WO2024155784A1

WO2024155784A1 - Systems and methods for determining polymer build-up within a chemical processing chamber

Info

Publication number: WO2024155784A1
Application number: PCT/US2024/011969
Authority: WO
Inventors: Ashish Bhatnagar; Grant BREWER
Original assignee: Watlow Electric Manufacturing Company
Priority date: 2023-01-18
Filing date: 2024-01-18
Publication date: 2024-07-25

Abstract

A method for monitoring polymer build-up within a chemical processing chamber and in response to generating thermal energy during a chemical process includes determining a response characteristic in response to generating the thermal energy, where the response characteristic includes an operational characteristic associated with the heater, a wall characteristic associated with at least one external wall surface of the chemical processing chamber, or a combination thereof. The method includes correlating the response characteristic to an amount of polymer build¬ up within the chemical processing chamber based on a response characteristic- polymer build-up correlation model and an emissivity range of the polymer build-up.

Description

SYSTEMS AND METHODS FOR DETERMINING POLYMER BUILD-UP WITHIN A CHEMICAL PROCESSING CHAMBER

FIELD

[0001] The present disclosure relates to systems and methods for determining polymer build-up within a chemical processing chamber, such as a semiconductor processing chamber.

BACKGROUND

[0002] The statements in this section merely provide background information related to the present disclosure and may not constitute prior art.

[0003] In various chemical processing environments, operators monitor various components to identify and diagnose potential issues and anomalies associated therewith. As an example, during a semiconductor process (e.g., a dry etching routine), an operator may monitor a semiconductor processing chamber to detect polymer build-up on, for example, an internal wall surface, a liner, a showerhead, a heater surface, among other components.

[0004] As a more specific example, during a dry etching routine, one or more precursor gases are employed to create etchants. As a number of iterations of the dry etching routine are performed, a polymer resulting from the combination of gases (e.g., a fluorocarbon polymer) may be deposited on, for example, the internal wall and/or liner of the semiconductor processing chamber and gradually grow in thickness. Furthermore, when the polymer thickness exceeds a threshold thickness, the polymer buildup may erode and accumulate onto the wafer or other components of the semiconductor processing chamber, thereby inhibiting the wafer yield, inducing wafer defects due to arcing, and/or inducing undesirable parameter changes of the etching routine to accommodate for the polymer deposits.

[0005] Accordingly, an operator may employ various polymer build-up monitoring routines to detect polymer build-up and/or perform one or more corrective actions to accommodate for the polymer build-up. As an example, an operator may control the semiconductor processing environment to provide a cleaning/oxidizing gas into the semiconductor processing chamber, initiate a wet cleaning routine according to a preventive maintenance schedule, and/or employ cleaning cycles after each wafer (or a predetermined number of wafers) is processed. However, these corrective routines inhibit the semiconductor processing system’s efficiency, as these corrective actions may require an operator to open the semiconductor processing chamber, clean the semiconductor processing chamber, and close the semiconductor processing chamber the cleaning cycle is complete. Once the semiconductor processing chamber is exposed to the atmosphere, a pumping operation is performed to return the semiconductor processing chamber to a base vacuum level, and the pumping operation may be a resource and time-intensive process, thereby inhibiting chamber throughput. That is, these corrective actions do not incorporate in-situ detection and mitigation routines to detect polymer build-up and/or perform a corresponding corrective actions.

[0006] These issues with detecting polymer build-up and performing corrective actions, among other issues, are addressed by the present disclosure.

SUMMARY

[0007] This section provides a general summary of the disclosure and is not a comprehensive disclosure of its full scope or all of its features.

[0008] The present disclosure provides a method for monitoring polymer build-up within a chemical processing chamber and in response to generating thermal energy during a chemical process. The method includes determining a response characteristic in response to generating the thermal energy, where the response characteristic includes an operational characteristic associated with the heater, a wall characteristic associated with at least one external wall surface of the chemical processing chamber, or a combination thereof. The method includes correlating the response characteristic to an amount of polymer build-up within the chemical processing chamber based on a response characteristic-polymer build-up correlation model and an emissivity range of the polymer build-up.

[0009] The following paragraph includes variations of the method of the above paragraph, and the variations may be implemented individually or in any combination while remaining within the scope of the present disclosure.

[0010] In one form, the method includes obtaining steady state data, where the steady state data is based on a temperature of a wafer of the chemical processing chamber, a chemical process recipe, or a combination thereof; determining whether the chemical process is operating in a steady state based on the steady state data; and determining the response characteristic in response to determining the chemical process is operating in the steady state; the operational characteristic is an electrical characteristic of a heater; the electrical characteristic is a voltage change of the heater when the chemical process is operating in the steady state, a current change of the heater when the chemical process is operating in the steady state, or a combination thereof; the method includes obtaining a steady state voltage of the heater in response to the chemical process operating in the steady state; and determining the electrical characteristic of the heater based on a difference between the steady state voltage and a previous steady state voltage of the heater stored in a database; the method includes obtaining a steady state current of the heater in response to the chemical process operating in the steady state; and determining the current change of the heater based on a difference between the steady state current and a previous steady state current of the heater stored in a database; the wall characteristic is one of a temperature characteristic of the at least one external wall surface and a heat flux characteristic of the at least one external wall surface; the method includes obtaining a steady state temperature of the at least one external wall surface in response to the chemical process operating in the steady state; and determining the temperature characteristic of the at least one external wall surface based on a difference between the steady state temperature and a previous steady state temperature of the at least one external wall surface stored in a database; the steady state temperature of the at least one external wall surface is obtained from a temperature sensor; the method includes obtaining a steady state heat flux of the at least one external wall surface in response to the chemical process operating in the steady state; and determining the heat flux characteristic of the at least one external wall surface based on a difference between the steady state heat flux and a previous steady state heat flux of the at least one external wall surface stored in a database; the steady state heat flux of the at least one external wall surface is obtained from a heat flux sensor; the method includes selectively performing a corrective action based on the amount of polymer build-up; the corrective action includes generating a notification based on the amount of polymer build-up, adjusting one or more parameters of the chemical process, or a combination thereof; the chemical process is a semiconductor process; the chemical processing chamber is a semiconductor processing chamber.

[0011] The present disclosure also provides a system for monitoring polymer build-up within a chemical processing chamber. The system includes a heater configured to generate thermal energy during a chemical process; a chemical processing chamber comprising a wafer and at least one external wall surface; and a control system comprising a chemical processing controller, a thermal controller, or a combination thereof. The control system is configured to determine whether the chemical process is operating in a steady state based on steady state data of the chemical processing chamber, where the steady state data is based on a temperature of the wafer, a chemical process recipe, or a combination thereof; and determine a response characteristic when the chemical processing is operating in a steady state and in response to the heater generating the thermal energy, where the response characteristic includes an operational characteristic associated with the heater, a wall characteristic associated with the at least one external wall surface, or a combination thereof. The control system is configured to correlate the response characteristic to an amount of polymer build-up within the chemical processing chamber based on a response characteristic-polymer build-up correlation model and an emissivity range of the polymer build-up; and selectively perform a corrective action based on the amount of polymer build-up.

[0012] The following paragraph includes variations of the system of the above paragraph, and the variations may be implemented individually or in any combination.

[0013] In one form, the operational characteristic is an electrical characteristic of the heater; the electrical characteristic is a voltage change of the heater when the chemical process is operating in the steady state, a current change of the heater when the chemical process is operating in the steady state, or a combination thereof; the control system is configured to obtain a steady state voltage of the heater in response to the chemical process operating in the steady state; and determine the electrical characteristic of the heater based on a difference between the steady state voltage and a previous steady state voltage of the heater stored in a database; the control system is configured to obtain a steady state current of the heater in response to the chemical process operating in the steady state; and determine the current change of the heater based on a difference between the steady state current and a previous steady state current of the heater stored in a database; the wall characteristic is one of a temperature characteristic of the at least one external wall surface and a heat flux characteristic of the at least one external wall surface; the control system is configured to obtain a steady state temperature of the at least one external wall surface in response to the chemical process operating in the steady state; and determine the temperature characteristic of the at least one external wall surface based on a difference between the steady state temperature and a previous steady state temperature of the least one external wall surface stored in a database; the steady state temperature of the at least one external wall surface is obtained from a temperature sensor disposed on the wall; the control system is configured to obtain a steady state heat flux of the least one external wall surface in response to the chemical process operating in the steady state; and determine the heat flux characteristic of the least one external wall surface based on a difference between the steady state heat flux and a previous steady state heat flux of the least one external wall surface stored in a database; the steady state heat flux of the least one external wall surface is obtained from a heat flux sensor disposed on the wall; the corrective action includes generating a notification based on the amount of polymer build-up, adjusting one or more parameters of the chemical process, or a combination thereof; the chemical process is a semiconductor process; the chemical processing chamber is a semiconductor processing chamber.

[0014] The present disclosure provides a method for monitoring polymer build-up within a chemical processing chamber, the chemical processing chamber comprising a wafer and at least one external wall surface. The method includes generating, by a heater, thermal energy during a chemical process; determining, by a control system, whether the chemical process is operating in a steady state based on steady state data of the chemical processing chamber, where the steady state data is based on a temperature of the wafer, a chemical process recipe, or a combination thereof; and determining, by the control system, a response characteristic when the chemical processing is operating in a steady state and in response to the heater generating the thermal energy, where the response characteristic includes an operational characteristic associated with the heater, a wall characteristic associated with the at least one external wall surface, or a combination thereof. The method includes correlating, by the control system, the response characteristic to an amount of polymer build-up within the chemical processing chamber based on a response characteristic-polymer build-up correlation model and an emissivity range of the polymer build-up; and selectively performing, by the control system, a corrective action based on the amount of polymer build-up.

[0015] Further areas of applicability will become apparent from the description provided herein. It should be understood that the description and specific examples are intended for purposes of illustration only and are not intended to limit the scope of the present disclosure.

DRAWINGS

[0016] In order that the disclosure may be well understood, there will now be described various forms thereof, given by way of example, reference being made to the accompanying drawings, in which:

[0017] FIG. 1 is an example chemical processing environment in accordance with the teachings of the present disclosure;

[0018] FIG. 2 is an example semiconductor processing environment in accordance with the teachings of the present disclosure;

[0019] FIG. 3 is a functional block diagram of an example semiconductor processing environment in accordance with the teachings of the present disclosure;

[0020] FIG. 4A is a functional block diagram of an example control system in accordance with the teachings of the present disclosure;

[0021] FIG. 4B is a functional block diagram of an example corrective action module in accordance with the teachings of the present disclosure;

[0022] FIG. 5A is a flowchart of an example routine for monitoring polymer build-up within the chemical processing environment in accordance with the teachings of the present disclosure;

[0023] FIG. 5B is a flowchart of an example routine for monitoring polymer build-up within a semiconductor processing environment in accordance with the teachings of the present disclosure;

[0024] FIG. 6A is a flowchart of another example routine for monitoring polymer build-up within the chemical processing environment in accordance with the teachings of the present disclosure; and

[0025] FIG. 6B is a flowchart of another example routine for monitoring polymer build-up within the semiconductor processing environment in accordance with the teachings of the present disclosure.

[0026] The drawings described herein are for illustration purposes only and are not intended to limit the scope of the present disclosure in any way. DETAILED DESCRIPTION

[0027] The following description is merely exemplary in nature and is not intended to limit the present disclosure, application, or uses. It should be understood that throughout the drawings, corresponding reference numerals indicate like or corresponding parts and features.

[0028] Referring to FIG. 1 , an example chemical processing environment 5 is shown and generally includes a chemical processing chamber 10 and a chemical processing control system 100. Generally, the chemical processing environment 5 is any type of environment in which one or more chemical processes are carried out, such as a semiconductor processing environment, a combustion exhaust environment, reaction vessels, heat exchangers, an industrial dryer and separator of a water treatment apparatus, a fluid flow environment, among other types of chemical processing environments. As used herein, “fluid” refers to a gas, liquid, and/or plasma.

[0029] As an example and referring to FIG. 2, a semiconductor processing environment 5-1 (as the chemical processing environment 5) for performing one or more semiconductor processes (as the chemical process) is shown and includes a semiconductor processing chamber 10-1 (as the chemical processing chamber 10), a gas delivery system 20, a fluid line thermal system 30, and a semiconductor processing system control system (SPSCS) 100-1 (as the chemical processing control system 100). In one form, the gas delivery system 20 includes a gas source 22, a gas supply line 24 for delivering process gases from the gas source 22 to the processing chamber 10-1 , a gas abatement system 26, and an exhaust line 28 for delivering exhaust gases from the processing chamber 10-1 to the gas abatement system 26, such as post-process gases, by-products of the gas/plasma, and/or waste associated with the wafer. In one form, the process gases used in semiconductor wafer processing may be pyrophoric or corrosive (e.g., fluoride, ammonia, silane, argon, arsine, and/or phosphine, among other gases). In some forms, unused process gases (e.g., argon or nitrogen) and undesirable by-products are delivered to the gas abatement system 26, where the unused process gases and by-products are cleansed and neutralized prior to being released to the environment or sent to another downstream process. In the following, process gases and exhaust gases may collectively be referred to as "gas."

[0030] In one form, the fluid line thermal system 30 includes a plurality of fluid line heaters 32 that are disposed at different locations along the gas supply line 24 and the exhaust line 28 to heat gases flowing in the gas supply line 24 and the exhaust line 28. In one form, the fluid line heaters 32 are flexible heaters wrapped about the gas supply line 24 and the exhaust line 28 to heat the gas therein. Heating the gas as it is delivered from the process chamber 10-1 and to the gas abatement system 26 facilitates the semiconductor process performed in the process chamber 10-1 and the exhaust gas treatment in the gas abatement system 26. Furthermore, heating the gas inhibits contaminants from depositing along the walls of the gas supply line 24 and the exhaust line 28 and therefore inhibits clogging in the gas supply line 24 and the exhaust line 28.

[0031] In one form, the fluid line thermal system 30 includes a plurality of fluid line heater sensors 34 for generating fluid line thermal system data that is indicative of a temperature of the fluid line heater 32, heat flux of the fluid line heater 32, and an electrical characteristic of the fluid line heater 32 (e.g., a voltage, a current, an electrical power, a resistance, a voltage change, a current change, an electrical power change, and/or a resistance change of the fluid line heater 32), among others. The plurality of fluid line heater sensors 34 may include a thermocouple, a resistance temperature detector, an infrared camera, a current sensor, and/or a voltage sensor, among others.

[0032] In one form, the plurality of fluid line heaters 32 may generate the electrical characteristic of the fluid line heaters 32 in lieu of or in addition to the one or more fluid line heater sensors 34. As an example, the fluid line heater 32 is provided as a "two-wire" heater that includes one or more resistive heating elements that operate as a sensor for measuring an average temperature of the resistive heating element based on a resistance of the resistive heating element as well as a heating element. Thus, only two wires are used rather than four wires with a discrete sensor. More particularly, such a two-wire heater is disclosed in U.S. Patent No. 7,196,295 titled “TWO-WIRE LAYERED HEATER SYSTEM,” which is commonly owned with the present application and the contents of which are incorporated herein by reference in its entirety. In a two-wire thermal system, the fluid line thermal system 30 is an adaptive thermal system that merges heater designs with controls that incorporate power, resistance, voltage, and current in a customizable feedback control system that limits one or more of these parameters (i.e., power, resistance, voltage, and current) while controlling another. In one form, the controller is configured to monitor at least one of current, voltage, and power delivered to the resistive heating element to determine the resistance and temperature of the resistive heating element. More particularly, such adaptive thermal systems and controllers are disclosed in U.S. Patent No. 10,690,705 titled “POWER CONVERTER FOR A THERMAL SYSTEM” and U.S. Patent No. 10,908,195 titled “SYSTEM AND METHOD FOR CONTROLLING POWER TO A HEATER,” which are commonly owned with the present application and the contents of which are incorporated herein by reference in its entirety.

[0033] In one form, the gas delivery system 20 includes a plurality of fluid line flow sensors 36 disposed proximate to (i.e., adjacent and/or near) the gas supply line 24 and the exhaust line 28 for measuring fluid line data. As an example, the fluid line flow sensors 36 are mounted on an external and/or internal surface of the gas supply line 24 and the exhaust line 28 to monitor for temperatures that may cause clogging, heat sinks, and hot spots that lead to system degradation and downtime. In one form, the fluid line data may include, but is not limited to, a temperature of the gas supply line 24/exhaust line 28, flow rate and pressure of the gases, and the types of process gases. Accordingly, the fluid line flow sensors 36 may include, but are not limited to, temperature sensors, pressure sensors, an anemometer, a pressure transducer, flow rate sensors, and gas sensors, among others.

[0034] In one form, the SPSCS 100-1 is configured to control the operation of the fluid line thermal system 30 and/or the gas delivery system 20 based on the fluid line thermal system data generated by the fluid line heater sensors 34 and/or the fluid line data generated by the fluid line flow sensors 36, among other process data. Example control routines for controlling the operation of the fluid line thermal system 30 and/or the gas delivery system 20 is disclosed in U.S. Patent Application No. 17/306,200 titled “METHOD OF MONITORING A SURFACE CONDITION OF A COMPONENT,” which is commonly owned with the present application and the contents of which are incorporated herein by reference in its entirety.

[0035] In one form, the semiconductor processing chamber 10-1 includes a chamber wall 42 defining an external wall surface 42A and an internal wall surface 42B, a liner 44, a chamber 46, a wafer 48, one or more external wall surface sensors 50, and a wafer support pedestal 60. It should be understood that the semiconductor processing chamber 10-1 may include other components (e.g., a lid, a showerhead, among other components) and is not limited to the components illustrated and/or described herein. In one form, the liner 44 is disposed on at least a portion of the internal wall surface 42B, and the chamber wall 42 and the liner 44 collectively define the chamber 46. Generally, the wafer 48 is disposed on an upper surface of the wafer support pedestal 60 (e.g., an electrostatic chuck) as shown during a semiconductor process.

[0036] In one form, the one or more external wall surface sensors 50 are disposed on the external wall surface 42A (e.g., secured, attached, and/or fixed to the external wall surface 42A) and are configured to generate sensor data corresponding to a wall characteristic of the external wall surface 42A. As an example, the external wall surface sensors 50 may be provided by temperature sensors configured to generate temperature data associated with the external wall surface 42A and/or heat flux sensors configured to generate heat flux data associated with the external wall surface 42A. As described below in further detail, the SPSCS 100-1 is configured to determine the wall characteristic of the external wall surface 42A (e.g., a temperature characteristic and/or heat flux characteristic) based on the sensor data generated by the one or more external wall surface sensors 50. It should be understood that any arrangement and/or number of the external wall surface sensors 50 may be provided, and as such, various arithmetic representations of the sensor data (e.g., a trend, mean, median, maximum, minimum, among others) may be provided to the SPSCS 100-1 . Furthermore, while the one or more external wall surface sensors 50 are shown as disposed on the external wall surface 42A, it should be understood that the one or more external wall surface sensors 50 may be disposed on the internal wall surface 42B in some variations.

[0037] In one form, the wafer support pedestal 60 includes one or more pedestal heaters 62 and/or one or more pedestal sensors 64. The one or more pedestal heaters 62 may each include one or more resistive heating elements that provide (e.g., increase or decrease) thermal energy to the wafer 48 and collectively define one or more heating zones. The SPSCS 100-1 may independently and selectively control the thermal energy provided to the wafer 48 based on pedestal sensor data generated by the pedestal sensors 64, which may be indicative of a temperature of the one or more pedestal heaters 62 and/or the wafer 48, a heat flux of the one or more pedestal heaters 62 and/or the wafer 48, an electrical characteristic of the one or more pedestal heaters 62 (e.g., a voltage, a current, an electrical power, a resistance, a voltage change, a current change, an electrical power change, and/or a resistance change of the one or more pedestal heaters 62), among others. As an example, the pedestal sensors 64 may include, but are not limited to, temperature sensors, thermocouples, RTDs, infrared sensors, fiber optic sensors, clamping electrodes, radio frequency (RF) antennas, and/or other conventional temperature sensing devices. Example pedestal heaters and sensors are disclosed in U.S. Patent No. 11 ,382,180 titled “MULTI-ZONE PEDESTAL HEATER HAVING A ROUTING LAYER” and U.S. Patent No. 11 ,343,879 titled “MULTI-ZONE PEDESTAL HEATER WITHOUT VIAS,” which are commonly owned with the present application and the contents of which are incorporated herein by reference in its entirety.

[0038] While the pedestal heaters 62 and pedestal sensors 64 are shown as built into the wafer support pedestal 60, it should be understood that the pedestal heaters 62 and/or pedestal sensors 64 may be disposed externally from the wafer support pedestal 60. In one variation, the pedestal does not include the pedestal heaters 62 when thermal energy is externally provided to the fluid (e.g., gas) via the gas supply line 24 to provide plasma into the chamber 46. Furthermore, it should be understood that the pedestal sensors 64 may be removed when the pedestal heaters 62 are “two-wire” heaters that are built into the wafer support pedestal 60.

[0039] Referring to FIGS. 2-3, the SPSCS 100-1 is configured to monitor polymer build-up 70 within the chamber 46, such as along the internal wall surface 42B and/or the liner 44. In one form, the SPSCS 100-1 includes a recipe module 105, a thermal controller 110, a response characteristic database 120, and a chemical processing controller 125. The chemical processing controller 125 may include a state module 130, a response characteristic module 140, a correlation module 150, a response characteristic-polymer build-up correlation (RCPBC) database 160, a corrective action module 170, and a human machine interface (HMI) 180. In one form, the components of the SPSCS 100-1 are communicably coupled using a wired communication protocol and/or a wireless communication protocol (e.g., a Bluetooth®- type protocol, a cellular protocol, a wireless fidelity (Wi-Fi)-type protocol, a near-field communication (NFC) protocol, an ultra-wideband (UWB) protocol, among others).

[0040] In one form, the recipe module 105 is configured to define a chemical process recipe to be performed by the SPSCS 100-1 based on a user input received from the HMI 180. As used herein, “chemical process recipe” refers to one or more predefined parameters of a chemical process. Example predefined parameters of the chemical process include, but are not limited to, a type of routine (e.g., a dry etching routine, a vapor deposition routine, among other routines), gas temperatures, a composition of process gasses/plasma to be supplied into the semiconductor processing chamber 10-1 , and/or one or more setpoint operational characteristics of the fluid line heaters 32 and/or the pedestal heaters 62 (e.g., setpoint electrical and/or temperature characteristics).

[0041] In one form and referring to FIGS. 3 and 4A, the thermal controller 110 is configured to control the operation of the one or more pedestal heaters 62 to generate thermal energy during a semiconductor process (as the chemical process). In one form, the thermal controller 110 includes a power source 112, a power converter system 114, and a heater control module 116. The power source 112 is configured to provide an input voltage (e.g., 240V, 208V) to the power converter system 114 by way of, for example, an interlock (not shown) that is operable by the heater control module 116 as a safety mechanism to shut-off power from the power source 112.

[0042] The power converter system 114 is configured to adjust the input voltage based on a control signal received from the heater control module 116 and apply an output voltage (VOUT) to the one or more pedestal heaters 62. In one form, the power converter system 114 includes a plurality of power converters that are configured to apply an adjustable power to the resistive heating elements of the one or more pedestal heaters 62 based on the control signal. An example power converter system is described in co-pending application U.S. Serial No. 15/624,060, filed June 15, 2017 and titled “POWER CONVERTER FOR A THERMAL SYSTEM”, which is commonly owned with the present application and the contents of which are incorporated herein by reference in its entirety. In this example, each power converter includes a buck converter that is operable by the heater controller to generate a desired output voltage for one or more heating elements of a given zone. Accordingly, the power converter system is operable to provide a customizable amount of power (i.e., a desired power) to each of the one or more pedestal heaters 62. It should be readily understood that other power converter systems may be employed for providing the desired power and the present disclosure is not limited to the example provided herein.

[0043] In one form, the heater control module 116 is configured to generate and provide the control signal to the power converter system 114 based on the pedestal sensor data generated by the pedestal sensors 64. As an example and in response to receiving the chemical process recipe from the recipe module 105, the heater control module 116 is configured to generate and provide a control signal for adjusting a duty cycle of the power converter system 114 to thereby ramp up or ramp down an output voltage applied to the pedestal heaters 62 based on the recipe. In response to receiving the output voltage, the one or more pedestal heaters 62 are configured to generate thermal energy for controlling, for example, the temperature of the wafer 48 during the semiconductor process. In one form, the heater control module 116 is configured to determine an electrical characteristic of the pedestal heaters 62 based on the pedestal sensor data generated by the pedestal sensors 64. Furthermore, the heater control module 116 is configured to store the determined electrical characteristic of the pedestal heaters 62 in the response characteristic database 120 along with a corresponding timestamp. As described below in further detail, the chemical processing controller 125 may determine whether the semiconductor process is operating in a steady state based on the data stored in the response characteristic database 120.

[0044] In one form and referring to FIG. 3, the state module 130 obtains steady state data and determines whether the semiconductor process is operating in a steady state based on the steady state data. The steady state data is based on a temperature of the wafer 48 as indicated by the pedestal sensor data and/or the chemical process defined by the recipe module 105. In one form, the state module 130 determines whether the semiconductor process is operating in the steady state in response to the pedestal heaters 62 generating thermal energy. The state module 130 may obtain baseline steady state data when the internal wall surface 42B of the chamber 46 is clean (e.g., generally free of contaminants, such as after a wet cleaning process of the internal wall surface 42B or when the chamber 46 is new) and therefore does not have an appreciable amount of polymer build-up 70. As described below in further detail, the response characteristic module 140 may determine a response characteristic based on a comparison between the baseline steady state data and steady state data that is obtained after one or more semiconductor process cycles are completed.

[0045] As an example, the state module 130 obtains the type of chemical process recipe (e.g., a dry etching routine) from the recipe module 105 and determines that the semiconductor process is operating in the steady state after a predetermined period of time has elapsed and after the pedestal heaters 62 have initiated the generation of thermal energy defined by the chemical process recipe (e.g., ramping up the temperature of the wafer 48). As another example, the state module 130 determines the semiconductor process is operating in the steady state when the temperature of the wafer 48 has stabilized or settled about a setpoint temperature defined by the chemical process recipe (as indicated by the pedestal sensor data).

[0046] In one form, the response characteristic module 140 determines a response characteristic of the semiconductor processing environment 5-1 in response to the pedestal heaters 62 generating thermal energy and/or the state module 130 determining that the semiconductor process is operating in a steady state. In one form, the response characteristic includes an operational characteristic of the pedestal heater 62 and/or a wall characteristic associated with the at least one external wall surface 42A of the semiconductor processing chamber 10-1. As an example, the operational characteristic of the pedestal heater 62 may be an electrical characteristic of the pedestal heater 62 (e.g., voltage and/or current changes), a temperature characteristic of the pedestal heater 62 (e.g., a temperature change), a performance characteristic of the pedestal heater 62, or a combination thereof. Furthermore, the wall characteristic of the at least one external wall surface 42A may be a temperature characteristic (e.g., a temperature change) and/or a heat flux characteristic (e.g., a heat flux change) of the at least one external wall surface 42A. Additional details regarding the electrical characteristic, the temperature characteristic, the wall characteristic, and the heat flux characteristic are provided below.

[0047] As an example, the response characteristic module 140 determines a voltage change of the pedestal heater 62 (as the electrical characteristic of the pedestal heater 62) when the semiconductor process is operating in the steady state. To determine the voltage change of the pedestal heater 62, the response characteristic module 140 obtains a steady state voltage of the pedestal heater 62 from the heater control module 116 and a previous steady state voltage of the pedestal heater 62 determined by the heater control module 116 and stored in the response characteristic database 120 (i.e., a steady state voltage having a preceding timestamp). As an example, the response characteristic module 140 determines the voltage change of the pedestal heater 62 based on a difference/trend the obtained or measured steady state voltage and a baseline steady state voltage stored in the response characteristic database 120 (i.e., the steady state voltage when the semiconductor processing chamber 10-1 is clean and does not have an appreciable amount of polymer build-up 70). Subsequently, the response characteristic module 140 determines the voltage change based on the difference/trend the steady state voltage and the previous steady state voltage.

[0048] As another example, the response characteristic module 140 determines a current change of the pedestal heater 62 (as the electrical characteristic of the pedestal heater 62) when the semiconductor process is operating in the steady state. To determine the current change of the pedestal heater 62, the response characteristic module 140 obtains a steady state current of the pedestal heater 62 from the heater control module 116 and a previous steady state current of the pedestal heater 62 determined by the heater control module 116 and stored in the response characteristic database 120 (i.e., a steady state current having a preceding timestamp). As an example, the response characteristic module 140 determines the current change of the pedestal heater 62 based on a difference/trend the obtained or measured steady state current and a baseline steady state current stored in the response characteristic database 120 (i.e., the steady state current when the semiconductor processing chamber 10-1 is clean and does not have an appreciable amount of polymer build-up 70). Subsequently, the response characteristic module 140 determines the current change based on the difference/trend the steady state current and the previous steady state current.

[0049] As yet another example, the response characteristic module 140 determines a temperature characteristic of the at least one external wall surface 42A (as the wall characteristic) when the one or more external wall surface sensors 50 include a temperature sensor. To determine the temperature characteristic of the at least one external wall surface 42A, the response characteristic module 140 determines a steady state temperature of the external wall surface 42A (i.e., a temperature of the external wall surface 42A when the semiconductor process is in the steady state) based on the temperature data generated by the temperature sensor (as the one or more external wall surface sensors 50). Furthermore, the response characteristic module 140 obtains a previous steady state temperature determined by the response characteristic module 140 and stored in the response characteristic database 120 (i.e., a steady state temperature having a preceding timestamp, such as a baseline steady state temperature when the semiconductor processing chamber 10-1 is clean and does not have an appreciable amount of polymer build-up 70) and determines the temperature characteristic based on the difference/trend the steady state temperature and the previous steady state temperature. [0050] As an additional example, the response characteristic module 140 determines a heat flux characteristic of the at least one external wall surface 42A (as the wall characteristic) when the one or more external wall surface sensors 50 include a heat flux sensor. To determine the heat flux characteristic of the at least one external wall surface 42A, the response characteristic module 140 determines a steady state heat flux of the external wall surface 42A (i.e., a heat flux of the external wall surface 42A when the semiconductor process is in the steady state) based on the heat flux data generated by the heat flux sensor (as the one or more external wall surface sensors 50). Furthermore, the response characteristic module 140 obtains a previous steady state heat flux determined by the response characteristic module 140 and stored in the response characteristic database 120 (i.e., a steady state heat flux having a preceding timestamp, such as a baseline steady state heat flux when the semiconductor processing chamber 10-1 is clean and does not have an appreciable amount of polymer build-up 70) and determines the heat flux characteristic based on the difference/trend the steady state heat flux and the previous steady state heat flux.

[0051] In one form, the correlation module 150 correlates the response characteristic to an amount of polymer build-up 70 (e.g., a volume, thickness, and/or profile) within the semiconductor processing chamber 10-1 based on a response characteristic-polymer build-up correlation (RCPBC) model stored in the RCPBC database 160 and an emissivity range of the polymer build-up 70. In one form, the RCPBC model is a table that maps the response characteristic (e.g., the operational characteristic of the pedestal heater 62 and/or a wall characteristic associated with the at least one external wall surface 42A of the semiconductor processing chamber 10- 1 ) and known emissivity ranges of the polymer build-up 70 (e.g., 0 to 1 , where an emissivity value of 0 corresponds to a perfect reflector, and an emissivity value of 1 corresponds to a perfect emitter) to an amount of the polymer build-up 70. The known emissivity range of the polymer build-up 70 may be defined based on, for example, the type of the polymer build-up 70. The RCPBC database 160 may store a plurality of RCPBC models for various emissivity ranges and wall characteristic types.

[0052] As an example, the RCPBC model is an empirically defined and/or mathematically based model that maps steady state voltage and/or current changes and known emissivity ranges of the polymer build-up to the amount of polymer build-up 70. As another example, the RCPBC model is an empirically defined and/or mathematically based model that maps steady state temperature and/or heat flux changes (as the wall characteristic) and known emissivity ranges of the polymer build-up 70 to the amount of polymer build-up 70.

[0053] In one form, the RCPBC model is a machine learning model, such as an artificial neural network model, a convolutional neural network model, and/or other similar machine learning model. Accordingly, the correlation module 150 may be configured to perform a machine learning routine, such as a supervised learning routine, an unsupervised learning routine, a reinforcement learning routine, selflearning routine, and/or black-box modeling routine based on the RCPBC model to determine the amount of polymer build-up 70.

[0054] As an example, the RCPBC model is a supervised learning model, such as a multiple regression model or a multivariate regression model (e.g., a linear regression model, a logistic regression model, a ridge regression model, a lasso regression model, a polynomial regression model, and/or a Bayesian linear regression model, among other regression models). That is, when the correlation module 150 performs a supervised learning routine based on the RCPBC, the correlation module 150 may correlate a known emissivity range of the polymer buildup 70 and at least one of the voltage change, current change, heat flux change, and the temperature change to the amount of the polymer build-up 70. Furthermore, the correlation module 150 may iteratively perform the supervised learning routine for various amounts of the polymer build-up 70, emissivity ranges, and wall characteristics to improve the accuracy of the RCPBC.

[0055] As another example, the RCPBC model is an unsupervised learning model, such as a clustering model. That is, when the correlation module 150 performs an unsupervised learning routine based on the RCPBC, the correlation module 150 may generate a feature vector having any number of dimensions (e.g., an n-dimensional vector) based on a known emissivity range of the polymer build-up 70 and at least one of the voltage change, current change, heat flux change, and the temperature change. The correlation module 150 may then group the feature vectors into a plurality of clusters by performing a connectivity-based clustering routine, a selforganizing map (SOM) clustering routine, a centroid-based clustering routine, a density-based clustering routine, among others), or a distribution-based clustering routine. Subsequently, the correlation module 150 may categorize the polymer buildup 70 into one or more polymer build-up amount ranges based on the clusters by, for example, performing a dimension reduction routine (e.g., principal component analysis ((PCA) routine) to reduce the number of dimensions of the clusters to a predetermined number of dimensions having the largest feature influence and to categorize the clusters into one or more polymer build-up amount ranges.

[0056] In one form, the corrective action module 170 is configured to selectively perform a corrective action based on the amount of polymer build-up 70. As an example, the corrective action may include instructing the HMI 180 to generate a notification when the amount of polymer build-up 70 is greater than a threshold value. The notification may include information indicating the amount of polymer buildup 70 and/or operator instructions for addressing the excessive polymer build-up 70 (e.g., operator instructions for providing a cleaning/oxidizing gas into the semiconductor processing chamber 10-1 or initiating a wet cleaning routine). As another example, the corrective action may include instructing the recipe module 105 to adjust one or more parameters of the semiconductor process recipe, such as gas temperatures and/or one or more setpoint operational characteristics of the fluid line heaters 32 and/or the pedestal heaters 62.

[0057] To perform the functionality described herein, the HMI 180 may be provided by a computing device (e.g., a smartphone, a laptop, a desktop computing device, a programmable logic controller, a tablet, among others) that include various visual interfaces (e.g., a touchscreen, a display monitor, an augmented reality device, and/or a plurality of light-emitting diodes (LEDs)), auditory interfaces (e.g., a speaker circuit for auditorily outputting messages corresponding to the notification), and/or haptic interfaces (e.g., a vibration motor circuit that selectively vibrates).

[0058] In one form, the corrective action module 170 is configured to perform the corrective action based on the amount of polymer build-up 70 and based on a machine learning routine, such as a supervised learning routine, an unsupervised learning routine, a reinforcement learning routine, self-learning routine, and/or blackbox modeling routine to select the appropriate corrective action. As an example, and as shown in FIG. 4B, corrective action module 170-1 (as the corrective action module 170) is configured to perform a reinforcement learning routine to select an appropriate corrective action based on the amount of polymer build-up 70. In one form, the corrective action module 170-1 includes a state vector module 171 , a state-corrective action module 172, a reward module 173, an entry generation module 174, a statecorrective action database 175, and a target corrective action module 176. In one form, the state vector module 171 generates a plurality of state vectors, where each state vector indicates, for a given discrete time value, the amount of polymer build-up 70.

[0059] In one form, the state-corrective action module 172 defines a plurality of corrective actions associated with the state vectors. The plurality of corrective actions may include, but are not limited to, instructing the gas source 22 to provide a cleaning/oxidizing gas into the semiconductor processing chamber 10-1 , instructing the gas source 22 to initiate a wet cleaning routine, adjusting a gas temperature, adjusting one or more setpoint operational characteristics of the fluid line heaters 32, adjusting one or more setpoint operational characteristics of the pedestal heaters 62, discontinuing the supply of power to the pedestal heaters 62 via an interlock (not shown), and a state-remain action. As used herein, “state-remain action” refers to refraining from performing a corrective action. In one form, the statecorrective action module 172 defines a corrective action for various amounts of polymer build-up 70 for each corrective action type.

[0060] In one form, the reward module 173 is configured to determine a reward for each corrective action using known reinforcement learning routines (e.g., Q-learning routines having a learning rate between 0 and 1). The reward value is indicative of a qualitative and/or quantitative metric associated with the predicted resulting change of the chamber throughput, an efficiency of the semiconductor processing system 5-1 , or a combination thereof. As an example, larger reward values may correspond to improved qualitative/quantitative metrics associated with the resulting chamber throughput and/or efficiency of the semiconductor processing system 5-1 , and smaller reward values may correspond to worsened qualitative/quantitative metrics associated with the resulting chamber throughput and/or efficiency of the semiconductor processing system 5-1 .

[0061] In one form, the entry generation module 174 associates each of the corrective actions generated by the state-corrective action module 172 and the corresponding reward value generated by the reward module 173. In one form, the entry generation module 174 generates an entry for each pair of state-corrective actions and reward values and stores the generated entries in the state-corrective action database 175. In one form, the target action module 176, when sufficiently trained, autonomously selects the corrective action to be performed based on the entries of the state-corrective action database 175 and the associated reward value. [0062] Referring to FIG. 5A, a flowchart illustrating a routine 500 for monitoring polymer build-up within the chemical processing chamber 10 is shown. At 504, the chemical processing control system 100 generates thermal energy during a chemical process. At 508, the chemical processing control system 100 determines a response characteristic in response to generating the thermal energy. At 512, the chemical processing control system 100 correlates the response characteristic to an amount of polymer build-up within the chemical processing chamber 10 based on the RCPBC model and an emissivity range of the polymer build-up.

[0063] Referring to FIG. 5B, a flowchart illustrating a routine 550 for monitoring the polymer build-up 70 within the semiconductor processing chamber 10- 1 is shown. At 554, the SPSCS 100-1 generates thermal energy during a semiconductor process. At 558, the SPSCS 100-1 determines a response characteristic in response to generating the thermal energy. At 562, the SPSCS 100- 1 correlates the response characteristic to an amount of polymer build-up within the semiconductor processing chamber 10-1 based on the RCPBC model and an emissivity range of the polymer build-up 70.

[0064] Referring to FIG. 6A, a flowchart illustrating a routine 600 for monitoring polymer build-up within the chemical processing chamber 10 is shown. At 604, the chemical processing control system 100 generates thermal energy during a chemical process. At 608, the chemical processing control system 100 determines whether the chemical process is operating in a steady state based on steady state data of the chemical processing chamber 10. If the chemical process is not operating in the steady state, the routine 600 proceeds to 604. If the chemical process is operating in the steady state at 608, the routine 600 proceeds to 612, where the chemical processing control system 100 determines a response characteristic. At 616, the chemical processing control system 100 correlates the response characteristic to an amount of polymer build-up within the chemical processing chamber based on the RCPBC model and an emissivity range of the polymer build-up. At 620, the chemical processing control system 100 selectively performs a corrective action based on the amount of polymer build-up.

[0065] Referring to FIG. 6B, a flowchart illustrating a routine 650 for monitoring polymer build-up within the semiconductor processing chamber 10-1 is shown. At 654, the SPSCS 100-1 generates thermal energy during a semiconductor process. At 658, SPSCS 100-1 determines whether the semiconductor process is operating in a steady state based on steady state data of the semiconductor processing chamber 10-1. If the semiconductor process is not operating in the steady state, the routine 650 proceeds to 654. If the semiconductor process is operating in the steady state at 658, the routine 650 proceeds to 662, where SPSCS 100-1 determines a response characteristic. At 666, SPSCS 100-1 correlates the response characteristic to an amount of polymer build-up 70 within the semiconductor processing chamber 10-1 based on the RCPBC model and an emissivity range of the polymer build-up 70. At 670, the SPSCS 100-1 selectively performs a corrective action based on the amount of polymer build-up.

[0066] The present disclosure described herein provides systems and methods for monitoring polymer build-up within a chemical processing chamber. A control system generates thermal energy during a chemical process and determines a response characteristic in response to generating the thermal energy. The response characteristic includes an operational characteristic associated with the heater, a wall characteristic associated with at least one external wall surface of the chemical processing chamber, or a combination thereof. The control system correlates the response characteristic to an amount of polymer build-up within the chemical processing chamber based on a response characteristic-polymer build-up correlation model and an emissivity range of the polymer build-up. Accordingly, the control system performs an in-situ-based monitoring routine to accurately monitor polymer thickness and thereby improve wafer yield, inhibit wafer defects, and inhibit undesirable shifts in a chemical process (e.g., a semiconductor process) to accommodate for the polymer deposits. Furthermore, the control system improves the chemical processing system’s efficiency as it relates to, for example, cycle times and/or a number of wafers produced during a given time period

[0067] Unless otherwise expressly indicated herein, all numerical values indicating mechanical/thermal properties, compositional percentages, dimensions and/or tolerances, or other characteristics are to be understood as modified by the word “about” or "approximately" in describing the scope of the present disclosure. This modification is desired for various reasons including industrial practice, material, manufacturing, and assembly tolerances, and testing capability.

[0068] As used herein, the phrase at least one of A, B, and C should be construed to mean a logical (A OR B OR C), using a non-exclusive logical OR, and should not be construed to mean “at least one of A, at least one of B, and at least one of C.”

[0069] In this application, the term “controller” and/or “module” may refer to, be part of, or include: an Application Specific Integrated Circuit (ASIC); a digital, analog, or mixed analog/digital discrete circuit; a digital, analog, or mixed analog/digital integrated circuit; a combinational logic circuit; a field programmable gate array (FPGA); a processor circuit (shared, dedicated, or group) that executes code; a memory circuit (shared, dedicated, or group) that stores code executed by the processor circuit; other suitable hardware components that provide the described functionality; or a combination of some or all of the above, such as in a system-on- chip.

[0070] The term memory is a subset of the term computer-readable medium. The term computer-readable medium, as used herein, does not encompass transitory electrical or electromagnetic signals propagating through a medium (such as on a carrier wave); the term computer-readable medium may therefore be considered tangible and non-transitory. Non-limiting examples of a non-transitory, tangible computer-readable medium are nonvolatile memory circuits (such as a flash memory circuit, an erasable programmable read-only memory circuit, or a mask readonly circuit), volatile memory circuits (such as a static random access memory circuit or a dynamic random access memory circuit), magnetic storage media (such as an analog or digital magnetic tape or a hard disk drive), and optical storage media (such as a CD, a DVD, or a Blu-ray Disc).

[0071] The apparatuses and methods described in this application may be partially or fully implemented by a special purpose computer created by configuring a general-purpose computer to execute one or more particular functions embodied in computer programs. The functional blocks, flowchart components, and other elements described above serve as software specifications, which can be translated into the computer programs by the routine work of a skilled technician or programmer.

[0072] The description of the disclosure is merely exemplary in nature and, thus, variations that do not depart from the substance of the disclosure are intended to be within the scope of the disclosure. Such variations are not to be regarded as a departure from the spirit and scope of the disclosure.

Claims

CLAIMS What is claimed is:

1 . A method for monitoring polymer build-up within a chemical processing chamber and in response to generating thermal energy during a chemical process, the method comprising: determining a response characteristic in response to generating the thermal energy, wherein the response characteristic includes an operational characteristic associated with a heater, a wall characteristic associated with at least one external wall surface of the chemical processing chamber, or a combination thereof; and correlating the response characteristic to an amount of polymer build-up within the chemical processing chamber based on a response characteristic-polymer build-up correlation model and an emissivity range of the polymer build-up.

2. The method according to Claim 1 further comprising: obtaining steady state data, wherein the steady state data is based on a temperature of a wafer of the chemical processing chamber, a chemical process recipe, or a combination thereof; determining whether the chemical process is operating in a steady state based on the steady state data; and determining the response characteristic in response to determining the chemical process is operating in the steady state.

3. The method according to Claim 2, wherein the operational characteristic is an electrical characteristic of the heater.

4. The method according to Claim 3, wherein the electrical characteristic is a voltage change of the heater when the chemical process is operating in the steady state, a current change of the heater when the chemical process is operating in the steady state, or a combination thereof.

5. The method according to Claim 4 further comprising: obtaining a steady state voltage of the heater in response to the chemical process operating in the steady state; and determining the electrical characteristic of the heater based on a difference between the steady state voltage and a previous steady state voltage of the heater stored in a database.

6. The method according to Claim 4 further comprising: obtaining a steady state current of the heater in response to the chemical process operating in the steady state; and determining the current change of the heater based on a difference between the steady state current and a previous steady state current of the heater stored in a database.

7. The method according to Claim 2, wherein the wall characteristic is one of a temperature characteristic of the at least one external wall surface and a heat flux characteristic of the at least one external wall surface.

8. The method according to Claim 7 further comprising: obtaining a steady state temperature of the at least one external wall surface in response to the chemical process operating in the steady state; and determining the temperature characteristic of the at least one external wall surface based on a difference between the steady state temperature and a previous steady state temperature of the at least one external wall surface stored in a database.

9. The method according to Claim 8, wherein the steady state temperature of the at least one external wall surface is obtained from a temperature sensor.

10. The method according to Claim 7 further comprising: obtaining a steady state heat flux of the at least one external wall surface in response to the chemical process operating in the steady state; and determining the heat flux characteristic of the at least one external wall surface based on a difference between the steady state heat flux and a previous steady state heat flux of the at least one external wall surface stored in a database.

11 . The method according to Claim 9, wherein the steady state heat flux of the at least one external wall surface is obtained from a heat flux sensor.

12. The method according to Claim 1 further comprising selectively performing a corrective action based on the amount of polymer build-up.

13. The method according to Claim 12, wherein the corrective action includes generating a notification based on the amount of polymer build-up, adjusting one or more parameters of the chemical process, or a combination thereof.

14. The method according to Claim 1 , wherein the chemical process is a semiconductor process.

15. The method according to Claim 1 , wherein the chemical processing chamber is a semiconductor processing chamber.

16. A system for monitoring polymer build-up within a chemical processing chamber, the system comprising: a heater configured to generate thermal energy during a chemical process; the chemical processing chamber comprising a wafer and at least one external wall surface; and a control system comprising a chemical processing controller, a thermal controller, or a combination thereof, the control system configured to: determine whether the chemical process is operating in a steady state based on steady state data of the chemical processing chamber, wherein the steady state data is based on a temperature of the wafer, a chemical process recipe, or a combination thereof; determine a response characteristic when the chemical process is operating in a steady state and in response to the heater generating the thermal energy, wherein the response characteristic includes an operational characteristic associated with the heater, a wall characteristic associated with the at least one external wall surface, or a combination thereof; correlate the response characteristic to an amount of polymer build-up within the chemical processing chamber based on a response characteristic- polymer build-up correlation model and an emissivity range of the polymer build-up; and selectively perform a corrective action based on the amount of polymer build-up.

17. The system according to Claim 16, wherein the operational characteristic is an electrical characteristic of the heater.

18. The system according to Claim 17, wherein the electrical characteristic is a voltage change of the heater when the chemical process is operating in the steady state, a current change of the heater when the chemical process is operating in the steady state, or a combination thereof.

19. The system according to Claim 18, wherein the control system is configured to: obtain a steady state voltage of the heater in response to the chemical process operating in the steady state; and determine the electrical characteristic of the heater based on a difference between the steady state voltage and a previous steady state voltage of the heater stored in a database.

20. The system according to Claim 18, wherein the control system is configured to: obtain a steady state current of the heater in response to the chemical process operating in the steady state; and determine the current change of the heater based on a difference between the steady state current and a previous steady state current of the heater stored in a database.

21 . The system according to Claim 16, wherein the wall characteristic is one of a temperature characteristic of the at least one external wall surface and a heat flux characteristic of the at least one external wall surface.

22. The system according to Claim 21 , wherein the control system is configured to: obtain a steady state temperature of the at least one external wall surface in response to the chemical process operating in the steady state; and determine the temperature characteristic of the at least one external wall surface based on a difference between the steady state temperature and a previous steady state temperature of the least one external wall surface stored in a database.

23. The system according to Claim 22, wherein the steady state temperature of the at least one external wall surface is obtained from a temperature sensor disposed on the wall.

24. The system according to Claim 21 , wherein the control system is configured to: obtain a steady state heat flux of the least one external wall surface in response to the chemical process operating in the steady state; and determine the heat flux characteristic of the least one external wall surface based on a difference between the steady state heat flux and a previous steady state heat flux of the least one external wall surface stored in a database.

25. The system according to Claim 24, wherein the steady state heat flux of the least one external wall surface is obtained from a heat flux sensor disposed on the wall.

26. The system according to Claim 16, wherein the corrective action includes generating a notification based on the amount of polymer build-up, adjusting one or more parameters of the chemical process, or a combination thereof.

27. The system according to Claim 16, wherein the chemical process is a semiconductor process.

28. The system according to Claim 16, wherein the chemical processing chamber is a semiconductor processing chamber.

29. A method for monitoring polymer build-up within a chemical processing chamber, the chemical processing chamber comprising a wafer and at least one external wall surface, the method comprising: generating, by a heater, thermal energy during a chemical process; determining, by a control system, whether the chemical process is operating in a steady state based on steady state data of the chemical processing chamber, wherein the steady state data is based on a temperature of the wafer, a chemical process recipe, or a combination thereof; determining, by the control system, a response characteristic when the chemical process is operating in the steady state and in response to the heater generating the thermal energy, wherein the response characteristic includes an operational characteristic associated with the heater, a wall characteristic associated with the at least one external wall surface, or a combination thereof; correlating, by the control system, the response characteristic to an amount of polymer build-up within the chemical processing chamber based on a response characteristic-polymer build-up correlation model and an emissivity range of the polymer build-up; and selectively performing, by the control system, a corrective action based on the amount of polymer build-up.