Raman sensors for supercritical fluid measurements

Abstract

The apparatus includes a measurement chamber configured to hold one or more sample substances. The apparatus includes an entrance window mounted to one side of the measurement chamber. The apparatus includes a light source configured to generate an incident light beam. The apparatus includes a Raman sensor configured to collect inelastically scattered light from the chamber and measure an intensity of a Raman peak of a first substance from the one or more sample substances based on the collected inelastically scattered light. The apparatus further includes a processor configured to (i) calculate a concentration of the first substance based on at least the intensity of the measured Raman peak of the first substance, (ii) determine an endpoint of the wafer cleaning process based on the calculated concentration of the first substance, and (iii) terminate the wafer cleaning process based on the determined endpoint.

Description

[Technical Field]

[0001] Cross-references to related patents and applications This application claims priority to and the benefit of the filing date of U.S. Non-Provisional Patent Application No. 17 / 445,570, filed August 20, 2021, which is incorporated herein by reference in its entirety. [Background technology]

[0002] Wafer cleaning solutions are an important part of the semiconductor industry. Cleaning objectives include removing residual byproducts of other semiconductor process steps, such as etching. Professionals may also want to remove particles or unwanted films from the surface. Typically, cleaning processes use one or more solvents, such as SC-1 / SC-2 solutions (RCA clean), followed by rinsing the wafer with alcohol / isopropanol. At the end of the process, it is also important to remove any traces of remaining isopropanol (IPA) from the wafer surface. Otherwise, evaporation of the IPA can exert capillary forces on tool structures on the wafer surface, causing their collapse. Developed methods involve the use of agents that reduce the surface tension and the cleaning agent's ability to "wet" the surface. Ideally, professionals prefer agents with a surface tension approaching zero and the ability to turn into a gas without undergoing a phase transition. An example of the latter is supercritical carbon dioxide (CO2).

[0003] The development of wafer cleaning solutions for the semiconductor industry has led to the use of supercritical fluids to remove cleaning agents from wafer surfaces. The wafer is placed in a chamber where CO2, normally a gas, is exposed to pressures and temperatures above its critical point, transforming into a supercritical fluid state (scCO2). Most substances change into a gas when heated above a certain temperature. Similarly, gases change into liquids and / or solids when compressed above a certain pressure. However, some substances, such as carbon dioxide, change into so-called supercritical fluids, which have properties significantly different from those of liquids or gases, when exposed to pressures and temperatures above their so-called critical points. Most importantly, supercritical fluids can undergo a gradual transition to a gas or liquid without a sudden phase change. ScCO2 also has a very low viscosity, thus exerting minimal capillary forces on the wafer structure.

[0004] The scCO2 dissolves and displaces the cleaning agent (e.g., isopropanol (IPA)). The solution of IPA in the scCO2 can be removed through an exhaust port. At the end of the cleaning cycle, preferably, only pure scCO2 remains. The pressure in the chamber is then gradually reduced below the supercritical point until the CO2 gradually turns into a gas, leaving the wafer dry and preferably free of cleaning by-products.

[0005] An endpoint method and apparatus is needed for real-time in-situ tracking of the presence of cleaning agent residue in the drain of the cleaning chamber. Summary of the Invention [Means for solving the problem]

[0006] According to some embodiments, an apparatus for in-situ cleaning endpoint detection includes a measurement chamber configured to hold one or more sample substances. The apparatus further includes an entrance window attached to one side of the measurement chamber. The apparatus further includes a light source configured to generate an incident light beam, the incident light beam being directed into the chamber through the entrance window, and the incident light beam being inelastically scattered inside the chamber by the one or more sample substances. The apparatus further includes a Raman sensor configured to collect the inelastically scattered light from the chamber and measure the intensity of a Raman peak of a first substance from the one or more sample substances based on the collected inelastically scattered light. The apparatus further includes a processor configured to (i) calculate a concentration of the first substance from the one or more sample substances based on the intensity of at least the measured Raman peak of the first substance, (ii) determine an endpoint of the wafer cleaning process based on the calculated concentration of the first substance, and (iii) terminate the wafer cleaning process based on the determined endpoint.

[0007] According to some embodiments, a method for in-situ cleaning endpoint detection includes directing, by a light source, an incident light beam through an entrance window of a measurement chamber during a wafer cleaning process, the measurement chamber holding one or more sample substances, the incident light beam being inelastically scattered within the chamber by the one or more sample substances. The method further includes collecting, by a Raman sensor, the inelastically scattered light from the chamber. The method further includes measuring, by the Raman sensor, the intensity of a Raman peak of a first substance from the one or more sample substances based on the collected inelastically scattered light. The method further includes calculating, by a processor, a concentration of the first substance based on at least the measured Raman peak intensity of the first substance. The method further includes determining, by the processor, an endpoint of the wafer cleaning process based on the calculated concentration of the first substance. The method further includes terminating the wafer cleaning process based on the endpoint determined by the processor.

[0008] The above paragraphs have been provided by way of general introduction and are not intended to limit the scope of the claims that follow. The described embodiments, together with further advantages, will best be understood by reference to the following detailed description taken in connection with the accompanying drawings, in which:

[0009] Aspects of the present disclosure are best understood from the following detailed description when read in conjunction with the accompanying drawings. It should be noted that, according to standard industry practice, various features have not been drawn to scale. In fact, the dimensions of various features may be arbitrarily increased or decreased for clarity of discussion. [Brief explanation of the drawings]

[0010] [Figure 1] 1 shows an exemplary block diagram of a cleaning device, according to some embodiments. [Figure 2] 1 illustrates an exemplary Raman sensor, according to some embodiments. [Figure 3] 1 illustrates an exemplary Raman sensor, according to some embodiments. [Figure 4] 1 illustrates an exemplary cleaning apparatus, according to some embodiments. [Figure 5] 1 illustrates an exemplary mechanical structure of a cleaning device, according to some embodiments. [Figure 6] 1 shows an exemplary graph of Raman peaks of IPA, according to some embodiments. [Figure 7] 1 shows an exemplary graph of the relationship between IPA concentration and Raman peaks of IPA, according to some embodiments. [Figure 8] 1 shows an exemplary flowchart of a wafer cleaning process according to some embodiments. [Figure 9] 1 shows an exemplary flowchart of endpoint detection for a wafer cleaning process, according to some embodiments. [Figure 10] 1 illustrates an exemplary diagram of a processor, according to some embodiments. DETAILED DESCRIPTION OF THE INVENTION

[0011] The following disclosure presents various embodiments or examples for implementing various features of the presented subject matter. To simplify the disclosure, specific examples of components and configurations are described below. It should be understood that these are merely examples and are not intended to be limiting. In addition, the disclosure may repeat reference numerals and / or letters in the various examples. This repetition is for the purpose of simplicity and clarity and does not itself dictate a relationship between the various embodiments and / or configurations discussed.

[0012] Additionally, spatial relationship terms such as "lower," "below," "lower side," "upper," and "above" may be used herein to facilitate a description of the relationship of one element or feature to another, as shown. Spatial relationship terms are intended to encompass different orientations of the device during use or operation in addition to the orientation shown in the drawings. The device may be reoriented (rotated 90 degrees or at other orientations) and the spatial relationship descriptors used herein may be similarly interpreted accordingly.

[0013] Throughout this specification, the term "one embodiment" or "an embodiment" means that a particular feature, structure, material, or characteristic described in connection with that embodiment is included in at least one embodiment, but is not necessarily present in all embodiments. Thus, the appearances of the phrase "in one embodiment" in various places throughout this specification do not necessarily refer to the same embodiment. Furthermore, the particular features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments.

[0014] Existing sensors allow for tracking the state of the CO2 fluid. However, these sensors have limited sensitivity to the concentration of contaminants (e.g., IPA) in supercritical CO2 or similar fluids. Without an endpoint IPA tracking sensor, the cleaning tool must either continue to pump CO2 through the chamber until a sufficient margin is established or risk damage to the wafer if the cleaning process is stopped before the IPA is completely removed. Furthermore, if the cleaning process is stopped too early, the wafer may be subjected to a subsequent cleaning process, thereby reducing wafer processing throughput.

[0015] The embodiments disclosed herein are directed to a method and cleaning apparatus designed to track the amplitude of contaminant-specific Raman scattering peaks and back-calculate the concentration of a contaminant (e.g., IPA) at a supercritical cleaning chamber exhaust port. In particular, there can be a continuous flow of fluid through the cleaning chamber from an inlet to an exhaust port. The scCO2 may gradually dissolve the IPA over a period of time (e.g., 1-2 minutes), and the solution of IPA in scCO2 exits the chamber through the exhaust port. The measurement module can be positioned in an exhaust position so that all of the effluent IPA and scCO2 passes through the measurement module. The cleaning apparatus can include a sensor that provides in-line remote sensing capability through a single optical window without interrupting the scCO2 flow.

[0016] According to some embodiments, the cleaning apparatus includes a remote-sensing Raman sensor that tracks contaminants within the high-pressure, high-temperature chamber through an optical window. The cleaning apparatus may further include a highly stable laser and beam-shaping optics. The Raman sensor may include two or more photosensitive detectors, each with a separate narrowband filter, at least one for tracking the amplitude of a specific Raman peak of the contaminant of interest and at least one for tracking the background.

[0017] FIG. 1 illustrates an embodiment of a cleaning apparatus. The cleaning apparatus may include a laser light source 100 that directs light 120A toward a chamber 102. The chamber 102 may contain one or more wafers for performing a cleaning process. The light 120A may enter the chamber 102 through an entrance window. The cleaning apparatus may further include a sensor 104 and a Raman sensor 106 that collects light 120B exiting the chamber 102. The light may be inelastically scattered light. The light 120B may exit the chamber 102 through the entrance window. The cleaning apparatus may further include a processor 108 that receives information from the sensors 104 and 106 and controls the flow of gas from the gas supply 110 to the chamber 102 based on the information received from the sensors 104 and 106. For example, based on the information received from the Raman sensor 106, the processor 108 may detect an endpoint of the wafer cleaning process and control the gas supply 110 to terminate the endpoint of the wafer cleaning process. Sensor 104 may be an optical sensor that can determine the phase of the supercritical fluid (SCF) from refractive index measurements. An example of an SCF refractive index sensor is provided in U.S. Pat. No. 10,837,902, the entire contents of which are incorporated herein by reference. Based on the data received from sensors 104 and 106, processor 108 can provide feedback to a cleaning process control system to help ensure the cleaning process is complete when the concentration of residue falls below a desired threshold, while minimizing cleaning cycle time and CO2 consumption for reduced cycle costs and environmental benefits.

[0018] In some embodiments, a Raman sensor can include two photodiodes, each with a narrowband filter. The center wavelength of one of the filters can be tuned to match the wavelength of one of the Raman peaks of a contaminant of interest, such as IPA. The center wavelengths of the filters can be tuned to wavelengths away from the Raman peaks of interest (e.g., IPA and CO2) or away from other wavelengths not anticipated by one skilled in the art for an optical signal with a selected light source. An example excitation wavelength includes 785 nm, with a notch filter blocking the 785 nm light in the collection path. In that example, the first filter can be tuned to transmit wavelengths, for example, within the 835-843 nm range around the IPA Raman peak at 839 nm, and the second filter can be tuned to transmit wavelengths, for example, within the 820-835 nm range (see Figure 6) for background light with that particular light source. In other embodiments, a Raman sensor can include three photodiodes, each with a narrowband filter (see Figure 2). In that example, one filter may be tuned to the IPA Raman peak wavelength at 839 nm, a second filter may be tuned to collect background over the range of 820-835 nm, and a third filter may be tuned to collect one of the CO2 Raman peaks at 873 nm.

[0019] According to some embodiments, the cleaning apparatus includes an optical design that transmits illumination light through a window in the high-pressure / high-temperature chamber and collects light scattered by the test material through the same window. The scattered light is then separated from the illumination light using a dichroic mirror, essentially. The scattered light is then further optically processed by filtering the remaining illumination light with a notch filter. The filtered light is then analyzed using two or more photosensitive detectors, at least one detector that measures background and at least one detector that measures the intensity of the Raman peak of the test material.

[0020] FIG. 2 illustrates an embodiment of a Raman sensor. As shown in FIG. 2, illumination light is focused into the test volume using an optical lens 204. This optical lens 204 can be used to collect scattered Raman light and separate it from the illumination light using a dichroic mirror 202 that transmits the excitation wavelength light and reflects light at the Raman peak wavelength. The collected scattered Raman light is further filtered by a notch filter 206. As those skilled in the art will appreciate, Raman light corresponds to inelastically scattered light (e.g., scattered photons have a different wavelength than unescaped photons). After filtering by the notch filter 206, the collected scattered light can pass through an additional bandpass filter "Filter-BG" 310 to select background wavelengths of interest. The background light can be focused by an optical lens 312 onto a background detector "PD-BG" 314, which can be a photodiode or similar photosensitive detector.

[0021] After being filtered by notch filter 206, an additional dichroic mirror 208 separates out background light of wavelengths other than the Raman peaks for the substances of interest (e.g., IPA and CO2). For example, after passing through dichroic mirror 208, the collected light may pass through an additional bandpass filter "Filter-CO2" 218 to select wavelengths corresponding to the Raman peak of CO2. The CO2 light may be focused by optical lens 220 onto CO2 detector "PD-CO2" 222, which may be a photodiode or similar light-sensitive detector.

[0022] Additionally, the Raman sensor may further include a dichroic mirror 216 that separates the CO2 light from the IPA light. For example, after passing through the dichroic mirror 216, the collected light may pass through an additional bandpass filter "Filter-IPA" 224 to select the wavelength corresponding to the Raman peak of IPA. The IPA light may be focused by an optical lens 226 onto a photodiode "PD-IPA" 228, which may be a photodiode or similar photosensitive detector. In some embodiments, instead of using a dichroic mirror, one skilled in the art may use a non-wavelength-sensitive beam splitter. In some embodiments, the photodiodes PD-CO2 214 and PD-IPA 228 register the Raman peaks for CO2 and IPA, respectively. The peak for CO2 is at 1286 cm -1 The shift from the illumination wavelength for IPA is 819 cm -1 This can occur in.

[0023] 3 shows another embodiment of a Raman sensor including a prism-based spectrometer configuration for registering the Raman peaks of substances of interest (e.g., CO2 and IPA). In this regard, light passing through the initial notch filter 206 may pass through a dispersive prism 302 that separates the different wavelengths. The prism 302 may include focusing optics that focus the light onto a line sensor 306. The line sensor may be a multi-pixel detector that operates as a high light throughput spectrometer, which includes the Raman peaks for molecules of interest, such as IPA and CO2.

[0024] 4 shows an example configuration of a cleaning apparatus including a light source 402 that directs light 402A through an entrance window 410 of a measurement chamber. The light may contact material on the wafer to generate inelastically scattered light 402B. The inelastically scattered light may exit the measurement chamber through the entrance window 410 and may be collected by a Raman sensor 406 and a photodetector 408. The measurement chamber may further include a refractive index sensor detector 412. Both the directed light 402A and the inelastically scattered light may exit the measurement chamber through an exit window.

[0025] 5 illustrates an exemplary mechanical structure of the cleaning apparatus shown in FIG. 4. The mechanical structure of the cleaning apparatus may include a light source 502 that directs light through an optical configuration 504 before entering a measurement chamber 506. The optical configuration 504 may include a dichroic mirror and an optical lens. The measurement chamber 506 may include ports 508 and 510. One of these ports may be connected to a gas supply line, and the other port is connected to another line and serves as an exhaust port.

[0026] FIG. 6 is an example graph showing how the intensity of the Raman peaks of IPA changes based on the concentration of IPA. The x-axis of the graph is the Raman shift (cm -1 ) The y-axis of the graph shows arbitrary units (au) of spectrometer signal intensity. FIG. 6 shows an example intensity (600) of a Raman peak for IPA at a first concentration and an example intensity (602) of a Raman peak for IPA at a second concentration that is 50% of the first concentration. As shown in FIG. 6, when the concentration of IPA is reduced by 50%, the intensity of the IPA Raman peak decreases by approximately 50%.

[0027] In some embodiments, the endpoint of the wafer cleaning process can be determined based on the intensity of the IPA Raman peak. In other embodiments, the endpoint of the wafer cleaning process can be determined based on the relative peak intensity of the IPA Raman peak. The relative peak intensity of the IPA Raman peak can be determined using the following parameters: A: Intensity of the Raman peak of the contaminant in question (e.g., IPA) B: Intensity of the Raman peak of the solvent / cleaner (e.g., SCF CO2) C: Background light intensity

[0028] The Raman peak intensity can then be calculated relative to the background. Formula 1: A' = AC Formula 2: B'=BC

[0029] The calculated parameter A' may be the relative peak intensity of IPA, and B' may be the relative peak intensity of CO. The relative peak intensity of IPA may then be determined as follows: Formula 3: D=A'-B', where D is the relative peak intensity of IPA.

[0030] In another example, the relative peak intensity of IPA can be determined as follows: Formula 4: D=A' / B' where D is the relative peak intensity of IPA.

[0031] The parameters A, B, and C may be provided from the Raman sensor to the processor 108 (FIG. 1) to perform the calculations of Equations 1-4.

[0032] FIG. 7 shows an exemplary graph of the relative peak intensity of the IPA Raman peak versus the concentration of IPA in the measurement chamber. As shown in FIG. 7, the relative peak intensity of the IPA Raman peak has a linear correlation with the concentration of IPA in the measurement chamber. Therefore, by determining the relative peak intensity of the IPA Raman peak, one skilled in the art can determine the concentration of IPA in the measurement chamber. In some embodiments, when the relative peak intensity of the IPA Raman peak is less than a predetermined threshold, the endpoint of the wafer cleaning process can be determined and the wafer cleaning process can be terminated.

[0033] FIG. 8 illustrates an embodiment of a wafer cleaning cycle based on supercritical CO fluid according to some embodiments of the present disclosure. The wafer cleaning cycle process may begin at 800. At 800, supercritical CO fluid is maintained in a supply pipe, and an IPA-covered wafer enters a processing chamber. In some embodiments, the wafer may have multiple microstructures. The microstructures may be openings having widths and heights. IPA may be trapped in the openings from a previous processing step, such as an IPA drying process. The process proceeds from step 800 to step 802, where supercritical CO fluid is introduced into the processing chamber through an input valve, causing the supercritical CO fluid to flow past the top surface of the wafer. At step 804, as more and more supercritical CO fluid is introduced into the processing chamber, the supercritical CO fluid dissolves in the IPA trapped in the openings. At step 806, as the wafer cleaning process continues, IPA is entrained and carried away within the supercritical CO fluid. In step 808, the bulk supercritical CO2 fluid displaces the remaining IPA as the processing time progresses. In step 810, the input valve is closed while the outlet valve remains on, reducing the pressure in the processing chamber. The supercritical CO2 fluid transitions to a gas and leaves the wafer as the pressure is reduced. The process shown in FIG. 8 can be terminated after step 810.

[0034] FIG. 9 illustrates an embodiment of endpoint detection for a wafer cleaning process. For example, the process illustrated in FIG. 9 may be performed at any time during the process illustrated in FIG. 8, and the process illustrated in FIG. 8 may be terminated at any time based on the process illustrated in FIG. 9. In some embodiments, the endpoint detection process illustrated in FIG. 9 may be performed at periodic intervals (e.g., 10 ms to 1 s). The process may begin in step 900. In step 900, an incident light beam is directed toward an entrance window of a measurement chamber during the wafer cleaning process. As the light beam enters the measurement chamber, it is inelastically scattered by one or more sample substances (e.g., IPA and CO) contained in the measurement chamber. The process proceeds to step 902, where light from the measurement chamber is collected and measured. The light may be collected through the same entrance window through which the light enters the measurement chamber. The inelastically scattered light may be collected by a Raman sensor, such as Raman sensor 200 (FIG. 2) or Raman sensor 300 (FIG. 3). For example, the Raman sensor may collect inelastically scattered light from the measurement chamber and perform spectral analysis of the collected light to measure the intensity of the Raman peaks of one or more substances contained in the measurement chamber. The Raman sensor may output the above-mentioned parameters A (e.g., the intensity of the Raman peak of IPA), B (e.g., the intensity of the Raman peak of CO), and C (e.g., the intensity of the background light).

[0035] The process may proceed to step 904, where the concentration of the substance is calculated. The concentration may be calculated by processor 108 (FIG. 1). The substance may be a contaminant of interest, such as IPA. In some embodiments, the concentration of IPA is determined based on the measured intensities of the IPA Raman peaks. In other embodiments, the calculated concentration is based on the relative peak intensities of the IPA Raman peaks, as determined according to Equations 1-4 above.

[0036] The process proceeds from step 904 to step 906 to determine an endpoint of the wafer cleaning process based on the calculated concentration. For example, the endpoint of the wafer cleaning process may be determined when the calculated concentration is less than a predetermined threshold. The process proceeds to step 908, where the wafer cleaning process is terminated in response to determining the endpoint of the wafer cleaning process. For example, once the endpoint of the wafer cleaning process is determined, processor 108 (FIG. 1) may control the supply of CO into the measurement chamber so that the wafer cleaning process is terminated. The process shown in FIG. 9 may end after step 908.

[0037] In some embodiments, processor 108 (FIG. 1) may be a stand-alone processor, such as a microcontroller, configured to receive data from one or more sensors and execute computer code to process the received data and control processes performed on wafers in a measurement chamber. In other embodiments, processor 108 may be a computer system operating as a workstation terminal. For example, FIG. 10 illustrates a computer system (1000) suitable for implementing some embodiments of the disclosed subject matter.

[0038] Computer software may be encoded using any suitable machine code or computer language that may be subject to assembly, compilation, linking, or similar mechanisms to generate code containing instructions that may be executed by one or more computer central processing units (CPUs), either directly, or through interpretation, microcode execution, etc. The instructions may be executed on various types of computers or components thereof, including, for example, personal computers, tablet computers, servers, etc.

[0039] 10 for computer system 1000 are exemplary in nature and are not intended to suggest any limitation as to the scope of use or functionality of the computer software implementing embodiments of the present disclosure. The arrangement of components should not be construed as having any dependency or requirement regarding any one or combination of components shown in the exemplary embodiment of computer system 1000.

[0040] The computer system (1000) may include several human interface input devices. Such human interface input devices may respond to input by one or more human users through, for example, tactile input (keystrokes, swipes, etc.). The input human interface devices may include one or more of a keyboard (1001), a mouse (1002), a trackpad (1003), and a touchscreen (1010).

[0041] The computer system (1000) may also include several human interface output devices. Such human interface output devices may include visual output devices (screens (1010), including CRT screens, LCD screens, plasma screens, OLED screens, etc.), each with or without touchscreen input capability, each with or without haptic feedback capability, some of which may be capable of outputting two-dimensional visual output or three or more dimensional output through means such as stereographic output.

[0042] The computer system (1000) may also include human-accessible storage devices and their associated media, such as optical media including CD / DVD ROM / RW (1020) with media (1021) such as CDs / DVDs, thumb drives (1022), removable hard drives or solid state drives (1023), legacy magnetic media such as tape and floppy disks (not shown), and dedicated ROM / ASIC / PLD-based devices such as security dongles (not shown).

[0043] Those skilled in the art should also understand that the term "computer-readable medium" as used in connection with the subject matter of this disclosure does not encompass transmission media, carrier waves, or other transitory signals.

[0044] The computer system 1000 may also include interfaces to one or more communication networks. The networks may be, for example, wireless, wired, or optical. The networks may also be local, wide-area, metropolitan, vehicular, industrial, real-time, delay-tolerant, etc. Examples of networks include local area networks such as Ethernet, wireless LANs, and cellular networks including GSM, 3G, 4G, 5G, LTE, etc. Some networks typically require an external network interface adapter attached to a general-purpose data port or peripheral bus 1049 (e.g., a USB port on the computer system 1000). Others are typically integrated into the core of the computer system 1000 by attachment to a system bus (e.g., an Ethernet interface on a PC computer system or a cellular network interface on a smartphone computer system), as described below. Using any of these networks, the computer system 1000 may communicate with other entities. Such communications may be unidirectional, receive-only, unidirectional transmit-only (e.g., a CANbus to a CANbus device), or bidirectional, for example, to other computer systems using local or wide area digital networks. Certain protocols and protocol stacks may be used over each of these networks and network interfaces described above.

[0045] The aforementioned human interface devices, human-accessible storage devices, and network interfaces may be attached to the core (1040) of the computer system (1000). The core (1040) may include one or more central processing units (CPUs) (1041), graphics processing units (GPUs) (1042), dedicated programmable processing units (1043) in the form of field-programmable gate arrays (FPGAs), hardware accelerators (1044) for some tasks, etc. These devices, along with read-only memory (ROM) (1045), random-access memory (1046), and internal mass storage devices (1047) such as internal non-user-accessible hard drives or SSDs, may be connected through a system bus (1048). In some computer systems, the system bus (1048) may be accessible in the form of one or more physical plugs to allow expansion with additional CPUs, GPUs, etc. Peripheral devices can be attached directly to the core system bus 1048 or through a peripheral bus 1049. Architectures for peripheral buses include PCI, USB, etc.

[0046] The CPU (1041), GPU (1042), FPGA (1043), and accelerator (1044) may execute certain instructions that may combine to constitute the aforementioned computer code. The computer code may be stored in ROM (1045) or RAM (1046). Transient data may also be stored in RAM (1046), and permanent data may be stored, for example, in internal mass storage device (1047). Fast storage and fast retrieval from any of the memory devices may be enabled through the use of cache memory, which may be closely associated with one or more of the CPU (1041), GPU (1042), mass storage device (1047), ROM (1045), RAM (1046), etc.

[0047] The computer-readable medium may have computer code thereon for performing various computer-implemented operations. The medium and computer code may be those specially designed and constructed for the purposes of the present disclosure, or they may be of the kind well known and available to those skilled in the computer software arts.

[0048] By way of example and not limitation, a computer system (1000) having an architecture, and specifically the core (1040), may provide functionality as a result of a processor (including a CPU, GPU, FPGA, accelerator, etc.) executing software embodied in one or more tangible computer-readable media. Such computer-readable media may be media associated with some storage of the core (1040) that is non-transitory in nature, such as the user-accessible mass storage introduced above and the core's internal mass storage (1047) or ROM (1045). Software implementing various embodiments of the present disclosure may be stored on such devices and executed by the core (1040). The computer-readable media may include one or more memory devices or chips according to particular needs. The software may cause the core (1040) and specifically the processor (including a CPU, GPU, FPGA, etc.) therein to perform particular processes or particular portions of particular processes described herein, including defining data structures stored in RAM (1046) and modifying such data structures according to the software-defined processes. Additionally, or alternatively, the computer system may provide functionality as a result of logic implemented in hardware or embodied in circuitry (e.g., accelerator 1044), which may operate in place of or in conjunction with software to perform particular processes or portions of particular processes described herein. References to software may encompass logic, and vice versa, as appropriate. References to computer-readable media may encompass circuitry (such as an integrated circuit (IC)) that stores software for execution, circuitry that embodies logic for execution, or both, as appropriate. The present disclosure encompasses any suitable combination of hardware and software.

[0049] The foregoing outlines features of several embodiments so that those skilled in the art may better understand aspects of the present disclosure. Those skilled in the art should appreciate that this disclosure may be readily utilized as a basis for designing or modifying other processes and structures to carry out the same purposes and / or achieve the same advantages of the embodiments presented herein. Those skilled in the art should also appreciate that such equivalent constructions do not depart from the spirit and scope of the present disclosure, and that various changes, substitutions, and alterations can be made without departing from the spirit and scope of the present disclosure.

[0050] (1) An apparatus for in-situ cleaning endpoint detection, the apparatus including: a measurement chamber configured to hold one or more sample substances; an entrance window attached to one side of the measurement chamber; a light source configured to generate an incident light beam, the incident light beam being directed into the chamber through the entrance window, the incident light beam being inelastically scattered inside the chamber by the one or more sample substances; a Raman sensor configured to collect the inelastically scattered light from the chamber and measure an intensity of a Raman peak of a first substance from the one or more sample substances based on the collected inelastically scattered light; and a processor configured to (i) calculate a concentration of the first substance from the one or more sample substances based on at least the measured intensity of the Raman peak of the first substance; (ii) determine an endpoint of a wafer cleaning process based on the calculated concentration of the first substance; and (iii) terminate the wafer cleaning process based on the determined endpoint.

[0051] (2) The apparatus of feature (1), wherein the Raman sensor is further configured to measure the intensity of a Raman peak of a second substance from one or more sample substances and the intensity of background light.

[0052] (3) The apparatus of feature (1) or (2), wherein the processor is further configured to determine a first relative intensity of the first substance by subtracting the intensity of the background light from the intensity of the Raman peak of the first substance, determine a second relative intensity of the second substance by subtracting the intensity of the background light from the intensity of the Raman peak of the second substance, and determine a sample Raman peak relative intensity based on the first relative intensity and the second relative intensities.

[0053] (4) The apparatus of feature (3), wherein the sample Raman peak relative intensity is the difference between the first relative intensity and the second relative intensity.

[0054] (5) The apparatus of feature (3), wherein the sample Raman peak relative intensity is a ratio between the first relative intensity and the second relative intensity.

[0055] (6) The apparatus of features (4) or (5), wherein the processor is further configured to calculate a concentration of the first substance from the determined sample Raman peak relative intensities.

[0056] (7) The apparatus according to any one of features (4) to (6), wherein the processor is further configured to determine an endpoint of the wafer cleaning process in response to determining that the sample Raman peak relative intensity is less than or equal to a threshold value.

[0057] (8) The apparatus according to any one of features (1) to (7), wherein the first substance is isopropanol (IPA), and the Raman sensor includes a first photosensitive detector configured to detect Raman peaks of IPA.

[0058] (9) The apparatus according to any one of features (2) to (8), wherein the second substance is carbon dioxide and the Raman sensor includes a second photosensitive detector configured to detect the Raman peak of carbon dioxide.

[0059] (10) The apparatus according to any one of features (2) to (9), wherein the Raman sensor includes a third photosensitive detector configured to detect background light.

[0060] (11) The apparatus according to any one of features (1) to (10), wherein the Raman sensor further includes: (i) a prism that separates the inelastically scattered light from the chamber into multiple wavelengths; and (ii) a line sensor for detecting the multiple wavelengths.

[0061] (12) The apparatus according to any one of features (1)-(11), further comprising a supercritical fluid (SCF) refractive index sensor configured to collect inelastically scattered light from the chamber, the SCF refractive index sensor configured to determine the phase of the SCF in the measurement chamber.

[0062] (13) The apparatus according to any one of features (1) to (11), wherein the one or more sample materials include carbon dioxide, and the carbon dioxide is under supercritical conditions.

[0063] (14) A method for in-situ cleaning endpoint detection includes: directing, by a light source, an incident light beam through an entrance window of a measurement chamber during a wafer cleaning process, the measurement chamber holding one or more sample substances, the incident light beam being inelastically scattered inside the chamber by the one or more sample substances; collecting, by a Raman sensor, the inelastically scattered light from the chamber; measuring, by the Raman sensor, an intensity of a Raman peak of a first substance from the one or more sample substances based on the collected inelastically scattered light; calculating, by a processor, a concentration of the first substance based on at least the measured intensity of the Raman peak of the first substance; determining, by the processor, an endpoint of the wafer cleaning process based on the calculated concentration of the first substance; and terminating, by the processor, the wafer cleaning process based on the determined endpoint.

[0064] (15) The method of feature (14), further comprising measuring, with the Raman sensor, the intensity of the Raman peak of the second substance from the one or more sample substances and the intensity of the background light.

[0065] (16) The method of feature (15), further including: determining, by the processor, a first relative intensity of the first material by subtracting the intensity of the background light from the intensity of the Raman peak of the first material; determining, by the processor, a second relative intensity of the second material by subtracting the intensity of the background light from the intensity of the Raman peak of the second material; and determining, by the processor, a sample Raman peak relative intensity based on the first relative intensity and the second relative intensities.

[0066] (17) The method of feature (16), wherein the sample Raman peak relative intensity is the difference between the first relative intensity and the second relative intensity.

[0067] (18) The method of feature (16), wherein the sample Raman peak relative intensity is a ratio between the first relative intensity and the second relative intensity.

[0068] (19) The method according to any one of features (16) to (18), wherein the calculated concentration is determined from the determined relative intensity of the sample Raman peak.

[0069] (20) The method according to any one of features (16) to (19), wherein the endpoint of the wafer cleaning process is determined in response to determining that the relative intensity of the sample Raman peak is equal to or less than a threshold value.

Claims

1. 1. An apparatus for in-situ cleaning endpoint detection, comprising: a measurement chamber configured to hold one or more sample substances; an entrance window attached to one side of the measurement chamber; a light source configured to generate an incident light beam, the incident light beam being directed into the measurement chamber through the entrance window, the incident light beam being inelastically scattered inside the measurement chamber by the one or more sample materials; a Raman sensor configured to collect the inelastically scattered light from the measurement chamber and measure an intensity of a Raman peak of a first substance from the one or more sample substances based on the collected inelastically scattered light; a processor configured to (i) calculate a concentration of the first substance from the one or more sample substances based on the intensity of at least the measured Raman peak of the first substance; (ii) determine the endpoint of a wafer cleaning process based on the calculated concentration of the first substance; and (iii) terminate the wafer cleaning process based on the determined endpoint; It is equipped with The apparatus, wherein the first substance is isopropanol (IPA), and the Raman sensor includes a first photosensitive detector configured to detect Raman peaks of the IPA.

2. The apparatus of claim 1 , wherein the Raman sensor is further configured to measure an intensity of a Raman peak of a second substance from the one or more sample substances and an intensity of background light.

3. the processor: determining a first relative intensity of the first material by subtracting the intensity of the background light from the intensity of the Raman peak of the first material; determining a second relative intensity of the second material by subtracting the intensity of the background light from the intensity of the Raman peak of the second material; The apparatus of claim 2 , further configured to determine a sample Raman peak relative intensity based on the first relative intensity and the second relative intensity.

4. 4. The apparatus of claim 3, wherein the sample Raman peak relative intensity is the difference between the first relative intensity and the second relative intensity.

5. 4. The apparatus of claim 3, wherein the sample Raman peak relative intensity is a ratio between the first relative intensity and the second relative intensity.

6. The apparatus of claim 3 , wherein the processor is further configured to calculate the concentration of the first substance from the determined sample Raman peak relative intensities.

7. 4. The apparatus of claim 3, wherein the processor is further configured to determine the endpoint of the wafer cleaning process in response to determining that the sample Raman peak relative intensity is less than or equal to a threshold value.

8. 3. The apparatus of claim 2, wherein the second substance is carbon dioxide and the Raman sensor includes a second photosensitive detector configured to detect Raman peaks of the carbon dioxide.

9. The apparatus of claim 2 , wherein the Raman sensor includes a third photosensitive detector configured to detect the background light.

10. 10. The apparatus of claim 1, wherein the Raman sensor further comprises: (i) a prism that separates the inelastically scattered light from the measurement chamber into multiple wavelengths; and (ii) a line sensor for detecting the multiple wavelengths.

11. 10. The apparatus of claim 1, further comprising a supercritical fluid (SCF) refractive index sensor configured to collect the inelastically scattered light from the measurement chamber, the SCF refractive index sensor configured to determine a phase of SCF in the measurement chamber.

12. The apparatus of claim 1 , wherein the one or more sample materials comprise carbon dioxide, and the carbon dioxide is under supercritical conditions.

13. 1. A method for in-situ cleaning endpoint detection, comprising: directing, by a light source, an incident light beam through an entrance window of a measurement chamber during a wafer cleaning process, the measurement chamber holding one or more sample materials, the incident light beam being inelastically scattered inside the measurement chamber by the one or more sample materials; collecting the inelastically scattered light from the measurement chamber with a Raman sensor; and measuring, by the Raman sensor, an intensity of a Raman peak of a first substance from the one or more sample substances based on the collected inelastically scattered light. calculating, by a processor, a concentration of the first substance based at least on the measured intensity of the Raman peak of the first substance; determining, by the processor, an endpoint of the wafer cleaning process based on the calculated concentration of the first substance; terminating the wafer cleaning process based on the endpoint determined by the processor; Including, The method, wherein the first substance is isopropanol (IPA), and the Raman sensor includes a first photosensitive detector configured to detect Raman peaks of the IPA.

14. 14. The method of claim 13, further comprising measuring, with the Raman sensor, an intensity of a Raman peak of a second substance from the one or more sample substances and an intensity of background light.

15. determining, by the processor, a first relative intensity of the first material by subtracting the intensity of the background light from the intensity of the Raman peak of the first material; determining, by the processor, a second relative intensity of the second material by subtracting the intensity of the background light from the intensity of the Raman peak of the second material; determining, by the processor, a sample Raman peak relative intensity based on the first relative intensity and the second relative intensity; 15. The method of claim 14, further comprising:

16. 16. The method of claim 15, wherein the sample Raman peak relative intensity is the difference between the first relative intensity and the second relative intensity.

17. 16. The method of claim 15, wherein the sample Raman peak relative intensity is a ratio between the first relative intensity and the second relative intensity.

18. 16. The method of claim 15, wherein the calculated concentration is determined from the determined sample Raman peak relative intensities.

19. 16. The method of claim 15, wherein the endpoint of the wafer cleaning process is determined in response to determining that the sample Raman peak relative intensity is less than or equal to a threshold value.

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