System and method for mapping thickness variations of substrates in manufacturing systems

Abstract

To enable optical inspection of variations in thickness of substrates during various stages of a manufacturing process in a substrate processing system.SOLUTION: A first set of intensity values associated with a third beam of light caused by a first beam of light incident on a substrate 202 at a first angle of incidence and interacting with the substrate 202, and a second set of intensity values associated with a fourth beam of light caused by a second beam of light incident on the substrate 202 at a second angle of incidence and interacting with the substrate 202 are used to determine thickness profile data of the substrate 202.SELECTED DRAWING: Figure 2A

Description

[Technical Field]

[0001] This specification relates generally to ensuring quality control of materials produced in a substrate processing system, and more particularly to optical inspection of thickness variations of a substrate during various stages of the manufacturing process. [Background technology]

[0002] Modern materials manufacturing 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 onto a substrate (wafer) held in a low- or high-vacuum environment provided by a vacuum deposition chamber. Materials produced in this manner can include single crystals, semiconductor films, fine coatings, and numerous other substances, all of which have practical uses in electronic device manufacturing. Many of these applications rely on the purity of the materials grown in the substrate processing system. The need to maintain chamber-to-chamber environmental separation and minimize exposure to the ambient atmosphere and its contaminants has led to various robotic techniques for sample manipulation and inspection. Improving the accuracy, reliability, and efficiency of such robotic techniques presents several technical challenges, the successful resolution of which will facilitate the continued advancement of electronic device manufacturing. This is especially true given the ever-increasing demands on the quality of chamber-manufactured products. Summary of the Invention

[0003] In one embodiment, a method includes scanning a substrate with a first beam of light; obtaining, for each of a plurality of locations on the substrate, a respective one of a first plurality of intensity values ​​associated with a second beam of light, the second beam of light obtaining a respective one of the first plurality of intensity values ​​caused by an interaction of the first beam of light with the substrate; and determining profile data characterizing variations in thickness of the substrate using the first plurality of intensity values.

[0004] In one embodiment, a system is configured to scan a substrate. The system includes a first light source for emitting a first light beam. The system further includes a first light sensor for obtaining, for each of a plurality of locations on the substrate, a respective one of a first plurality of intensity values ​​associated with a second light beam, the second light beam being caused by an interaction of the first light beam with the substrate. The system further includes a processing device for determining profile data characterizing thickness variations of the substrate using the first plurality of intensity values.

[0005] In one embodiment, a system includes a movable stage for supporting a substrate. The system further includes a light source for directing a first light beam to scan a substrate being transported on the movable stage. The system further includes a first light sensor for obtaining, for each of a plurality of locations on the substrate, a respective one of a first plurality of intensity values ​​associated with a second light beam, the second light beam being caused by an interaction of the first light beam with the substrate. The system further includes a processing device communicatively coupled to the first light sensor for generating profile data characterizing variations in thickness of the substrate. [Brief explanation of the drawings]

[0006] [Figure 1] FIG. 1 illustrates an exemplary embodiment of a manufacturing machine capable of supporting efficient thickness variation metrology of substrates processed therein, according to one embodiment. [Figure 2A] FIG. 1 illustrates a small-spot scanning interferometric system with a single light source for mapping thickness variations in a substrate, according to one embodiment. [Figure 2B] FIG. 1 illustrates a small-spot scanning interferometer system with two light sources for mapping thickness variations in a substrate, according to one embodiment. [Figure 2C] FIG. 1 illustrates a small-spot scanning interferometer system with a single light source and a movable mirror for mapping thickness variations in a substrate, according to one embodiment. [Figure 3] FIG. 2 is a diagram illustrating a schematic of interference fringes for a scan using two light beams over a region of a substrate having thickness variations, according to one embodiment. [Figure 4] FIG. 1 illustrates the integration of machine learning methods for manufacturing process control with optical inspection and metrology, according to one embodiment. [Figure 5] 1 is a flow diagram of a method for mapping the thickness of a substrate, according to one embodiment. [Figure 6] FIG. 1 is a block diagram of an example processing device that operates in accordance with one or more aspects of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0007] Embodiments disclosed herein provide optical mapping of substrate and wafer thickness variations due to non-uniformities resulting from wafer fabrication processes, including polishing, etching, material deposition, and the like, to smooth, add, and / or remove material. For example, the disclosed embodiments may enable determining 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 thickness profile variations resulting from deposition and / or etching processes. In some embodiments, deposition may include epitaxial silicon carbide (SiC) deposition, which may occur after CMP. Furthermore, once the thickness variation profile is known, the metrology data may indicate how best to correct unwanted thickness variations and create as uniform a surface as possible (or achieve other target thickness variations, as may be specified by the technology process being performed). For example, the thickness variation profile may be used in a feedback process within a processing chamber to add or remove additional material, such as a transparent film, from the substrate as needed.

[0008] Precise thickness metrology can be useful in many disciplines of technological and commercial interest, including the production of flat semiconductor wafers (e.g., optical flats). During the manufacturing process of optical flats and semiconductor wafers, thickness non-uniformities can occur within a few microns. Furthermore, wafer thickness variations generally have a low spatial frequency across the wafer. In some embodiments, the objective of thickness metrology of semiconductor wafers, e.g., transparent semiconductor wafers, is not the absolute thickness itself, since absolute thickness can be controlled to within a few microns, but rather the thickness variation across the wafer. For example, in some manufacturing operations (e.g., CMP operations) performed on semiconductor wafers, the intent may be to produce wafers that are as flat and uniform as possible.

[0009] Therefore, it may be advantageous to have information regarding thickness variations of a surface, which may relate to its quality, roughness, etc., before the manufacturing process is completed, to enable correction of processing errors and defects while the sample is still inside the processing system. In some embodiments, the target surface may have a complex profile, including several ridges, depressions, kinks, grooves, flat regions, rounded regions, etc. For example, the thickness profile of a wafer surface may be represented by the dependence of the height (width, depth) of the target surface h(x,y) measured from some reference surface (e.g., a horizontal or vertical plane) on the coordinates (e.g., x,y) along this reference surface. The profile may be characterized by a discrete (or quasi-continuous) set of locations with a resolution determined by the spacing (e.g., Δx, Δy) between adjacent locations. The spacing may be preset based on the desired resolution of the target surface imaging.

[0010] Existing techniques for performing precision thickness measurements may include the use of capacitive probes, confocal microscopes, interferometric methods, etc., each of which has its own advantages and disadvantages when applied to specific use cases. For example, interferometric techniques (both absolute and differential) can offer good sensitivity for both large and small substrates and have been implemented with varying degrees of success.

[0011] However, in many cases, optical techniques for performing thickness metrology (also called wafer topography) often require measuring two surfaces individually to obtain two separate maps, and comparison of such maps allows wafer thickness variation to be determined. Such methods require elaborate setups in which proper processing relies on referencing an optical flat that must be precisely held relative to the semiconductor wafer in a highly stabilized environment. Therefore, constantly monitoring and mapping thickness variations can be time-consuming and expensive. Such standalone, highly optimized setups may be undesirable, especially when on-board metrology is required.

[0012] Aspects and embodiments of the present disclosure address these and other shortcomings of existing technologies. A method and setup for efficient optical thickness metrology of substrates is described herein. This facilitates compact, stable, and affordable data collection that can provide high-sensitivity and high-resolution information regarding the effectiveness of technology processes, such as deposition (such as epitaxial silicon carbide (SiC) deposition, which may occur after CMP), etching, CMP, or any other manufacturing process. Furthermore, the solution can be implemented as an on-board metrology system.

[0013] During manufacturing processes involving optical flats and semiconductor wafers, thickness non-uniformities can occur within a few microns. Furthermore, wafer thickness variations generally have a low spatial frequency across the wafer. Thus, assuming that the wafer of interest is transparent at a particular wavelength of electromagnetic radiation (such as an optical wavelength), the passage of coherent radiation through the wafer occurs with multiple internal reflections. This phenomenon can be exploited to implement an etalon-type interferometer to map thickness variations across the surface of the wafer.

[0014] The disclosed embodiments relate to various manufacturing techniques that use processing chambers (which may include deposition chambers, etch chambers, etc.), such as chemical mechanical polishing (CMP) techniques, chemical vapor deposition (CVD) techniques, physical vapor deposition (PVD), plasma CVD, plasma PVD, sputter deposition, atomic layer CVD, combustion CVD, catalytic CVD, evaporation, molecular beam epitaxy techniques, etc. While the most significant practical impact of the disclosed embodiments can be expected to occur in techniques that use vacuum deposition chambers (e.g., ultra-high vacuum CVD or PVD, low pressure CVD, etc.), the same systems and methods can be utilized in atmospheric pressure deposition chambers for non-intrusive monitoring of chamber conditions present during the deposition process.

[0015] FIG. 1 illustrates an exemplary embodiment of a manufacturing machine 100 capable of supporting efficient thickness variation metrology 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 chamber(s) 106 may be interfaced to the transfer chamber 104 via a transfer port (not shown). The number of processing chamber(s) associated with the transfer chamber 104 may vary (by way of example, three processing chambers are shown in FIG. 1 ). The transfer chamber 104 may include a robot 108, a robot blade 110 for supporting a substrate (e.g., a wafer or transparent wafer), a light source(s) 112 for scanning the substrate 116 (e.g., a target), and an optical sensor 114 disposed in one of the processing chambers 106. The light source(s) 112 and the optical sensor 114 may be part of a thickness mapping device 111. The transfer chamber 104 may be maintained at a pressure (temperature) above (or below) atmospheric pressure (temperature).

[0016] The robot 108 can transfer various products and devices (eg, semiconductor wafers, substrates, liquid crystal displays, reticles, calibration devices) between the loading station 102 and one of the processing chambers 106 .

[0017] In one embodiment, the robot blade 110 of the robot 108 supports the substrate 116 as it is transferred to one of the processing chambers 106. The robot blade 110 may be attached to an extendable arm sufficient to reach between different chambers. The light source(s) 112 may scan the substrate 116 with one or more light beams to obtain intensity values ​​caused by reflection of the one or more light beams from the substrate 116. The substrate 116 may be a wafer, substrate chuck, edge ring, or any other object / tool ​​disposed in one of the processing chambers 106 (or in the loading station 102, the transfer chamber 104, or a port connecting the transfer chamber 104 to the loading station 102 or a processing chamber 106). The reflected light beams may be received by one or more optical sensors 114. The thickness mapping device 111 may include alignment points for proper alignment with the substrate 116. The alignment point may be a hole, notch, or indentation, and may be centered within a pocket or recess in the robot blade 110. The optical sensor 114 of the thickness mapping device 111 may be capable of sensing visible light or other electromagnetic radiation coming from (e.g., reflected by) the target surface of the substrate 116. The light detected by the optical sensor 114 may be reflected from the target surface to which the light may be directed by one or more light sources 112. In some embodiments, the light sources 112 may be mounted on the same thickness mapping device 111. In other embodiments, the light sources 112 may be located outside the thickness mapping device 111, for example, mounted inside the transfer chamber 104, loading station 102, or processing chamber 106. The robot blade 110 may supply (and remove) substrates to (and from) the processing chamber(s) 106 through a slit valve port (not shown) while the lid to the processing chamber(s) 106 remains closed. The processing chamber(s) 106 may contain the processing gases, plasma, and various particles used in the deposition process.A magnetic field may be present inside the processing chamber(s) 106. The inside of the processing chamber(s) 106 may be maintained at a temperature and pressure that is different from the temperature and pressure outside the processing chamber(s) 106. The temperature and pressure inside the processing chamber(s) 106 may be similar to those that correspond to actual online processing conditions. While the substrate 116 is shown as being supported and moved by the robot blade 110 of the robot 108, in other embodiments, the substrate 116 may be moved using a dedicated motion stage, or any other suitable movable stage, an existing substrate transfer mechanism, an existing motion mechanism in the process chamber (such as a polishing head or another wafer deployed in a CMP process).

[0018] The computing device 118 may include a light sensor control module 122 and a thickness analysis module 124. The light sensor control module 122 may control the operation of the light sensor 114 and, in some cases, the light source(s) 112. The thickness analysis module 124 may receive intensity values ​​measured by the light sensor 114 and determine a thickness variation map of the substrate 116.

[0019] In one exemplary embodiment, the electronics module 150 may be capable of facilitating wireless thickness variation mapping of targets inside the manufacturing machine 100 to determine profile data corresponding to thickness variations of the substrate. The electronics 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 sending the data to the computing device 118. In some embodiments, the data may be sent using wireless communication circuitry. In other embodiments, the data may be sent using a wired connection between the electronics module 150 and the computing device 118. In some embodiments, the data may be first stored (buffered) in a memory buffer before being sent to the computing device 118. In other embodiments, the data may be sent to the computing device 118 as the data is collected without being stored in a 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 upon completion of an inspection or some other triggering event (e.g., when the memory buffer is near full). The electronics module 150 may further include a power element and a start-up circuit. In some embodiments, the power element may be a battery. In some embodiments, the power element may be a capacitor. The power element may be rechargeable from a power station. The microcontroller may be coupled to one or more light sensors 114. The light sensors 114 may include a light source and a light detector. The electronics module 150 may also include an accelerometer to facilitate precise extension and angular rotation of the robot blade 110. The electronics module 150 may also include a temperature sensor to detect the temperature near the substrate 116.

[0020] The electronics module 150 may further include wireless communication circuitry, i.e., radio circuitry for receiving wireless instructions from the computing device 118 and for sending intensity values ​​to the computing device 118. For example, the radio circuitry may, in one embodiment, 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, that may be exposed to a chamber temperature of 450 degrees C for a short period of time, such as 1 to 8 minutes.

[0021] Some components may be located on or in the fixed portion of the robot 108. For example, a microcontroller, a memory buffer, and an RF front end may also be located. Other components of the electronics module 150 may be located on or in the robot blade 110 of the robot 108 and / or a thickness mapping device supported by the robot blade. The robot blade may be movable to support a substrate that may be transported by the robot blade. For example, an optical sensor 114, an accelerometer, and a temperature sensor may also be located. In some embodiments, some of the components of the electronics module 150 may be located on both the fixed portion of the robot 108 and the extendable robot blade 110, such as power elements. In some embodiments, two separate microcontrollers may be implemented, one of the microcontrollers located on the fixed portion of the robot 108 and the other microcontroller located on the thickness mapping device 111.

[0022] A wireless connection facilitated by an RF front end and antenna may, in some embodiments, support a communications link between the microcontroller and the computing device 118. In some embodiments, a microcontroller integrated with the robot 108 may have minimal computing capabilities sufficient to communicate information to the computing device 118, where the majority of the information processing may occur. In other embodiments, the microcontroller may perform a significant portion of the computations, while the computing device 118 may provide computational support for specific, processing-intensive tasks. Data received by the computing device 118 may be data acquired from inside 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 a memory buffer and / or sent to or from the computing device 118 may be in a raw format or a processed format.

[0023] In one embodiment, the thickness mapping device may determine and output (using the processing power of the microcontroller and / or computing device 118) profile data characterizing thickness variations of the substrate based on intensity values ​​associated with one or more received light beams. The one or more received light beams may be caused by scanning and interaction of the substrate with one or more incident light beams. The intensity values ​​may be attributed to one or more locations on the substrate.

[0024] For example, the thickness mapping device 111 may scan the substrate with a first light beam from the light source(s) 112. The thickness mapping device 111 may acquire intensity values ​​associated with a second light beam corresponding to one or more locations on the substrate. The second light beam may be caused by an interaction between the first light beam and the substrate. The interaction may include reflection or transmission of the first (incident) light beam with the substrate. Thus, the second light beam may be a reflected beam or a transmitted beam. The thickness mapping device 111 may use the acquired intensity values ​​to determine profile data characterizing thickness variations of the substrate. In some cases, during substrate processing stages, such as deposition, etching, polishing, etc., slurry (which may include beads of water and / or other materials used in processing) may form that is detrimental to the accuracy of optical measurements and thickness mapping. To remove residual water, in some embodiments, a directed gas source (e.g., a jet of gas), such as nitrogen, argon, xenon, air, etc., may be applied to dry the substrate prior to scanning with the light beam to minimize the optical effects of such extraneous materials and ensure the accuracy of the determined profile data.

[0025] Multiple intensity values ​​may be determined for the substrate. In some embodiments, if thickness mapping is performed using reflected light, the intensity values ​​may represent the reflectivity of the substrate at various locations. In some embodiments, if 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 of the substrate may interfere with light reflected from the bottom surface, the reflectivity and / or transmittance may exhibit a series of bright (maximum) and dark (minimum) interference fringes. Such interference fringes may be used as a benchmark for determining the thickness (and / or thickness variation) of the substrate, as described in more detail below. In particular, the intensity values ​​may include at least a first intensity value from a first location of the one or more locations and a second intensity value from a second location of the one or more locations. The profile data may use the first intensity value and the second intensity value to identify thickness changes of the substrate between the first and second locations.

[0026] Because reflectance (and / or transmittance) may be a periodic function of substrate thickness, in some cases there may be some ambiguity as to whether the thickness is increasing or decreasing between a first location and a second location. For example, for a given wavelength λ and incident angle θ, the intensity I=f(d;λ,θ) of a reflected (or transmitted) light beam may contain several interference maxima and minima for varying substrate thicknesses d. As a result, when a first intensity value determined at a first location, e.g., I=f(d;λ,θ), is close to the maximum (or minimum) of the function f, a lower (or higher) second intensity value, e.g., I=f(d;λ,θ), may not fully determine whether the substrate thickness is increasing (d>d) or decreasing (d>d) between the first and second locations. In such cases, the thickness mapping device 111 may scan the substrate with an additional light beam (e.g., a third light beam) from the same or other light source(s) 112. The third light beam may differ from the first light beam by at least one of wavelength (e.g., λ2) or angle of incidence relative to the substrate (e.g., θ2). For example, in one embodiment, there may be two (or more) light sources 112, each providing a light beam of a different wavelength. In another embodiment, there may be a single light source 112 providing a light beam, which may be 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 light beams incident on the substrate may have different wavelengths as well as different angles of incidence. In either case, the thickness mapping device 111 may obtain a second set of intensity values ​​associated with at least some of the one or more locations on the substrate. The fourth light beam may be caused by the interaction of the third light beam with the substrate and may be a reflected or transmitted beam (like the second beam).To resolve possible ambiguity as to whether the thickness is increasing or decreasing, the thickness mapping device may determine and output a profile based on both the first set of intensity values ​​and the second set of intensity values, for example, I3=f(d1;λ2,θ2) and I4=f(d2;λ2,θ2).

[0027] 2A shows a small-spot scanning interferometer system 200 with a single light source 204 for mapping thickness variations of a substrate 202, according to one embodiment. The interferometer system 200 may include a light source 204, a detector 206, and a beam splitter 208. In some embodiments, the thickness variation mapping setup may include an optical head 212 that combines one or more of the light source 204, the detector 206, and the beam splitter 208. The substrate may be supported by lift pins 210. The pins 210 may be used for edge handling of the substrate 202. In some embodiments, the substrate may be a silicon carbide (SiC) wafer.

[0028] The substrate 202 may be illuminated by an incident beam 214 of light (or other form of electromagnetic radiation), and a reflected beam 216 may be generated upon interaction of the incident beam 214 with 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 light beam. The intensity of the reflected beam 216 may exhibit several bright and dark fringes (e.g., as a function of substrate thickness) caused by constructive and destructive interference, respectively, of multiple internal reflections of the beam within the substrate 202. As the incident beam 214 is moved relative to the substrate 202 (or the substrate 202 is transported relative to the incident beam 214), uniform small variations in the thickness of the substrate may lead to a series of alternating fringes—peaks and valleys / troughs—in the intensity of the reflected (or transmitted) beam.

[0029] The spatial frequency of the alternating peaks / valleys (e.g., the inverse of the lateral distance between adjacent fringes) can be determined by the thickness variation of the substrate 202 (e.g., the tangent of the angle the surface makes with the horizontal), the wavelength of the incident light beam, and the angle of incidence of the light beam with respect to the substrate. Thus, by scanning the substrate 202 with a light beam at a known frequency and a known angle of incidence, the thickness profile of the substrate can be mapped. For example, the substrate 202 can be scanned in various manners. In one embodiment, the substrate 202 can be rotated and radially translated such that the entire surface of the substrate 202 is scanned in a spiral trace. In another embodiment, the substrate 202 can be fixed while the optical head 212 is rotated in a spiral pattern such that the entire surface of the substrate 202 is scanned. In another embodiment, the substrate 202 can be raster scanned by moving one or both of the substrate 202 or the optical head 212 in a rectangular pattern.

[0030] As shown in FIG. 2A , the optical head 212 may include a light source 204 that emits a light beam at a wavelength λ. The light beam may be split into a first light beam and a second light beam, each having a wavelength λ. The first light beam may be incident on the substrate 202 at a first angle of incidence and may interact with the substrate 202. The first detector 206 a may detect a first set of intensity values ​​associated with a third light beam caused by the first light beam interacting with the substrate 202. Each intensity value may be associated with a set of locations on the substrate 202 according to a selected scan pattern (e.g., spiral, rectangular, etc.). Similarly, the second light beam may be incident on the substrate 202 at a second angle of incidence and may interact with the substrate 202. The second detector 206 b may detect a second set of intensity values ​​associated with a fourth light beam caused by the third light beam interacting with the substrate 202. Each intensity value may be associated with one of the set of locations on the substrate 202 according to a selected scan pattern. The first set of intensity values ​​and / or the second set of intensity values ​​may then be used to determine thickness profile data for the substrate 202 .

[0031] In some embodiments in which light reflected from the substrate 202 is detected, an absorber 218 may be located opposite (e.g., below) the substrate 202 to prevent (or minimize) light transmitted through the substrate from reflecting back onto the substrate and affecting the substrate reflectivity data acquired by detectors 206a and 206b. The absorber 218 may include special anti-reflective materials to prevent light from interacting with the underlying substrate support. Additionally or alternatively, the backside of the substrate may include special anti-reflective materials to prevent light from interacting with the underlying substrate support.

[0032] Figure 2B shows a small-spot scanning interferometer system 200 with two light sources 204a and 204b for mapping thickness variations in a substrate 202, according to one embodiment. The small-spot scanning interferometer system 200 of Figure 2B may be similar to the small-spot scanning interferometer system 200 of Figure 2A, but may have an optical head that includes multiple (two or more) light sources.

[0033] As shown in FIG. 2B , the optical head 212 may include a first light source 204a and a second light source 204b that may emit light beams having a first wavelength λ1 and a second wavelength λ2. The first light beam may be incident on the substrate 202 at a given angle of incidence (e.g., a normal angle or other small angle) and may interact with the substrate 202. The first detector 206a may detect a first set of intensity values ​​associated with a third light beam caused by the first light beam interacting with the substrate 202. Each intensity value may be associated with one of a set of locations on the substrate 202 according to a scan pattern. Similarly, the second light beam may be incident on the substrate 202 at a given angle of incidence and may interact with the substrate 202. The second detector 206b may detect a second set of intensity values ​​associated with a fourth light beam caused by the second light beam interacting with the substrate 202. Each intensity value may be associated with a set of locations on the substrate 202 according to a scan pattern. The first set of intensity values ​​and the second set of intensity values ​​may be used to determine thickness profile data for the substrate 202 .

[0034] FIG. 2C illustrates a small-spot scanning interferometer system 201 with a single light source 204 and a movable mirror for mapping thickness variations in a substrate 202, according to one embodiment. The small-spot scanning interferometer system 201 may be similar to the small-spot scanning interferometer system 200 of FIGS. 2A-2B, as indicated by like reference numerals. As shown in FIG. 2C, a light beam from the light source 204 may be directed toward a beam splitter 208. The beam splitter 208 splits the light beam into a first incident light beam 214a and a second incident light beam 214b. The first incident light beam 214a may be incident on the substrate 202 (e.g., a sample) at a first angle of incidence. The second incident light beam 214a to the sample may be directed toward the sample by a mirror 220. The mirror 220 may be tilted by an angle to set a second angle of incidence of the second incident light beam 214b to the sample. In some embodiments, mirror 220 may be mounted on a tilting stage, such that changes in tilt may alter the angle of incidence of second light beam 214a. Referring to equation (2) (presented below), Snell's law relates the internal reflection angle β to the angle of incidence α relative to the sample: nsinβ=sinα

[0035] Therefore, a small change in α will result in a change in the internal reflection angle. This will result in a shift in the fringe position, as per Equation (1) (introduced below). Therefore, the fringe position can be adjusted or changed by very small changes in the angle of incidence. Such small changes to the angle of incidence will result in negligible changes to the beam position on the substrate 202. This allows for the ability to resolve thickness variation ambiguities. For example, if the thickness variation of the substrate 202 is such that the signal in the thickness plateau region (i.e., the location where the signal does not change as a function of position on the sample) is at a maximum or minimum for both angles of incidence, then a small shift in the angle of incidence of one beam will break the coincidence of the two signals at their maximum or minimum values, thus resolving the ambiguity condition. Small changes in the angle of incidence can be easily achieved, for example, by using a piezo-mounted mirror.

[0036] In some embodiments, the small-spot scanning interferometer systems 200 and 201 can be combined with a mass metrology system to perform cross-validation of deposition and etch processes. For example, the mass metrology system can provide information about the total mass change of the substrate due to a processing operation (without providing spatial information), and the thickness variation profile can indicate regions of non-uniform thickness due to the processing operation. In such a manner, determining the thickness variation profile can be used as a feedforward or feedback mechanism for an additive or subtractive process.

[0037] 3 shows a schematic representation of intensity values ​​and interference fringes for a scan using two light beams over a region of a substrate with thickness variations, according to one embodiment. Making the assumption that the substrate is illuminated from above with coherent, collimated radiation, the reflected response can appear as several parallel fringes.

[0038] For example, the intensity of the fringes is TIFF2025148336000002.tif28170, where: TIFF2025148336000003.tif17170, where β is the angle of internal reflection 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 r 2 is the surface reflectance.

[0039] For a given light beam, the spatial frequency of the interference fringes can be determined by the slope of the thickness fluctuations, the angle of incidence, and the wavelength. For example, dark fringes in reflectance can be encountered at points (x, y) on the substrate where θ = 0, 2π, 4π... Thus, different dark fringes in reflectance can correspond to locations on the substrate where the thickness differs by integer multiples of Δh = λ / (2n cos β). Correspondingly, local maxima in reflectance are encountered at locations where the substrate thickness differs by ±Δh / 2 from the thickness at the location where the reflectance has a dark fringe (local minimum). Thus, the substrate can be scanned with a first (incident) light beam, and a second (reflected or transmitted) light beam corresponding to the interaction of the first light beam with the substrate can be detected. A first set of intensity values ​​associated with the second light beam and corresponding to various locations on the substrate can be obtained (e.g., using detector 206). The first set of intensity values ​​can be used to determine profile data characterizing the thickness fluctuations h(x, y) of the substrate.

[0040] In particular, the intensity values ​​may include a first intensity value I(x1, y1) for the first location and a second intensity value I(x2, y2) for the second location. The first and second intensity values ​​may be used to determine a change in thickness Δh of the substrate between the first and second locations. However, as explained above, in some cases, particularly when the reflection (or transmission) at the plateau is close to a maximum or minimum, there may be some ambiguity as to whether the thickness is increasing or decreasing after the plateau.

[0041] A plateau may be identified based on a subset of the first set of intensity values ​​being equal. It should be understood that two substrate thicknesses h1 and h2 may still be considered equal if the difference |h1-h2|<δh is within a target accuracy δh. The target accuracy δh may refer to a desired accuracy of the manufacturing process. In some embodiments, the target accuracy δh may refer to the resolution of the optical inspection system. For example, if the resolution of the optical inspection system is δh r If |h1-h2|<δh r can be considered to have equal thickness.

[0042] In some cases, a plateau of equal thickness (in the sense described above) may be close to a particular thickness where the reflectance or transmittance has a maximum or minimum value. As the thickness changes, the reflectance or transmittance may decrease or increase, respectively, regardless of whether the substrate thickness is increasing or decreasing. To resolve such ambiguities, additional scans may be performed with additional beams having different angles of incidence and / or different wavelengths. Generally, even if the reflectance or transmittance of the first beam is at a peak or trough on the plateau, the additional beams (if they have different angles of incidence and / or wavelengths) will not be close to their maximum or minimum values. The additional beams may therefore serve as disambiguating benchmarks for comparing the reflectance / transmittance of the first beam.

[0043] More specifically, the substrate may be scanned with an additional light beam (e.g., a third light beam). The third light beam may differ from the first light beam in at least one of wavelength λ2 or angle of incidence θ2 relative to the substrate. A fourth light beam corresponding to the interaction of the third light beam with the substrate may be detected. A second set of intensity values ​​corresponding to various locations on the substrate associated with the fourth light beam may be obtained. The second set of intensity values ​​may be used to further determine profile data characterizing thickness variations of the substrate. Because the first and third light beams have different wavelengths and / or angles of incidence (leading to different internal reflection angles), the intensity fringes produced by the first and third light beams are different. This provides the ability to remove ambiguity as to whether the thickness is increasing or decreasing following scanning of the plateau.

[0044] For example, when scanning is performed in the direction of increasing thickness, the intensity maxima or minima of the second beam (e.g., the reflected λ1, θ1 light) are encountered at a different (spatial) frequency than the intensity maxima and minima of the fourth beam (e.g., the reflected λ2, θ2 light). As shown in FIG. 3, in the first region 303 of positive slope, the interference fringes 301 (solid lines) resulting from scanning with the first light beam are shifted to the left relative to the interference fringes 302 (dashed lines) resulting from scanning with the third light beam. In the second region 305, the slope is zero (plateau region), and the intensity for both 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 (the interference fringes 301 are shifted to the right). For example, interference fringes 313 and 315 exhibit opposite slopes due to the reversal of the relative order of the fringes from the scans with the first and third light beams. After another plateau in the fourth region 309, in the fifth region 311, the slope is again positive, and the relative spatial order of interference fringes 301 and 302 is reversed compared to the third region 307. As shown, interference fringes 317 and 319 exhibit opposite slopes due to the reversal of the relative order of the fringes from the scans with the first and third light beams. In a similar manner, interference fringes 313 and 319 have the same relative order, indicating that the slope in the first region 303 and the fifth region 311 is the same (e.g., positive).

[0045] FIG. 4 illustrates the integration of machine learning methods for manufacturing process control with optical inspection and metrology, according to one embodiment. A substrate 202 being processed by a process tool 410, which may be a CMP (or some other polishing device), is shown in FIG. 4. A metrology device, e.g., an optical head 212 (or some other measurement device), may monitor the real-time state of the substrate 202. For example, the optical head 212 may determine the thickness and profile of the substrate 202 while the process tool 410 changes the state of the substrate, e.g., by removing material from the substrate 202. The profile data 420 output by the optical head 212 may be processed by one or more machine learning models 430 (MLMs). The MLMs 430 may be or include a decision tree algorithm, a support vector machine, a deep neural network, or any combination thereof. The deep neural network may include a convolutional neural network, a recurrent neural network (RNN) with one or more hidden layers, a fully connected neural network, a long short-term memory neural network, a Boltzmann machine, etc. The MLM 430 may be trained to perform a particular technology process, including a particular substrate profile to be created over a particular time period, a particular quality of the substrate's surface to be achieved, etc. The MLM 430 may use as input the profile data 420, a technology process specification (not shown), a current timestamp (e.g., counted from the beginning of the technology process), and other suitable data. The MLM 430 may output (e.g., in real time) tool settings 440 for the process tool 410. The tool settings may include the pressure applied by the process tool 410 against the substrate 202, the rate of material removal from the substrate 202, the speed of rotation of the process tool 410, or any other applicable tool settings 440. As processing by the process tool 410 continues, the tool settings 440 may change accordingly. For example, when approaching a target profile, the MLM 430 may output tool settings 440 to slow down the rate of material removal, reduce pressure on the substrate, etc.

[0046] In some embodiments, the metrology device (e.g., optical head 212) continuously monitors the condition of substrate 202 (e.g., by moving over substrate 202 in a predetermined pattern). In some embodiments, the metrology device may monitor the condition of substrate 202 periodically, such as at specific times.

[0047] The MLM 430 can be trained by an MLM training engine 450. The training engine 450 can be located on the same manufacturing machine that hosts the process tool 410 and the metrology device, or on some external server communicatively coupled to the manufacturing machine. In some embodiments, the MLM training engine 450 can be located on a server that does not interact with the manufacturing machine, and the trained MLM is installed on the manufacturing machine after training is performed. The MLM training engine 450 can use training data 460, which can include data related to similar types of substrates and processed in a similar (or the same) technology process. For example, the training data 460 can include dynamic profile data as well as tool settings implemented during previous processing of similar wafers. The training data 460 can further include annotations indicating correct and incorrect processing. In some embodiments, the MLM training engine 450 can train the MLM 430 in real time on the same manufacturing machine as the process tool 410, for example, using self-directed training iterations for a single (or multiple) batches of substrates.

[0048] FIG. 5 is a flow diagram of a method 500 for mapping the thickness of a substrate, according to one embodiment. Method 500 may be implemented using the systems and components shown in FIGS. 1 and 2A-2B, or some combination thereof. Method 500 may be implemented using a single optical sensor or multiple optical sensors. The optical sensor may be configured to scan the substrate as shown in FIGS. 2A-2B. Some or all of the blocks of method 500 may be implemented in some embodiments 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), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), a network processor, etc. The processing device(s) are communicatively coupled to one or more memory devices, such as read-only memory (ROM), flash memory, static memory, dynamic random access memory (DRAM), etc. The microcontroller 152 can be part of a desktop computer, a laptop computer, a workstation, a wearable device (e.g., a tablet, a smartphone, etc.), a cloud-based computing service, etc. In some embodiments, the microcontroller 152 is part of a larger network of computing devices. In some embodiments, an external computing device that communicates with the microcontroller 152 can reconfigure (e.g., change settings, update memory, or possibly reprogram) the microcontroller 152. In some embodiments, the thickness mapping method 500 can be performed while the wafer is inside the processing chamber. In some embodiments, the method 500 can be performed once the wafer is removed from the processing chamber. The thickness mapping method can be performed under conditions (e.g., pressure and temperature) that are similar to the actual conditions in the processing chamber during the manufacturing process. Thus, the manufacturing process can be performed at low temperatures, or at temperatures below or significantly below room temperature.Alternatively, the fabrication process can be carried out at room temperature, above room temperature, or significantly above room temperature. In some embodiments, the pressure inside the chamber can be below or significantly below atmospheric pressure, including low or high vacuum conditions.

[0049] The method 500 may include scanning a substrate with a first light beam (block 502). The first light beam may be emitted from a laser, a narrowband light source, a broadband light source whose spectral distribution is later narrowed, a spectrally narrowed light emitting diode, etc. The first light beam may have a first wavelength and be incident on the substrate at a first angle. Scanning the substrate may include moving the first light beam relative to the substrate. In some embodiments, the light source (and light detector) are stationary (e.g., relative to the substrate processing system) while the substrate is moving. For example, the substrate may be transported under the light source (and light detector) while the scanning is performed. In some embodiments, the first light beam is moved in a spiral pattern relative to the substrate. In some embodiments, the first light beam is moved relative to the substrate in a rectangular pattern, a zigzag pattern, or any other geometric pattern.

[0050] The method 500 may continue by obtaining (block 504) a respective one of a first set of intensity values ​​associated with a second light beam for each of the set of substrate locations. The second light beam may be caused by the interaction of the first light beam with the substrate. The first set of intensity values ​​associated with the second light beam may include at least a first intensity value for a first location of the set of locations and a second intensity value for a second location of the set of locations. In one embodiment, the second light beam is a reflected beam caused by the interaction of the first light beam with the substrate, and each of the first set of intensity values ​​is associated with the reflectivity of the substrate at a respective location of the set of substrate locations. In another embodiment, the second light beam is a transmitted beam caused by the interaction of the first light beam with the substrate, and each of the first set of intensity values ​​is associated with the transmittance of the substrate at a respective location of the set of substrate locations.

[0051] The method 500 may continue with determining profile data characterizing variations in thickness of the substrate (block 506). Determining the profile data may be based on using the first set of intensity values ​​and may correspond to determining a change in thickness of the substrate between the first location and the second location using the first intensity value and the second intensity value, and the method 500 ends.

[0052] In a further embodiment, the method 500 may further include scanning the substrate with a third light beam. The third light beam may differ from the first light beam in at least one of wavelength or angle of incidence of the light beam relative to the substrate. In a further embodiment, the method 500 may further include obtaining, for at least some of the locations of the substrate, a respective one of a second plurality of intensity values ​​associated with a fourth light beam. The fourth light beam may be caused by an interaction of the third light beam with the substrate, and determining the profile data may be further based on the second set of intensity values.

[0053] The second set of intensity values ​​associated with the fourth beam may identify a third group of interference fringes for the first region of the substrate and a fourth group of interference fringes for the second region of the substrate. In some embodiments, determining the profile data further includes identifying that the relative spatial order of the first group of interference fringes and the third group of interference fringes is different from the relative spatial order of the second group of interference fringes and the fourth group of interference fringes. The identified relative spatial order of the interference fringes may be used to determine whether the thickness of the substrate is either increasing in the direction of the scan (e.g., in the first region) and decreasing in the direction of the scan (e.g., in the second region), or vice versa.

[0054] Scanning the substrate may include moving at least one of the first light beam or the third light beam in a spiral pattern relative to the substrate. In other embodiments, scanning the substrate may include moving the substrate in a spiral pattern relative to at least one of the first light beam or the third light beam. In some embodiments, scanning the substrate may include scanning in a pattern other than a spiral, for example, in a raster scan pattern.

[0055] In some embodiments, if a subset of the first set of intensity values ​​is determined to be substantially equal (e.g., equal within a target accuracy value), it may be determined that the thickness of the region of the substrate is uniform.

[0056] In some embodiments, for example, residual CMP water may remain on the substrate. To improve the accuracy of the thickness mapping, a portion of the substrate may be dried (or cleaned) with a flow of gas (such as nitrogen, argon, xenon, air, etc.) prior to scanning.

[0057] In some embodiments, the thickness of the substrate may be modified (either increased (e.g., by additional deposition by a deposition device), decreased (e.g., etched using an etching device or polished using a polishing device), or otherwise adjusted) in view of the determined thickness profile data. In some embodiments, the substrate is a SiC wafer, which may be adjusted by varying device control parameters. The control parameters may determine the rate or amount of material added to (or removed from) the substrate.

[0058] The systems and methods disclosed herein can be used for thickness variation monitoring during manufacturing, as well as for testing and development of 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, etc.

[0059] 6 illustrates a block diagram of an exemplary processing device 600 that operates in accordance with one or more aspects of the present disclosure. The processing device 600 may be the computing device 118 of FIG.

[0060] The exemplary processing device 600 may be connected to other processing devices in a local area network (LAN), an intranet, an extranet, and / or the Internet. The processing device 600 may be a personal computer (PC), a set-top box (STB), a server, a network router, a switch or bridge, or any device capable of executing a set of instructions (sequential or otherwise) that specify actions to be taken by that device. Furthermore, although only a single exemplary processing device is shown, the term "processing device" shall also be taken to include any collection of processing devices (e.g., computers) that individually or together execute a set (or sets) of instructions to perform any one or more of the methodologies described herein.

[0061] The exemplary processing device 600 may include a processor 602 (e.g., a CPU), a main memory 604 (e.g., read-only memory (ROM), flash memory, dynamic random access memory (DRAM) such as synchronous DRAM (SDRAM), etc.), a static memory 606 (e.g., flash memory, static random access memory (SRAM), etc.), and a secondary memory (e.g., a data storage device 618), which may communicate with each other via a bus 630.

[0062] The processor 602 represents one or more general-purpose processing devices, such as a microprocessor, a central processing unit, or the like. More specifically, the 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. The processor 602 may also be one or more special-purpose processing devices, such as an application specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal processor (DSP), a network processor, or the like. According to one or more aspects of the present disclosure, the processor 602 may be configured to execute instructions implementing the method 500 of thickness variation mapping.

[0063] The example processing device 600 may further include a network interface device 608 that may be communicatively coupled to a network 620. The example 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)), an alphanumeric 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., an audio speaker).

[0064] 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 thereon one or more sets of executable instructions 622. According to one or more aspects of the present disclosure, the executable instructions 622 may include executable instructions that implement the method 500 of thickness variation mapping.

[0065] The executable instructions 622 may also reside, completely or at least partially, within the main memory 604 and / or within the processor 602 during execution of the executable instructions 622 by the exemplary processing device 600, with the main memory 604 and the processor 602 also constituting computer-readable storage media. The executable instructions 622 may further be transmitted or received over a network via the network interface device 608.

[0066] While computer-readable storage medium 628 is illustrated in FIG. 6 as a single medium, the term "computer-readable storage medium" shall be interpreted to include a single medium or multiple media (e.g., centralized or distributed databases, and / or associated caches and servers) that store one or more sets of operating instructions. The term "computer-readable storage medium" shall also be interpreted to include any medium capable of storing or encoding a set of instructions for execution by a machine, causing the machine to perform any one or more of the methodologies described herein. The term "computer-readable storage medium" shall therefore be interpreted to include, but not be limited to, solid-state memories and optical and magnetic media.

[0067] It should be understood that the above description is illustrative, and not restrictive. Many other embodiments will be apparent to those skilled in the art upon reading and understanding the above description. While the present disclosure describes particular examples, it will be recognized that the systems and methods of the present disclosure are not limited to the examples described herein, but may be practiced with modification within the scope of the appended claims. Accordingly, the specification and drawings should be considered in an illustrative rather than a restrictive sense. The scope of the present disclosure should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled.

[0068] The method, hardware, software, firmware, or code embodiments described above may be implemented via instructions or code stored on a machine-accessible, machine-readable, computer-accessible, or computer-readable medium that is executable by a processing element. "Memory" includes any mechanism that provides (i.e., stores and / or transmits) information in a form readable by a machine, 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 devices, electrical storage devices, optical storage devices, acoustic storage devices, 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).

[0069] References throughout this specification to "one embodiment" or "an embodiment" mean that a particular feature, structure, or characteristic described in connection with that embodiment is included in at least one embodiment of the present disclosure. Thus, the appearances of the phrase "in one embodiment" or "in an embodiment" in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0070] In the foregoing specification, a detailed description has been given with reference to certain exemplary embodiments. However, it will be apparent that various modifications and changes may be made thereto without departing from the broader spirit and scope of the present disclosure as set forth in the appended claims. Accordingly, the specification and drawings should be considered in an illustrative rather than a restrictive sense. Furthermore, the above use of embodiment and / or other exemplary language does not necessarily refer to the same embodiment or the same example, but may refer to different and separate embodiments, as well as potentially the same embodiment.

[0071] The word "example" or "exemplary" is used herein to mean serving as an example, instance, or illustration. Any aspect or design described herein as "example" or "exemplary" is not necessarily to be construed as preferred or advantageous over other aspects or designs. Rather, use of the word "example" or "exemplary" is intended to present concepts in a concrete manner. As used herein, the term "or" is intended to mean an inclusive "or" rather than an exclusive "or." That is, unless otherwise specified or clear from the context, "X includes A or B" is intended to mean any of the natural inclusive permutations. That is, if X includes A, X includes B, or X includes both A and B, then "X includes A or B" is satisfied under any of the above cases. Furthermore, the articles "a" and "an," as used in this application and the appended claims, should generally be construed to mean "one or more" unless otherwise specified or clear from the context that the singular form is intended. Moreover, use of the terms "an embodiment" or "one embodiment" throughout does not refer to the same embodiment or example unless described as such. Also, the terms "first," "second," "third," "fourth," etc., as used herein are meant as labels to distinguish between different elements and do not necessarily have any ordering meaning according to their numerical designations.

Claims

1. scanning the substrate with a first light beam; obtaining, for each of a plurality of locations on the substrate, a respective one of a first plurality of intensity values ​​associated with a second light beam, the second light beam obtaining a respective one of the first plurality of intensity values ​​caused by an interaction of the first light beam with the substrate; using the first plurality of intensity values ​​to determine profile data characterizing thickness variations of the substrate; and A method comprising:

2. the first plurality of intensity values ​​associated with the second light beam; a first intensity value for a first location of the plurality of locations; a second intensity value for a second location of the plurality of locations; and Including, determining the profile data Using the first intensity value and the second intensity value to determine a change in the thickness of the substrate between the first location and the second location. The method of claim 1 , comprising:

3. scanning the substrate with a third light beam, the third light beam differing from the first light beam in at least one of wavelength or angle of incidence on the substrate; obtaining, for at least some of the plurality of locations on the substrate, respective ones of a second plurality of intensity values ​​associated with a fourth light beam, the fourth light beam being caused by an interaction of the third light beam with the substrate; further comprising determining the profile data is further based on the second plurality of intensity values; The method of claim 1.

4. The first plurality of intensity values ​​is: a first group of interference fringes for a first region of the substrate; a second group of interference fringes for a second region of the substrate; and Identify the The second plurality of intensity values ​​is: a third group of interference fringes for the first region of the substrate; and a fourth group of interference fringes for a second region of the substrate; and Identify the Determining the profile data includes: identifying that a relative spatial order of the first group of interference fringes and the third group of interference fringes is different from a relative spatial order of the second group of interference fringes and the fourth group of interference fringes; Based on the identifying, the thickness of the substrate is: In the first region, the density is increasing in the direction of scanning; a decrease in the second region in the direction of scanning; and determining The method of claim 3, comprising:

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

6. 2. The method of claim 1, wherein the second light beam is a reflected beam caused by interaction of the first light beam with the substrate, and each of the first plurality of intensity values ​​is related to the reflectivity of the substrate at a respective one of the plurality of locations on the substrate.

7. 2. The method of claim 1, wherein the second light beam is a transmitted beam caused by interaction of the first light beam with the substrate, and each of the first plurality of intensity values ​​is related to the transmittance of the substrate at a respective one of the plurality of locations on the substrate.

8. 2. The method of claim 1, further comprising determining that the thickness of a region of the substrate is uniform based on subsets of the first plurality of intensity values ​​being equal within a target accuracy, each of the subsets of the first plurality of intensity values ​​obtained for the region of the substrate.

9. scanning the substrate with the first light beam; drying at least a portion of the substrate with a gas flow; The method of claim 1 , comprising:

10. modifying the thickness of the substrate in at least one region of the substrate in view of the determined profile data. The method of claim 1 further comprising:

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

12. 1. 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 respective one of a first plurality of intensity values ​​associated with a second optical beam, the second optical beam being caused by an interaction of the first optical beam with the substrate; a processing device for determining profile data characterizing thickness variations of the substrate using the first plurality of intensity values; A system comprising:

13. a second light source for emitting a third light beam for scanning the first area and the second area of ​​the substrate; detecting, for at least some of the plurality of locations of the first region, a respective one of a second plurality of intensity values ​​associated with a fourth light beam, the fourth light beam detecting a respective one of the second plurality of intensity values ​​caused by an interaction of the third light beam with the first region of the substrate; outputting the profile data further based on the plurality of intensity values; a second optical sensor for performing The system of claim 12 further comprising:

14. The first plurality of intensity values ​​is: a first group of interference fringes for a first region of the substrate; a second group of interference fringes for a second region of the substrate; and Identify the The second plurality of intensity values ​​is: a third group of interference fringes for the first region of the substrate; and a fourth group of interference fringes for a second region of the substrate; and Identify the The outputting of the profile data includes: identifying that a relative spatial order of the first group of interference fringes and the third group of interference fringes is different from a relative spatial order of the second group of interference fringes and the fourth group of interference fringes; Based on the identifying, the thickness of the substrate is: In the first region, the density is increasing in the direction of scanning; a decrease in the second region in the direction of scanning; and determining The system of claim 13 , comprising:

15. 14. The system of claim 13, further comprising a beam splitter, wherein the second light source and the first light source are the same, and an angle of incidence of the third light beam on the substrate is different from an angle of incidence of the first light beam on the substrate.

16. 14. The system of claim 13, wherein the second light source and the first light source are different and the wavelength of the third light beam is different from the wavelength of the first light beam.

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

18. The system of claim 12 further comprising a directional gas source for drying at least a portion of the substrate with a gas flow.

19. 13. The system of claim 12, further comprising a substrate processing tool configured to modify the thickness of the substrate, wherein the processing device is further for applying a machine learning model to the first plurality of intensity values ​​to determine adjusted tool settings for the substrate processing tool.

20. a movable stage for supporting the substrate; a light source for directing a first light beam to scan the substrate being transported on the movable stage; a first optical sensor for obtaining, for each of a plurality of locations on the substrate, a respective one of a first plurality of intensity values ​​associated with a second optical beam, the second optical beam being caused by an interaction of the first optical beam with the substrate; a processing device communicatively coupled to the first optical sensor for generating profile data characterizing thickness variations of the substrate; and A system comprising:

21. 21. The system of claim 20, further comprising at least one of a deposition device, an etching device, or a polishing device configured to adjust a thickness of at least one of the plurality of locations of the substrate based on the profile data.

22. 22. The system of claim 21, wherein a device control parameter of the at least one of the deposition device, the etching device, or the polishing device is controlled to adjust the thickness of the substrate.

23. 22. The system of claim 21, wherein the polishing device is a chemical mechanical polishing (CMP) device.

24. 21. The system of claim 20, wherein the movable stage comprises at least one of i) a robot blade or ii) a polishing device capable of adjusting the thickness of at least one of the plurality of locations of the substrate.

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