the light source (and detector) is stationary (e.g., relative to the substrate processing system), but the substrate is moving. For example, the substrate may be transported below the light source (and detector) while the scanning is performed. In some embodiments, the first beam moves in a spiral pattern relative to the substrate. In some embodiments, the first beam moves in a rectangular pattern, a zigzag pattern, or any other geometric pattern relative to the substrate.

[0057] Method 500 may further obtain a corresponding one of a first set of intensity values ​​associated with the second beam for each of a set of locations on the substrate (block 504). The second beam may be caused by the interaction between the first beam and the substrate. The first set of intensity values ​​associated with the second beam may include at least a first intensity value for a first location in the set of locations and a second intensity value for a second location in the set of locations. In one embodiment, the second beam is a reflected beam caused by the interaction between the first beam and the substrate, and each of the first set of intensity values ​​is associated with the reflectivity of the substrate at the corresponding location in the set of locations on the substrate. In another embodiment, the second beam is a transmitted beam caused by the interaction between the first beam and the substrate, and each of the first set of intensity values ​​is associated with the transmittance of the substrate at the corresponding location in the set of locations on the substrate.

[0058] Method 500 may further determine profile data characterizing the change in substrate thickness (block 506). The determination of profile data may be based on using a first set of intensity values ​​and may correspond to using the first intensity value and a second intensity value to determine the thickness change of the substrate between the first position and the second position; Method 500 ends.

[0059] In other embodiments, method 500 may further include scanning the substrate with a third beam. The third beam may differ from the first beam in at least one of wavelength or angle of incidence of the beam on the substrate. In other embodiments, method 500 may further include obtaining a corresponding one of a second plurality of intensity values ​​associated with a fourth beam for at least some of the locations on the substrate. The fourth beam may be caused by the interaction between the third beam and the substrate, and the determination profile may be further based on a second set of intensity values.

[0060] The second set of intensity values ​​associated with the fourth beam can identify a third set of interference fringes for a first region of the substrate and a fourth set of interference fringes for a second region of the substrate. In some embodiments, determining the profile data further includes identifying that the relative spatial order of the first and third sets of interference fringes is different from the relative spatial order of the second and fourth sets of interference fringes. Using the identified relative spatial order of the interference fringes, it may be determined whether the substrate thickness increases or decreases in the scanning direction (e.g., in the first region) or vice versa.

[0061] The scanning substrate may include moving at least one of the first beam or the third beam in a spiral pattern relative to the substrate. In other embodiments, the scanning substrate may include moving the substrate in a spiral pattern relative to at least one of the first beam or the third beam. In some embodiments, the scanning substrate may include scanning in a pattern other than a spiral, for example, in a raster scanning pattern.

[0062] In some embodiments, if a subset of the first set of intensity values ​​is determined to be substantially equal (e.g., equal within the target accuracy value), then the thickness of the substrate region can be determined to be uniform.

[0063] In some embodiments, for example, residual water from CMP may remain on the substrate. To improve the accuracy of thickness mapping, a portion of the substrate may be dried (or cleaned) by an airflow (such as nitrogen, argon, xenon, air, or the like) before scanning.

[0064] In some embodiments, given the determined thickness profile data, the thickness of the substrate can be modified (increased (e.g., by performing additional deposition using a deposition apparatus) or decreased (e.g., by etching using an etching apparatus or polishing using a polishing apparatus) or otherwise adjusted). In some embodiments, the substrate is a SiC wafer, which can be adjusted by changing the equipment control parameters. The control parameters can determine the rate or amount of material added to (or removed from) the substrate.

[0065] The systems and methods disclosed herein can be used not only for monitoring thickness variations during manufacturing, but also for testing and developing various deposition and polishing processes. Advantages of the disclosed embodiments include, but are not limited to, the ability to inspect process quality and substrate surface uniformity.

[0066] Figure 6 depicts a block diagram of an example processing device 600 operating according to one or more of the modes of this disclosure. The processing device 600 may be the computing device 118 of Figure 1.

[0067] Instance processing device 600 can be connected to other processing devices via a local area network (LAN), intranet, extranet, and / or internet. Processing device 600 can be a personal computer (PC), set-top box (STB), server, network router, switch, or bridge, or any device capable of executing a set of instructions (sequentially or otherwise) specifying actions to be taken by that device. Furthermore, although only a single instance processing device is illustrated, the term "processing device" should also be considered to include any collection of processing devices (e.g., computers) that individually or collectively execute a set (or more) of instructions to perform any one or more of the methods disclosed herein.

[0068] The instance processing device 600 may include a processor 602 (e.g., CPU), main memory 604 (e.g., read-only memory (ROM), flash memory, dynamic random access memory (DRAM) (such as synchronous DRAM (SDRAM)), static memory 606 (e.g., flash memory, static random access memory (SRAM), etc.), and secondary memory (e.g., data storage device 618), which can communicate with each other via bus 630.

[0069] Processor 602 represents one or more general-purpose processing devices, such as microprocessors, central processing units, or the like. More specifically, processor 602 may be a complex instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a processor implementing other instruction sets, or a processor implementing a combination of instruction sets. Processor 602 may also be one or more special-purpose processing devices, such as application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), digital signal processors (DSPs), network processors, or the like. According to one or more embodiments of this disclosure, processor 602 may be configured to execute instructions for implementing the thickness variation drawing method 500.

[0070] The instance processing device 600 may further include a network interface device 608, which can be communicatively coupled to the network 620. The instance processing device 600 may further include a video display 610 (e.g., a liquid crystal display (LCD), a touch screen, or a cathode ray tube (CRT)), a digit input device 612 (e.g., a keyboard), an input control device 614 (e.g., a cursor control device, a touch screen control device, a mouse), and a signal generation device 616 (e.g., a speaker).

[0071] The data storage device 618 may include a computer-readable storage medium (or more specifically, a non-transitory computer-readable storage medium) 628 having stored one or more sets of executable instructions 622 thereon. According to one or more embodiments of this disclosure, the executable instructions 622 may include executable instructions for implementing the thickness variation drawing method 500.

[0072] The executable instructions 622 may also reside wholly or at least partially in main memory 604 and / or processor 6020 during execution by instance processing device 600, the main memory 604 and processor 6020 also constituting computer-readable storage media. The executable instructions 622 may further be transmitted or received over a network via network interface device 608.

[0073] Although computer-readable storage medium 628 is shown as a single medium in Figure 6, the term "computer-readable storage medium" should be considered as a single medium or multiple media (e.g., a centralized or distributed database, and / or associated cache and server) that includes one or more sets of storage operation instructions. The term "computer-readable storage medium" should also be considered as any medium capable of storing or encoding a set of instructions for execution by a machine, such instructions causing the machine to perform any one or more of the methods described herein. The term "computer-readable storage medium" should accordingly be considered as including, but not limited to, solid-state memory, and optical and magnetic media.

[0074] It should be understood that the above description is intended to be illustrative and not restrictive. Many other embodiments will become apparent to those skilled in the art after reading and understanding the above description. Although this disclosure describes specific examples, it should be recognized that the system and method of this disclosure are not limited to the examples described herein, but can be practiced with modifications within the scope of the appended claims. Therefore, the specification and drawings should be considered in an illustrative rather than restrictive sense. Thus, the scope of this disclosure should be determined with reference to the entire scope of the appended claims together with the equivalents conferred by the claims of this application.

[0075] Embodiments of the above-described methods, hardware, software, firmware, or code may be implemented via instructions or code stored on a machine-accessible, machine-readable, computer-accessible, or computer-readable medium executable by a processing element. "Memory" includes any mechanism that provides (i.e., stores and / or transmits) information in a machine-readable form (such as a computer or electronic system). For example, "memory" includes random-access memory (RAM), such as static RAM (SRAM) or dynamic RAM (DRAM); ROM; magnetic or optical storage media; flash memory elements; electrical storage elements; optical storage elements; acoustic storage elements; and any type of tangible machine-readable medium suitable for storing or transmitting electronic instructions or information in a form readable by a machine (e.g., a computer).

[0076] Throughout this specification, the reference to "an embodiment" or "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of this disclosure. Therefore, the phrases "in an embodiment" or "in an embodiment" appearing throughout this specification do not necessarily represent the same embodiment. In addition, particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0077] In the foregoing specification, a detailed description has been given with reference to specific exemplary embodiments. However, it will be apparent that various modifications and changes can be made thereto without departing from the broader spirit and scope of this disclosure as set forth in the appended claims. Therefore, the specification and drawings should be considered in an illustrative sense rather than a restrictive sense. Furthermore, the foregoing use of the terms "exemplary," "conceptual," and / or other illustrative language does not necessarily represent the same embodiment or the same instance, but may represent different and dissimilar embodiments, as well as possibly the same embodiment.

[0078] The terms “example” or “illustrative” are used herein to mean serving as an example, instance, or illustration. Any form or design described herein as “example” or “illustrative” is not necessarily to be construed as preferred or superior to other forms or designs. Rather, the use of the terms “example” or “illustrative” is intended to present the concept in a concrete manner. As used in this specification, the term “or” is intended to mean an inclusive “or” rather than an exclusive “or.” That is, unless otherwise stated or clearly stated from the context, “X includes A or B” is intended to mean either of the naturally inclusive arrangements. That is, if X includes A; X includes B; or X includes A and B, then “X includes A or B” is satisfied in any of the foregoing cases. In addition, as used in the claims of this application and the appendix claims, the articles “a” and “an” should be generally interpreted as meaning “one or more” unless otherwise stated or clearly stated from the context to be singular. Furthermore, unless otherwise described, the terms "an embodiment" or "one embodiment" are always used and are not intended to refer to the same embodiment or embodiment. Also, as used herein, the terms "first," "second," "third," "fourth," etc., are labels used to distinguish different elements and may not necessarily have ordinal meanings according to their numerical designations. [Simplified Explanation of the Diagram]

[0006] Figure 1 illustrates an exemplary embodiment of a manufacturing machine capable of supporting efficient thickness variation measurement of substrates processed therein, according to one embodiment.

[0007] Figure 2A illustrates, according to one embodiment, a small-spot scanning interferometry system with a single light source for plotting thickness variations of a substrate.

[0008] Figure 2B illustrates a small-spot scanning interferometry system with two light sources for plotting the thickness variation of a substrate, according to one embodiment.

[0009] Figure 2C illustrates, according to one embodiment, a small-spot scanning interferometry system with a single light source and a movable mirror for plotting thickness variations of a substrate.

[0010] Figure 3 schematically depicts interference fringes for scanning over a substrate region with varying thickness using two light beams, according to one embodiment.

[0011] Figure 4 illustrates, according to one embodiment, the integration of machine learning methods for manufacturing process control with optical inspection metrology.

[0012] Figure 5 is a flowchart of a method for drawing the thickness of a substrate according to one embodiment.

[0013] Figure 6 is a block diagram of an instance processing device operating in one or more modes according to this disclosure. [Biomaterial Storage]

[0080] Domestic storage information (please note in order of storage institution, date, and number): None. International storage information (please note in order of storage country, institution, date, and number): None.

Claims

1. A method for plotting thickness variations of a substrate, comprising the steps of: scanning a substrate with a first light beam; obtaining, for each of a plurality of locations on the substrate, a corresponding of a first plurality of intensity values ​​associated with a second light beam, wherein the second light beam is caused by the interaction between the first light beam and the substrate, and wherein the first plurality of intensity values ​​characterize one or more spatial interference fringes caused by interference between the second light beam originating from a first portion of a first surface of the substrate and the second light beam originating from a second portion of a second surface of the substrate; scanning the substrate with a third light beam, wherein the third light beam differs from the first light beam in at least one of a wavelength or an angle of incidence on the substrate; For each of the plurality of locations on the substrate, a corresponding one of a second plurality of intensity values ​​associated with a fourth beam is obtained, wherein the fourth beam is caused by the interaction between the third beam and the substrate, and wherein the second plurality of intensity values ​​characterize one or more additional spatial interference fringes caused by the interference of the third beam originating from a third portion of a first surface of the substrate and the fourth beam originating from a fourth portion of a second surface of the substrate; and the first plurality of intensity values ​​and the second plurality of intensity values ​​are used to determine a profile characterizing a variation in the thickness of the substrate.

2. The method as described in claim 1, wherein the step of determining the first plurality of intensity values ​​associated with the second beam includes the following steps: determining a first intensity value for one of the plurality of positions at a first position and a second intensity value for one of the plurality of positions at a second position, and wherein the step of determining the profile data includes the following steps: determining a variation of the thickness of the substrate between the first position and the second position using the first intensity value and the second intensity value.

3. The method as described in claim 1, wherein the profile data characterizing the change in the thickness of the substrate determines: the magnitude of a change in the thickness of the substrate between a first region of the substrate and a second region of the substrate; and an indication of the change in thickness.

4. The method as claimed in claim 1, wherein the first plurality of intensity values ​​identify: a first set of interference fringes for a first region of the substrate and a second set of interference fringes for a second region of the substrate, and wherein the second plurality of intensity values ​​identify: a third set of interference fringes for the first region of the substrate and a fourth set of interference fringes for the second region of the substrate, and wherein the step of determining the profile data includes the following steps: identifying that the relative spatial order of the first set of interference fringes and one of the third set of interference fringes is different from the relative spatial order of the second set of interference fringes and one of the fourth set of interference fringes; and based on the identification, determining that the thickness of the substrate increases in the first region in a scanning direction and decreases in the second region in the scanning direction.

5. The method as described in claim 3, wherein the step of scanning the substrate includes the step of moving at least one of the first beam or the third beam in a spiral pattern relative to the substrate.

6. The method of claim 1, wherein the second beam is a reflected beam resulting from the interaction between the first beam and the substrate, and wherein each of the first plurality of intensity values ​​is associated with a reflectivity of the substrate at a corresponding location among the plurality of locations on the substrate.

7. The method of claim 1, wherein the second beam is a transmitted beam resulting from the interaction between the first beam and the substrate, and wherein each of the first plurality of intensity values ​​is associated with a transmittance of the substrate at a corresponding location among the plurality of locations on the substrate.

8. The method as claimed in claim 1, further comprising the step of: determining that the thickness of a region of the substrate is uniform based on the equality of a subset of the first plurality of intensity values ​​within a target accuracy, wherein each of the subset of the first plurality of intensity values ​​is obtained for the region of the substrate.

9. The method as claimed in claim 1, wherein the step of scanning the substrate by the first beam includes the following steps: drying at least a portion of the substrate by an airflow.

10. The method as described in claim 1 further includes the step of: modifying the thickness of the substrate in at least one region of the substrate based on the determined profile information.

11. The method as described in claim 1, wherein the substrate is a silicon carbide (SiC) wafer.

12. A system configured to scan a substrate, the system comprising: A first light source, used to emit a first beam of light; A first optical sensor for obtaining, at each of a plurality of locations on the substrate, a corresponding of a first plurality of intensity values ​​associated with a second beam, wherein the second beam is generated by the interaction of the first beam with the substrate, and wherein the first plurality of intensity values ​​characterize one or more spatial interference fringes generated by interference between the second beam originating from a first portion of a first surface of the substrate and the second beam originating from a second portion of a second surface of the substrate; and one or more optical elements for guiding a third beam to the substrate. A second optical sensor for obtaining, for each of the plurality of locations on the substrate, a corresponding of a second plurality of intensity values ​​associated with a fourth beam, wherein the fourth beam is caused by the interaction of the third beam with the substrate, and wherein the second plurality of intensity values ​​characterize one or more additional spatial interference fringes caused by interference between the third beam originating from a third portion of a first surface of the substrate and the fourth beam originating from a fourth portion of a second surface of the substrate; and a processing device configured to use the first plurality of intensity values ​​and the second plurality of intensity values ​​to determine a profile of a variation in the thickness of the substrate.

13. The system as claimed in claim 12, wherein the one or more optical elements include at least one of: a second light source for emitting the third beam; or a beam splitter for generating the third beam by splitting a portion of the first beam.

14. The system of claim 13, wherein the first plurality of intensity values ​​identify: a first set of interference fringes for a first region of one of the substrates, and a second set of interference fringes for a second region of one of the substrates, and wherein the second plurality of intensity values ​​identify: a third set of interference fringes for a first region of one of the substrates, and a fourth set of interference fringes for a second region of one of the substrates, and wherein, for determining the profile data, the processing device is configured to: identify that the relative spatial order of one of the first set of interference fringes and one of the third set of interference fringes is different from the relative spatial order of one of the second set of interference fringes and one of the fourth set of interference fringes; and, based on the relative spatial order, determine that the thickness of the substrate increases in the first region in a scanning direction and decreases in the second region in the scanning direction.

15. The system as claimed in claim 12, wherein the third beam has an incident angle on the substrate that is different from the first beam has an incident angle on the substrate.

16. The system as claimed in claim 12, wherein one wavelength of the third beam is different from one wavelength of the first beam.

17. The system of claim 12, wherein the first light source and the first optical sensor are mounted on an optical head, and wherein, in order to scan the substrate, the first light beam is moved relative to the substrate by moving the substrate or at least one of the optical head.

18. The system as claimed in claim 12 further includes a directional air source for drying at least a portion of the substrate by means of an airflow.

19. The system as claimed in claim 12 further includes a substrate processing tool configured to modify the thickness of the substrate, wherein the processing apparatus further applies a machine learning model to the first plurality of intensity values ​​to determine adjusted tooling settings for the substrate processing tool.

20. A system for plotting thickness variations of a substrate, comprising: A movable stage for supporting a substrate; A light source is used to guide a first beam of light to scan the substrate being transported on the movable stage; A first optical sensor for obtaining, at each of a plurality of locations on the substrate, a corresponding of a first plurality of intensity values ​​associated with a second beam, wherein the second beam is generated by the interaction of the first beam with the substrate, and wherein the first plurality of intensity values ​​characterize one or more spatial interference fringes generated by interference between the second beam originating from a first portion of a first surface of the substrate and the second beam originating from a second portion of a second surface of the substrate; and one or more optical elements for guiding a third beam to scan the substrate. A second optical sensor for obtaining, for each of the plurality of locations on the substrate, a corresponding of a second plurality of intensity values ​​associated with a fourth beam, wherein the fourth beam is caused by the interaction of the third beam with the substrate, and wherein the second plurality of intensity values ​​characterize one or more additional spatial interference fringes caused by interference between the third beam originating from a third portion of a first surface of the substrate and the fourth beam originating from a fourth portion of a second surface of the substrate; and a processing device communicatively coupled to the first optical sensor and the second optical sensor, the processing device using the first plurality of intensity values ​​and the second plurality of intensity values ​​to generate profile data characterizing a variation in the thickness of a portion of the substrate.

21. The system as claimed in claim 20 further includes at least one of a deposition apparatus, an etching apparatus, or a polishing apparatus configured to adjust the thickness of at least one of the plurality of locations of the substrate based on the profile information.

22. The system of claim 21, wherein equipment control parameters of at least one of the deposition apparatus, the etching apparatus, or the polishing apparatus are controlled to adjust the thickness of the substrate.

23. The system as described in claim 21, wherein the grinding apparatus is a chemical mechanical polishing (CMP) apparatus.

24. The system as claimed in claim 20, wherein the movable stage includes at least one of i) a robotic blade or ii) a grinding device capable of adjusting the thickness of at least one of the plurality of positions of the substrate.

Images