Method for analyzing uniformity for semiconductor manufacturing and associated apparatus and system

Abstract

The invention relates to a method for analyzing uniformity of substrate processing for semiconductor manufacturing and related equipment and system. In one or more embodiments, non-uniformities are indicated, and the non-uniformities are temperature non-uniformities and / or physical non-uniformities. In one or more embodiments, a signal profile is accepted or rejected. In one or more embodiments, a method of analyzing uniformity of substrate processing suitable for semiconductor manufacturing includes heating an interior volume of a processing chamber using a target value. The method includes rotating the substrate support and scanning the sensor across one or more segments while rotating the substrate support to acquire a plurality of readings. The method includes generating a signal profile including a plurality of readings, and analyzing the signal profile by comparing the signal profile to a range.

Description

Background Technology field

[0001] This disclosure relates to methods, related equipment, and systems for analyzing the uniformity of substrate processing in semiconductor manufacturing. Related technical descriptions

[0002] Semiconductor substrates are processed for a wide variety of applications, including the fabrication of integrated devices and microdevices. One method of processing a substrate involves depositing a material, such as a semiconductor material or a conductive material, on the upper surface of the substrate. For example, epitaxy is a deposition process that deposits films of various materials on the surface of a substrate within a processing chamber. During processing, various parameters can affect the uniformity of the material deposited on the substrate. For example, temperature nonuniformity and / or physical nonuniformity can affect deposition uniformity. As an example, the temperature of the substrate and / or the temperature of the processing chamber components can affect deposition uniformity. As another example, stress and / or warpage of the substrate can cause temperature nonuniformity and / or deposition nonuniformity. Stress and / or warpage can also cause performance degradation and may lead to breakage.

[0003] Non-uniformity may be difficult to detect, and non-uniformity can lead to processing delays, substrate waste, and reduced throughput.

[0004] Therefore, there is a need for improved methods, equipment, and systems for analyzing uniformity. Summary of the Invention

[0005] This disclosure relates to methods, related apparatus, and systems for analyzing the uniformity of substrate processing in semiconductor manufacturing. In one or more embodiments, non-uniformity is indicated, and the non-uniformity is temperature non-uniformity and / or physical non-uniformity.

[0006] In one or more embodiments, a method for analyzing the uniformity of a substrate processing step in semiconductor manufacturing includes heating the internal volume of a processing chamber using a target value. The method includes rotating a substrate support and, while rotating the substrate support, causing a sensor to scan across one or more segments to acquire multiple readings. The method includes generating a signal profile comprising the multiple readings and analyzing the signal profile by comparing it to a range.

[0007] In one or more embodiments, a non-transitory computer-readable medium suitable for semiconductor manufacturing includes instructions that, when executed, cause a plurality of operations to be performed. The plurality of operations includes analyzing a signal profile by comparing it to a range. The range is less than 10% of a target value. The analysis includes identifying signal differences in the signal profile and determining whether the signal differences are within or outside the range. The plurality of operations includes, if the signal differences are outside the range, performing one or more of the following: indicating process non-uniformity, or rejecting the signal profile.

[0008] In one or more embodiments, a system for processing a substrate and suitable for semiconductor manufacturing includes: a chamber body including one or more sidewalls; and a window. The one or more sidewalls and the window at least partially define an internal volume. The system includes: one or more heat sources configured to heat the internal volume; a substrate support disposed within the internal volume; and a sensor configured to sense parameters within the internal volume. The system includes a controller including instructions that, when executed, cause a plurality of operations. The plurality of operations includes generating a signal profile comprising a plurality of readings. The plurality of operations includes analyzing the signal profile by comparing it to a range. The range is less than 10% of a target value. The analysis includes identifying signal differences in the signal profile and determining whether the signal difference is within or outside the range. The plurality of operations includes: if the signal difference is outside the range, performing one or more of the following: indicating process non-uniformity, or rejecting the signal profile. Attached Figure Description

[0009] To gain a more detailed understanding of the features described above in this disclosure, a more specific description of the disclosure briefly outlined above can be obtained by referring to the embodiments, some of which are illustrated in the accompanying drawings. However, it should be noted that the drawings illustrate exemplary embodiments only and should not be considered as limiting their scope, and other equally effective embodiments are appreciated.

[0010] Figure 1 This is a schematic side cross-sectional view of a processing chamber according to one or more embodiments.

[0011] Figure 2 For cross according to one or more embodiments Figure 1 A schematic side view of the uniformity profile of the substrate and / or substrate support shown.

[0012] Figure 3 This is a schematic block diagram of a method for analyzing the uniformity of substrate processing suitable for semiconductor manufacturing, according to one or more embodiments.

[0013] Figure 4This is a schematic block diagram of a method for analyzing the uniformity of substrate processing suitable for semiconductor manufacturing, according to one or more embodiments.

[0014] Figure 5 According to one or more embodiments Figure 3 The method shown and Figure 4 A schematic flowchart illustrating an exemplary implementation of the method shown.

[0015] Figure 6 For the processing chamber according to one or more embodiments in Figure 3 A schematic top view of the operation of the method shown.

[0016] Figure 7 For use according to one or more embodiments Figure 6 A schematic diagram of an exemplary signal profile generated by the implementation shown.

[0017] Figure 8 For the processing chamber according to one or more embodiments in Figure 3 A schematic top view of the operation of the method shown.

[0018] Figure 9 This is based on the use of one or more embodiments. Figure 8 The schematic diagram of the exemplary first and second signal profiles generated by the implementation shown is shown.

[0019] For ease of understanding, the same element symbols have been used where possible to denote the same elements common to all figures. It is contemplated that elements and features of one embodiment may be beneficially incorporated into other embodiments without further description. Detailed Implementation

[0020] This disclosure relates to methods, related apparatus, and systems for analyzing the uniformity of substrate processing in semiconductor manufacturing. In one or more embodiments, non-uniformity is indicated, and the non-uniformity is temperature non-uniformity and / or physical non-uniformity. In one or more embodiments, signal profiles are accepted or rejected.

[0021] This disclosure envisions that terms such as “couples,” “coupling,” “couple,” and “coupled” may include, but are not limited to, welding, fusion, melting together, interference fit, and / or fastening achieved through the use of bolts, threaded connections, pins, and / or screws. This disclosure envisions that terms such as “couples,” “coupling,” “couple,” and “coupled” may include, but are not limited to, integrally formed. This disclosure envisions that terms such as “couples,” “coupling,” “couple,” and “coupled” may include, but are not limited to, direct coupling and / or indirect coupling, such as indirect coupling through components such as links, blocks, and / or frames.

[0022] Figure 1 This is a schematic side cross-sectional view of a processing chamber 100 according to one or more embodiments. The processing chamber 100 is a deposition chamber. In one or more embodiments, the processing chamber 100 is an epitaxial deposition chamber. The processing chamber 100 is used to grow an epitaxial film on a substrate 102. The processing chamber 100 generates a precursor crossflow across the top surface 150 of the substrate 102. Figure 1 The image shows a processing chamber 100 under processing conditions.

[0023] The processing chamber 100 includes an upper body 156, a lower body 148 disposed below the upper body 156, and a flow module 112 disposed between the upper body 156 and the lower body 148. The upper body 156, the flow module 112, and the lower body 148 form the chamber body. Disposed within the chamber body are a substrate support 106, an upper window 108 (such as an upper dome), a lower window 110 (such as a lower dome), a plurality of upper heat sources 141, and a plurality of lower heat sources 143. In one or more embodiments, the upper heat source 141 includes an upper lamp, and the lower heat source 143 includes a lower lamp. This disclosure contemplates that other heat sources may be used (as an addition to or alternative to the lamps) of the various heat sources described herein. For example, resistance heaters, light-emitting diodes (LEDs), and / or lasers may be used of the various heat sources described herein.

[0024] A substrate support 106 is disposed between the upper window 108 and the lower window 110. The substrate support 106 supports the substrate 102. In one or more embodiments, the substrate support 106 includes a base. This disclosure contemplates other substrate supports (including, for example, a substrate carrier and / or one or more annular segments supporting one or more outer regions of the substrate 102). A plurality of upper heat sources 141 are disposed between the upper window and the cover 154. The plurality of upper heat sources 141 form part of the upper heat source module 155.

[0025] Multiple lower heat sources 143 are disposed between the lower window 110 and the base plate 152. The multiple lower heat sources 143 form part of the lower heat source module 145. The upper window 108 is an upper dome and / or formed of an energy-transmitting material such as quartz. The lower window 110 is a lower dome and / or formed of an energy-transmitting material such as quartz.

[0026] Upper volume 136 and purification volume 138 are formed between upper window 108 and lower window 110. Upper volume 136 and purification volume 138 are at least part of an internal volume defined by upper window 108, lower window 110 and one or more liners 111, 163. In one or more embodiments, upper volume 136 is a processing volume.

[0027] A substrate support 106 is disposed within the internal volume. The substrate support 106 includes a top surface on which a substrate 102 is disposed. The substrate support 106 is attached to a shaft 118. In one or more embodiments, the substrate support 106 is connected to the shaft 118 via one or more arms 119 connected to the shaft 118. The shaft 118 is connected to a motion assembly 121. The motion assembly 121 includes one or more actuators and / or adjustment devices that provide movement and / or adjustment of the shaft 118 and / or the substrate support 106 within the upper volume 136.

[0028] The substrate support 106 may include lifting rod holes 107 disposed therein. Each lifting rod hole 107 is sized to accommodate a lifting rod 132 for lifting the substrate 102 from the substrate support 106 before or after a deposition process. When the substrate support 106 descends from a processing position to a transport position, the lifting rod 132 is reliably secured to a lifting rod stop 134. The lifting rod stop 134 may include a plurality of arms 139 attached to a shaft 135.

[0029] The flow module 112 includes one or more gas inlets 114 (e.g., multiple gas inlets), one or more purge gas inlets 164 (e.g., multiple purge gas inlets), and one or more exhaust outlets 116. The one or more gas inlets 114 and the one or more purge gas inlets 164 are disposed on opposite sides of the flow module 112 relative to the one or more exhaust outlets 116. A preheating ring 117 is disposed below the one or more gas inlets 114 and the one or more exhaust outlets 116. The preheating ring 117 is disposed above the one or more purge gas inlets 164. One or more liners 111, 163 are disposed on the inner surface of the flow module 112 and protect the flow module 112 from the reactive gases used during deposition and / or cleaning operations. The gas inlets 114 and the purge gas inlets 164 are each positioned such that a corresponding one or more process gases P1 and one or more purge gases P2 flow parallel to the top surface 150 of the substrate 102 disposed within the upper volume 136. The gas inlets 114 are fluidly connected to one or more process gas sources 151 and one or more cleaning gas sources 153. A purified gas inlet 164 is fluidly connected to one or more purified gas sources 162. One or more exhaust outlets 116 are fluidly connected to an exhaust pump 157. One or more process gases P1 supplied using one or more process gas sources 151 may include one or more reactive gases (such as one or more of silicon (Si), phosphorus (P), and / or germanium (Ge)) and / or one or more carrier gases (such as one or more of nitrogen (N2) and / or hydrogen (H2)). One or more purified gases P2 supplied using one or more purified gas sources 162 may include one or more inert gases (such as one or more of argon (Ar), helium (He), and / or nitrogen (N2)). One or more clean gases supplied using one or more clean gas sources 153 may include one or more of hydrogen (H) and / or chlorine (Cl). In one or more embodiments, one or more process gases P1 include silicon phosphide (SiP) and / or phosphine (PH3), and one or more clean gases include hydrochloric acid (HCl).

[0030] One or more exhaust outlets 116 are further connected to or include an exhaust system 178. The exhaust system 178 is fluidly connected to one or more exhaust outlets 116 and an exhaust pump 157. The exhaust system 178 may assist in the controlled deposition of a layer on the substrate 102. The exhaust system 178 is located on the opposite side of the processing chamber 100 relative to the flow module 112.

[0031] Processing chamber 100 includes one or more liners 111, 163 (e.g., lower liner 111 and upper liner 163). Flow module 112 (which may be at least a portion of the sidewall of processing chamber 100) includes one or more gas inlets 114 in fluid communication with the upper volume 136. The one or more gas inlets 114 are in fluid communication with one or more flow gaps between the upper liner 163 and the lower liner 111. One or more second gas inlets 175 are in fluid communication with one or more inlet openings 183 of the upper liner 163.

[0032] During a deposition operation (e.g., an epitaxial growth operation), one or more processing gases P1 flow through one or more gas inlets 114, through one or more gaps, and into the upper volume 136 to flow over the substrate 102.

[0033] This disclosure also envisions that, during deposition operations, one or more purge gases P2 may be supplied to and discharged from the purge volume 138 (through one or more purge gas inlets 164). The flow of one or more purge gases P2 occurs simultaneously with the flow of one or more process gases P1. The one or more process gases P1 are discharged through the gap between the upper liner 163 and the lower liner 111 and through one or more exhaust outlets 116. The one or more purge gases P2 may be discharged through one or more outlet openings and through one or more exhaust outlets 116 identical to those of the one or more process gases P1. This disclosure also envisions that one or more purge gases P2 may be discharged separately through one or more second exhaust outlets, separate from the one or more exhaust outlets 116.

[0034] During the cleaning operation, one or more cleaning gases flow through one or more gas inlets 114, through one or more gaps (between the upper liner 163 and the lower liner 111), and into the upper volume 136.

[0035] The processing system includes one or more sensors 195, 196, 197, 198 (e.g., temperature sensors) configured to measure parameters (e.g., temperature) within the processing chamber 100. In one or more embodiments, the one or more temperature sensors 195, 196, 197, 198 include a central sensor 196 and one or more external sensors 195, 197, 198. A controller 190 (as described below) can control the one or more sensors 195, 196, 197, 198 and can use at least one of the one or more sensors 195, 196, 197, 198 to perform a method for analyzing the uniformity of the substrate processing. In one or more embodiments, each of the one or more sensors 195, 196, 197, 198 includes a pyrometer, such as a pyrometer including a silicon sensor. In one or more embodiments, each sensor 195, 196, 197, 198 is an optical sensor, such as an optical pyrometer. This disclosure envisions the use of sensors other than pyrometers, and / or one or more of sensors 195, 196, 197, and 198 that can measure properties other than temperature.

[0036] In one or more embodiments, one or more sensors 195, 196, 197, 198 include one or more upper sensors 196, 197, 198 and one or more lower sensors 195, the upper sensors being disposed above the substrate 102 and adjacent to the cover 154, and the lower sensors being disposed below the substrate 102 and adjacent to the base plate 152. This disclosure contemplates that at least one of the one or more lower sensors 195 may be vertically aligned below at least one of the upper sensors 196, 197 (such as the outer sensor 197).

[0037] Each sensor 195, 196, 197, 198 may be a single-wavelength sensor device or a multi-wavelength (such as a dual-wavelength) sensor device. In one or more embodiments, the system including the processing chamber 100 includes any one, two, or three of the four illustrated sensors 195, 196, 197, 198. In one or more embodiments, in addition to sensors 195, 196, 197, 198, the processing chamber 100 may also include one or more additional sensors. In one or more embodiments, the processing chamber 100 may include sensors disposed at locations different from and / or in orientations different from those of the illustrated sensors 195, 196, 197, 198.

[0038] As shown in the figure, the controller 190 communicates with the processing chamber 100 and is used to control the operation of processes and methods, such as those described herein.

[0039] The controller 190 is configured to receive data or inputs as sensor readings from sensors, such as one or more of sensors 195, 196, 197, and 198. Sensors may include, for example, sensors monitoring the growth of layers on substrate 102 and / or sensors monitoring the temperature of substrate 102, substrate support 106, and / or liners 111 and 163. The controller 190 is equipped with or communicates with a system model of the processing chamber 100. The system model includes a heating model, a temperature uniformity model, a film uniformity model, a film deposition rate model, a coating model, a rotational position model, and / or a gas flow model. The system model is a program configured to estimate parameters within the processing chamber 100, such as signal profiles (e.g., temperature profiles) of substrate 102 and / or substrate support 106, gas flow rates, gas pressures, component rotational positions, heating profiles, coating conditions, and / or cleaning conditions, throughout the deposition and / or cleaning operations. The controller 190 is further configured to store readings and perform calculations. The readings and calculations include previous sensor readings, such as any previous sensor readings within the processing chamber 100. The readings and calculations further include calculated values ​​stored after the sensor readings are measured by the controller 190 and processed through the system model. Therefore, the controller 190 is configured to perform both: retrieve stored readings and calculations, and save readings and calculations for future use. Maintaining previous readings and calculations allows the controller 190 to adjust the system model over time to reflect a more accurate version of the processing chamber 100.

[0040] The controller 190 can monitor heating, generate signal profiles (e.g., temperature profiles), indicate process non-uniformity, accept or reject signal profiles, estimate optimized parameters, adjust one or more sensors, generate alarms on a display, abort deposition operations, initiate chamber downtime, delay subsequent iterations of deposition operations, initiate cleaning operations, abort cleaning operations, adjust heating power, and / or otherwise adjust process formulations.

[0041] Controller 190 includes a central processing unit (CPU) 193 (e.g., a processor), a memory 191 containing instructions, and support circuitry 192 for CPU 193. Controller 190 controls various items directly or via other computers and / or controllers. In one or more embodiments, controller 190 is communicatively coupled to a dedicated controller, and controller 190 functions as a central controller.

[0042] Controller 190 is any form of general-purpose computer processor used to control various substrate processing chambers and devices and their subprocessors in or within them in an industrial environment. Memory 191 or non-transitory computer-readable medium is one or more of the following: readily available memory (such as random access memory (RAM), dynamic random access memory (DRAM), static RAM (SRAM), and synchronous dynamic RAM (SDRAM) (e.g., DDR1, DDR2, DDR3, DDR3L, LPDDR3, DDR4, LPDDR4, etc.), read-only memory (ROM), floppy disk, hard disk, flash drive, or any other form of local or remote digital storage device. Support circuitry 192 of controller 190 is coupled to CPU 193 to support CPU 193. Support circuitry 192 includes cache, power supply, clock circuitry, input / output circuitry systems, and subsystems, etc. Operating parameters (e.g., target values, readings, signal difference, signal profile, ranges compared to the signal difference and / or training ranges, heating power applied to heat sources 141, 143, cleaning formulas and / or treatment formulas) and operations are stored as software routines in memory 191. These software routines are executed or invoked to transform controller 190 into a dedicated controller to control the operation of the various chambers / modules described herein. Controller 190 is configured to perform any of the operations described herein. Instructions stored in memory, when executed, cause method 300, method 400, etc., to be performed with respect to processing chamber 100. Figure 5 , Figure 6 and / or Figure 8 One or more operations in the operation. The controller 190 and the processing chamber 100 are at least part of a system for processing the substrate.

[0043] The various operations described in this document (such as method 300, method 400, etc.) Figure 5 , Figure 6 and / or Figure 8 The operation can be performed automatically by the controller 190, or it can be performed automatically or manually by certain operations performed by the user.

[0044] In one or more embodiments, controller 190 includes a large-capacity storage device, an input control unit, and a display unit. Controller 190 can monitor the temperature of substrate 102, the temperature of substrate support 106, the flow rate of processed gas, and / or the flow rate of purified gas. In one or more embodiments, controller 190 includes a plurality of controllers 190 such that stored readings and calculations, as well as system models, are stored in a controller of controller 190 independent of the operation of the control chamber 100. In one or more embodiments, all system models and stored readings and calculations are stored in controller 190.

[0045] The controller 190 is configured to control the deposition, cleaning, rotational position, heating and airflow through the processing chamber 100 by providing outputs to controls of sensors 195, 196, 197, 198, upper heat source 141, lower heat source 143, processing air source 151, purified air source 162, motion device 121 and / or exhaust pump 157.

[0046] Controller 190 is configured to adjust the output to the control based on sensor readings, a system model, and stored readings and calculations. Controller 190 includes embedded software and compensation algorithms to calibrate measurements. Controller 190 may include one or more machine learning algorithms and / or artificial intelligence algorithms that estimate optimized parameters for uniformity analysis operations, deposition operations, and / or cleaning operations.

[0047] One or more machine learning algorithms and / or artificial intelligence algorithms may implement, adjust, and / or improve one or more of the algorithms, inputs, outputs, or variables described above. Additionally or alternatively, one or more machine learning algorithms and / or artificial intelligence algorithms may rank or prioritize certain aspects of adjustments to processing chamber 100 and / or methods (such as methods 300, 400) relative to other aspects of processing chamber 100 and / or methods (such as methods 300, 400). One or more machine learning algorithms and / or artificial intelligence algorithms may take into account other changes within the processing system, such as hardware replacement and / or degradation. In one or more embodiments, one or more machine learning algorithms and / or artificial intelligence algorithms take into account upstream or downstream changes that may occur in the processing system due to changes in variables of processing chamber 100 and / or methods (such as methods 300, 400). For example, if variable “A” is adjusted to cause a change in aspect “B” of the process, and this adjustment unintentionally causes a change in aspect “C” of the process, one or more machine learning algorithms and / or artificial intelligence algorithms may take into account this change in aspect “C”. In this embodiment, one or more machine learning algorithms and / or artificial intelligence algorithms embody predictive aspects related to the implementation of processing chamber 100 and / or methods (such as methods 300, 400). These predictive aspects can be used to proactively mitigate unintended changes within the processing system.

[0048] One or more machine learning and / or artificial intelligence algorithms may be used, for example, regression models (such as linear regression models) or clustering techniques to estimate optimization parameters. The algorithm may be unsupervised or supervised. One or more machine learning and / or artificial intelligence algorithms may be used to optimize, for example, parameters such as target values, readings, signal differences, signal profiles, ranges compared to the signal differences and / or training ranges, heating power applied to heat sources 141, 143, cleaning formulations and / or treatment formulations.

[0049] In one or more embodiments, controller 190 performs the operations described herein automatically without using one or more machine learning algorithms and / or artificial intelligence algorithms. In one or more embodiments, controller 190 compares measurements (such as readings and / or signal differences) with data in lookup tables and / or libraries to indicate process non-uniformity and / or accept or reject signal profiles. Controller 190 may store measurements as data in lookup tables and / or libraries.

[0050] Figure 2 For cross according to one or more embodiments Figure 1 A schematic side view of the uniformity profile 200 of the substrate 102 and / or substrate support 106 shown. As shown, the uniformity profile 200 may include one or more process non-uniformities across a direction parallel to the diameter of the substrate 102 and / or the diameter of the substrate support 106.

[0051] Figure 3 This is a schematic block diagram of a method 300 for analyzing the uniformity of a substrate processing for semiconductor manufacturing, according to one or more embodiments.

[0052] Operation 302 of method 300 includes heating the internal volume of the processing chamber using a target value. The target value may be preset, for example, by a user and / or by a controller 190. In one or more embodiments, the target value described herein is a target temperature. In one or more embodiments, the target temperature is in the range of 400°C to 550°C. In one or more embodiments, the target temperature is in the range of 700°C to 800°C.

[0053] Operation 304 includes a rotating substrate support.

[0054] Operation 306 includes causing a sensor to scan across one or more segments to acquire multiple readings while rotating a substrate support. In one or more embodiments, the sensor is a temperature sensor, and the multiple readings are multiple temperature readings. In one or more embodiments, the one or more segments are disposed along the substrate support or along a substrate positioned on the substrate support. The one or more segments extend along an azimuth angle and are disposed at one or more radial locations. In one or more embodiments, the multiple readings are acquired at a sampling frequency as the substrate support rotates at a rotational speed. The rotational speed is proportional to the sampling frequency. In one or more embodiments, the ratio is less than 0.1. In one or more embodiments, the ratio is 0.015 or less. In one or more embodiments, the ratio is 0.010 or less, such as in the range of 0.0025 to 0.0075. The sampling frequency is in the range of 1 Hz to 10 kHz. In one or more embodiments, the sampling frequency is in the range of 90 Hz to 110 Hz, such as about 100 Hz. In one or more embodiments, the rotational speed is in the range of 0.50 revolutions per second (e.g., rotations) to 0.55 revolutions per second, such as about 32 revolutions per minute. Readings are obtained at a rate of at least 100 data points per revolution of the substrate support. In one or more embodiments, the read rate is at least 200 data points per revolution, such as at least 400 data points per revolution, such as 600 or more data points per revolution. Other values ​​are contemplated for the rotational speed, sampling frequency, ratio, and / or read rate.

[0055] Operation 308 includes generating a signal profile containing multiple readings. In one or more embodiments, the signal profile is a temperature profile.

[0056] Operation 310 includes analyzing the signal profile by comparing it to a range. This analysis includes identifying signal differences within the signal profile and determining whether the signal difference is within or outside the range. In one or more embodiments, the signal difference is a temperature difference.

[0057] The identification of signal difference includes (in optional operation 311) determining the standard deviation of the signal profile, and the signal difference is the standard deviation.

[0058] Identifying the signal difference includes (in optional operation 312) identifying one or more peaks and one or more valleys of the signal profile. In one or more embodiments, the signal difference is the difference between one of the one or more peaks and an adjacent valley of the one or more valleys. An adjacent valley may be within one rotation of one of the one or more peaks. In one or more embodiments, the signal difference is the difference between the highest peak of the one or more peaks and the lowest valley of the one or more valleys.

[0059] In one or more embodiments, the field of view of the sensor is moved during the scanning of operation 306 such that one or more segments extend radially and the range is less than 10% of the target value of operation 302. In one or more embodiments, the range is 8% or less of the target value, such as 5% or less of the target value.

[0060] In one or more embodiments, the sensor’s field of view is substantially stationary during the scanning of operation 306, such that one or more segments extend in an arc (e.g., along the azimuth, such as circumferentially) and the range is less than 2.5% of the target value of operation 302. In one or more embodiments, the range is less than 1.0% of the target value, such as 0.8% or lower of the target value, for example, 0.5% or lower of the target value.

[0061] Operation 313 includes indicating process non-uniformity if the signal difference is outside the range. Process non-uniformity may indicate, for example, non-uniformity of the substrate (such as substrate 102) and / or substrate support (such as substrate support 106). Process non-uniformity may be non-uniformity of temperature or materials (such as component thickness of the substrate and / or substrate support, coating thickness of the substrate support (e.g., silicon carbide coated on graphite or reactive material from the process gas), machining defects of the substrate support, and / or surface roughness of the substrate support). Non-uniformity may be caused by insufficient and / or uneven cleaning. Process non-uniformity may be non-uniformity of the substrate shape caused by warping (e.g., bowing). Warping may be caused by, for example, uneven heating and / or properties of the substrate. This disclosure contemplates that process non-uniformity may indicate other non-uniformities. Non-uniformity may be caused by, for example, component placement (such as non-uniformity of the distance between the lifting rod 132 and substrate 102 and / or misalignment of substrate 102 relative to the center of substrate support 106). Non-uniformity can be caused by, for example, component corrosion (such as corrosion of the substrate support 106, such as corrosion of the coating on the substrate support 106) and / or component reactions (such as the reaction of process gas with the substrate support 106). Non-uniformity may also be caused by, for example, process drift (such as heat source drift).

[0062] Method 300 may use process non-uniformity (indicated at operation 313) to cause an action (e.g., automatically or by using an alarm generated to the user). The action may include, for example, initiating a chamber downtime, replacing a substrate support, adjusting the process formulation (such as a target value, e.g., a target temperature) and / or heating power, and / or marking the substrate for reprocessing (such as re-deposition).

[0063] As an addition to or alternative to operation 313, method 300 may include at operation 315 rejecting the signal profile if the signal difference is outside the range. As discussed below, signal profiles may be rejected with respect to training the model.

[0064] Information from method 300 (such as target values, readings, signal differences, signal profiles, and / or ranges) can be stored and tracked. In one or more embodiments, the data is analyzed and / or compared using averaging, derivatives, modeling, imaging, and / or other data analysis techniques. For example, one or more optical sensors can capture images, and the intensity of the images can be analyzed to detect readings (e.g., temperature readings).

[0065] This disclosure envisions that the methods described herein (such as method 300) may be performed during and / or before and / or after the deposition operation. For example, method 300 may be performed during a simulated process in the absence of substrate 102 in chamber 100.

[0066] Figure 4 This is a schematic block diagram of a method 400 for analyzing the uniformity of substrate processing in semiconductor manufacturing, according to one or more embodiments. In one or more embodiments, method 400 is part of a supervised machine learning algorithm that facilitates the training of a system (e.g., controller 190).

[0067] Operation 402 includes generating one or more first signal profiles of the substrate support. In one or more embodiments, the one or more first signal profiles are one or more first temperature profiles. Operation 402 may include operations 306 and 308 of method 300, and one or more segments of operation 306 are performed along the substrate support. Operation 402 may include, for example, the use of a lower sensor 195.

[0068] Operation 404 includes generating one or more second signal profiles of the substrate. In one or more embodiments, the one or more second signal profiles are one or more second temperature profiles. Operation 404 may include operations 306 and 308 of method 300, and one or more segments of operation 306 are performed along the substrate. Operation 402 may include, for example, using one or more upper sensors 196, 197, 198. The one or more segments of operation 404 are positioned at the same one or more radial locations as the one or more segments of operation 402.

[0069] Operation 406 includes analyzing one or more first signal contours and one or more second signal contours by comparing them to a training range. The training range may be the same as or different from the range of operation 310 (e.g., larger than the range of operation 310). Operation 406 may include one or more aspects of operation 310 of method 300.

[0070] If the corresponding signal difference (e.g., temperature difference) between each of the first and second signal profiles is within the training range, the corresponding signal profile is accepted at operation 408. If accepted, the corresponding signal profile may be included as part of the training data for the training model and may be included in, for example, a lookup table and / or a library. In one or more embodiments, acceptance at operation 408 includes marking the corresponding profile as accepted in the training model. The accepted label may be stored, for example, in a lookup table and / or a library. The accepted label may be applied to, for example, one or more corresponding components (such as a substrate and / or substrate support corresponding to the corresponding signal profile).

[0071] If the corresponding signal difference between each of the first and second signal contours is outside the training range, the corresponding signal contour is rejected at operation 410. If rejected, the corresponding signal contour may be omitted from the training data of the training model, and may also be omitted from, for example, a lookup table and / or library. In one or more embodiments, rejection at operation 410 includes marking the corresponding contour as rejected in the training model. The rejected label may be stored, for example, in a lookup table and / or library. The rejected label may be applied, for example, to one or more corresponding components (such as a substrate and / or substrate support corresponding to the corresponding signal contour).

[0072] In one or more embodiments, instead of merging, one or more first signal profiles and one or more second signal profiles are analyzed at operation 406. In one or more embodiments, one or more first signal profiles and one or more second signal profiles (e.g., generated by using simultaneously collected readings (e.g., temperature readings)) are merged into one or more merged profiles, which are analyzed at operation 406 and then accepted and / or rejected according to operation 408 and / or operation 410.

[0073] This disclosure envisions comparing a first signal profile of a substrate support and a second signal profile of the substrate with each other. For example, when a substrate is placed on a substrate support, a first signal profile of the substrate support (e.g., a first temperature profile) is generated, and a second signal profile of the substrate (e.g., a second temperature profile) is generated. An increase in the first signal profile of the substrate support (e.g., a temperature increase) and a decrease in the second signal profile of the substrate (e.g., a temperature decrease) when regions corresponding to the substrate appear can indicate that the substrate warps (e.g., bends) when placed on the substrate support, and these regions are areas where the substrate is spaced apart from the substrate support. Similarly, a decrease in the first signal profile of the substrate support (e.g., a temperature decrease) and an increase in the second signal profile of the substrate (e.g., a temperature increase) when regions corresponding to the substrate appear can indicate that the substrate warps (e.g., bends) when placed on the substrate support, and these regions are areas where the substrate contacts the substrate support.

[0074] This disclosure envisions that a training model used to train the systems and / or methods described herein may involve the generated film thickness readings and associated film thickness profiles. The film thickness readings may be acquired during and / or after processing. The film thickness profile may be analyzed instead of the temperature profile described above, or the film thickness profile may be combined with the temperature profile described above, such that the data are combined (e.g., averaged) at the same location along the substrate. This disclosure envisions that the training model used to train the systems and / or methods described herein may be at least partially unsupervised. For example, the training model may take into account the film thickness profile measured on the substrate after processing the substrate.

[0075] This disclosure envisions that the readings described herein (unitless) can be analyzed before being correlated with measurements having certain units. For example, the reading acquired at operation 306 may be a unitless value and / or may be used to generate a signal profile (at operation 308) and analyze the signal profile (at operation 310) before correlating the reading with a temperature measurement having units such as Celsius or Fahrenheit (using the emissivity of the substrate and / or substrate support). For example, the reading may be a measured intensity.

[0076] Figure 5 According to one or more embodiments Figure 3 Method 300 and shown Figure 4 A schematic flowchart illustrating an exemplary implementation of method 400.

[0077] Operation 502 includes generating an initial signal profile (e.g., an initial temperature profile) using one or more sensors (e.g., a temperature sensor), and graph 503 shows a portion of a signal profile 504 (e.g., a temperature profile) over time using readings (e.g., temperature readings) of data collected during the initial signal profile generation. This time may be the time spent by one or more sensors scanning across one or more segments. Performing operation 502 may include, for example, operations 302, 304, 306, and 308 of method 300.

[0078] Operation 508 includes generating additional signal profiles 505 to 507 (e.g., temperature profiles) through multiple iterations across the curves shown in Figure 509 by performing operations 306 and 308 of method 300 once or more. A portion of signal profiles 505 to 507 is shown in Figure 509. For example, a more complete illustration of signal profiles 505 to 507 may include a sinusoidal pattern. Iterations may be, for example, multiple target values ​​(e.g., target temperatures), multiple radial locations of one or more segments, multiple deposition operations (which may be performed across multiple substrates), multiple substrate supports (which may be used to perform the multiple deposition operations), and / or multiple components of one or more segments (such as substrate 102 and substrate support 106).

[0079] Each signal profile 504 to 507 corresponds to one of multiple iterations. If the iteration is a target temperature, the target temperature can be achieved by applying multiple different bias power levels to heat sources 141, 143. Signal profiles 504 to 507 and / or associated readings (e.g., temperature readings) can be stored (e.g., in a library in memory). Signal profiles 504 to 507 can be generated at different times (e.g., on different dates) and may include process drift (e.g., sensor, heater drift, and / or substrate drift (e.g., due to erosion)).

[0080] Operation 510 includes merging signal profiles 504 to 507 (which may be stored in a library of memory) to produce a merged profile 511 as shown in graph 512 (a portion of the merged profile 511 is shown in graph 512). The merged profile 511 may be analyzed at operation 310 and may be used to determine whether process non-uniformity should be indicated. Merging may include averaging values ​​along signal profiles 504 to 507 (which may be linearly fitted), and the averaging may include a weighted average.

[0081] Operation 514 uses adjustment domain 515 to adjust the merged profile 511, as shown in graph 516. Adjustment domain 515 can be calculated and applied using a model, such as a model that includes one or more machine learning and / or artificial intelligence algorithms. This model can use other measurements, such as film thickness measurements performed on the treated substrate and / or the substrate being treated, to determine film uniformity and / or film deposition rate.

[0082] Figure 6 For the processing chamber 100 according to one or more embodiments in Figure 3 A schematic top view of method 300 during operations 302, 304 and 306.

[0083] The rotating substrate support 106 allows the field of view 602 of the sensor 197 to scan across one or more segments 604 of the substrate 102 and / or the substrate support 106. The field of view 602 remains substantially stationary during scanning, causing the one or more segments 604 to extend in an arcuate pattern (e.g., along an azimuth, such as circumferentially). For example, the substrate support 106 may undergo one or more complete rotations, allowing the one or more segments 604 to form a complete loop.

[0084] Figure 7 For use according to one or more embodiments Figure 6 A graphical view of an exemplary signal profile 701 generated by the implementation shown.

[0085] The signal profile 701 (e.g., a temperature profile) includes one or more peaks 711 to 715 and one or more valleys 721 to 725. As discussed above, analyzing the signal profile 701 may include identifying the highest peak 711 and the lowest valley 722. In one or more embodiments, the highest peak 711 indicates the maximum warpage (e.g., bowing) of the substrate, and / or the lowest valley 722 indicates the contact point between the substrate and a substrate support. In one or more embodiments, the highest peak 711 may indicate the contact point between the substrate and a substrate support, and / or the lowest valley 722 may indicate the maximum warpage (e.g., bowing) of the substrate.

[0086] Analyzing the signal profile 701 may include obtaining the standard deviation of the signal profile 701 (e.g., by obtaining the standard deviation under the signal profile 701). Arrow 705 indicates one complete rotation of the substrate support 106.

[0087] Figure 8 The processing chamber 100 according to one or more embodiments is in Figure 3 A schematic top view of method 300 during operations 302, 304 and 306.

[0088] The substrate support 106 is rotated such that the field of view 802 of the sensor 197 scans across one or more segments 804 of the substrate 102 and / or the substrate support 106. During scanning, the field of view 802 is moved (e.g., linearly, such as radially relative to the center of the substrate support 106 along the D1 direction), such that one or more segments 804 extend radially (e.g., in addition to along the azimuth). In one or more embodiments, the field of view 802 is scanned at least partially between the center of the substrate support 106 and the outer diameter 809. For example, the substrate support 106 may be rotated once or multiple times, such that one or more segments 804 may form a lobe shape (e.g., Figure 8 As shown). In one or more embodiments, by pivoting sensor 197 to multiple angular increments A1 (as shown). Figure 1(As shown) to move the field of view 802. This allows sensor 197 to pivot between collected data points by an angular increment A1. In one or more embodiments, the angular increment A1 between data points is less than 5 degrees, such as about 1.8 degrees. In one or more embodiments, pivoting creates a spacing between the collected data points. The spacing is less than 25 millimeters, such as about 10 millimeters.

[0089] Figure 9 For use according to one or more embodiments Figure 8 The illustrated implementation produces a schematic view of an exemplary first signal profile 901 and a second signal profile 951. In one or more embodiments, the first signal profile 901 is a first temperature profile, and the second signal profile 951 is a second temperature profile.

[0090] The first signal profile 901 includes one or more peaks 911 to 913 and one or more valleys 921 to 924.

[0091] The second signal profile 951 includes one or more peaks 961 to 964 and one or more valleys 971 to 974.

[0092] For both the first signal profile 901 and the second signal profile 951, arrow 905 indicates one complete rotation of the substrate support.

[0093] The first signal profile 901 includes a first signal difference DF1 (e.g., a first temperature difference), while the second signal profile 951 includes a second signal difference DF2 (e.g., a second temperature difference). As shown, the first signal difference DF1 is greater than the second signal difference DF2. This disclosure contemplates that the second signal difference DF2 may be within a range, while the first signal difference DF1 may be outside a range. In one or more embodiments, the first signal difference DF1 is directed to a first substrate support, while the second signal difference DF2 is directed to a second substrate support. In such embodiments, the second substrate support is acceptable for further use, and an alarm may be generated for maintenance and / or replacement of the first substrate support.

[0094] The benefits of this disclosure include accurate identification of non-uniformities; reduction, mitigation, or elimination of the use of certain corrective actions (such as preheating); reduced inefficiency; accurate initiation of maintenance and / or replacement of chamber components (such as substrate supports); accurate and efficient resolution of process drift (such as aging and wear of chamber components); accurate and efficient resolution of substrate warpage (e.g., bowing); adjustability of parameters (such as temperature, deposition uniformity, and / or deposition rate (e.g., in nanometers per minute)) under various operating conditions (such as low rotational speeds, high pressures, and / or low flow rates); a wider and / or more modular range of adjustability; and improved deposition uniformity and / or deposition rate. The benefits of this disclosure also include reduced substrate waste.

[0095] Further benefits of this disclosure include extended component life; reduced chamber downtime; reduced processing delays; and increased throughput. Benefits of this disclosure also include enhanced deposition repeatability and / or cleaning repeatability.

[0096] It is envisioned that one or more aspects disclosed herein can be combined. As an example, processing chamber 100, controller 190, one or more sensors 195, 196, 197, 198, method 300, method 400, etc. Figure 5 The exemplary implementation shown Figure 6 The exemplary implementation shown, signal profile 701, Figure 8 The exemplary implementations shown, one or more aspects, features, components, operations, and / or properties of the first signal profile 901 and / or the second signal profile 951 can be combined. For example, regarding Figure 5 , Figure 6 and / or Figure 8 The described operations and / or parameters may be combined with the operations and / or parameters of method 300 and / or method 400. Furthermore, it is contemplated that one or more aspects disclosed herein may include some or all of the foregoing benefits.

[0097] While the foregoing describes embodiments of this disclosure, other and further embodiments of this disclosure may be designed without departing from the basic scope of this disclosure, and the scope of this disclosure is defined by the appended claims.

Claims

1. A method for analyzing the uniformity of substrate processing in semiconductor manufacturing, the method comprising: The target value is used to heat the internal volume of the treatment chamber; Rotating substrate support; While rotating the substrate support, the sensor scans across one or more segments to obtain multiple readings; Generate a signal profile that includes the plurality of readings; as well as The signal profile is analyzed by comparing it to a range.

2. The method of claim 1, wherein the analysis comprises: Identify the signal difference in the signal profile; as well as Determine whether the signal difference is within or outside the range.

3. The method of claim 2, wherein the identification of the signal difference includes identifying one or more peaks and one or more valleys of the signal profile.

4. The method of claim 2, further comprising: If the signal difference is outside the range, then one or more of the following are performed: Indicator process non-uniformity; or The signal profile is rejected.

5. The method of claim 2, wherein the field of view of the sensor is substantially stationary during the scanning, such that the one or more segments extend along the azimuth angle, and the range is less than 2.5% of the target value.

6. The method of claim 2, wherein the field of view of the sensor moves during the scan such that the one or more segments extend radially, and the range is less than 10% of the target value.

7. The method of claim 2, wherein the identification of the signal difference comprises: Determine the standard deviation of the signal profile.

8. The method of claim 1, wherein: The one or more segments are positioned along the substrate support or along a substrate positioned on the substrate support; and The target value is the target temperature, the sensor is a temperature sensor, the multiple readings are multiple temperature readings, the signal difference is the temperature difference, and the signal profile is the temperature profile.

9. A non-transitory computer-readable medium suitable for semiconductor manufacturing, the non-transitory computer-readable medium comprising instructions that, when executed, cause a plurality of operations to be performed, the plurality of operations including: The signal profile is analyzed by comparing it to a range less than 10% of a target value, and the analysis includes: Identify the signal difference in the signal profile, and Determine whether the signal difference is within or outside the range; and If the signal difference is outside the range, then one or more of the following are performed: Indicator process non-uniformity, or The signal profile is rejected.

10. The non-transitory computer-readable medium of claim 9, wherein the plurality of operations further comprises: The signal profile is generated before analysis, and the signal profile includes multiple readings.

11. The non-transitory computer-readable medium of claim 10, wherein the plurality of operations further comprises: While rotating the substrate support at a rotational speed, the plurality of readings are acquired at a sampling frequency, wherein the rotational speed is proportional to the sampling frequency and the ratio is less than 0.

1.

12. The non-transitory computer-readable medium of claim 9, wherein the identification of the signal difference comprises identifying one or more peaks and one or more valleys of the signal profile.

13. The non-transitory computer-readable medium of claim 12, wherein the signal difference is the difference between one of the one or more peaks and an adjacent valley of the one or more valleys.

14. The non-transitory computer-readable medium of claim 13, wherein the adjacent valley is located within one rotation of one of the one or more peaks.

15. The non-transitory computer-readable medium of claim 12, wherein the signal difference is the difference between the highest peak of the one or more peaks and the lowest valley of the one or more valleys.

16. The non-transitory computer-readable medium of claim 9, wherein: The range is less than 2.5% of the target value; and The target value is the target temperature, the signal difference is the temperature difference, and the signal profile is the temperature profile.

17. The non-transitory computer-readable medium of claim 9, wherein the identification of the signal difference includes determining the standard deviation of the signal profile.

18. A system for processing a substrate and suitable for semiconductor manufacturing, the system comprising: The main body of the chamber includes one or more sidewalls; A window, wherein the one or more sidewalls and the window at least partially define an internal volume; One or more heat sources are configured to heat the internal volume; A substrate support member, wherein the substrate support member is disposed within the internal volume; The sensor is configured to sense parameters in the internal volume; as well as The controller includes instructions that, when executed, cause a plurality of operations to be performed, the plurality of operations including: A signal profile is generated, which includes multiple readings. The signal profile is analyzed by comparing it to a range less than 10% of a target value, and the analysis includes: Identify the signal difference in the signal profile, and Determine whether the signal difference is within or outside the range, and If the signal difference is outside the range, then one or more of the following are performed: Indicator process non-uniformity, or The signal profile is rejected.

19. The system of claim 18, wherein the plurality of operations further comprises: While rotating the substrate support at a rotational speed, the plurality of readings are acquired at a sampling frequency, wherein the rotational speed is proportional to the sampling frequency, and the ratio is 0.015 or less.

20. The system of claim 18, wherein the identification of the signal difference comprises: Determine the standard deviation of the signal profile.

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