Intelligent dynamic load emulator for RF power delivery control system

Abstract

Embodiments disclosed herein include a dynamic load simulator. In an embodiment, the dynamic load simulator comprises: an impedance load; reversely matching the network; and an intelligent RF controller. In an embodiment, the smart RF controller includes: a dynamic load generator; and a reverse matching controller.

Description

[0001] CROSS-REFERENCE TO RELATED APPLICATIONS

[0002] This application claims priority to U.S. patent application No. 17 / 843,830 filed on June 17, 2022, and the entire contents of the above-mentioned U.S. patent application are incorporated into this application by reference. Technical Field

[0003] Embodiments relate to the field of semiconductor manufacturing, and more particularly, to a dynamic load simulator for RF power delivery control.

[0004] Description of the Prior Art

[0005] In semiconductor processing operations (e.g., plasma etching or plasma deposition), an RF delivery system is used to provide RF power to the chamber. Typically, the RF delivery system includes an RF generator and an RF matching network (sometimes simply referred to as matching). The RF matching network allows the input impedance to match the impedance of the plasma chamber in order to minimize or eliminate reflected power. As a result, higher levels of power can be delivered to the plasma chamber. Impedance matching of the power supply and the process chamber load is a key requirement for the performance and safety of RF power delivery and wafer processing. The chamber load is a key design factor that defines the operating envelope as well as the dynamics of the power delivery system.

[0006] Current RF system development relies on some fixed or variable dummy loads. Using such systems allows basic authentication of RF systems. However, such simplistic impedance load architectures are limited because they cannot accurately match the impedance load characteristics of the plasma chamber. Accordingly, extensive and in-depth processing chamber testing is required for comprehensive system validation. This leads to scheduling, resource and cost challenges. Generally speaking, it is very costly to take the processing chamber offline in order to perform system validation of the RF system. Summary of the invention

[0007] In semiconductor processing operations (e.g., plasma etching or plasma deposition), an RF delivery system is used to provide RF power to the chamber. Typically, the RF delivery system includes an RF generator and an RF matching network (sometimes simply referred to as matching). The RF matching network allows the input impedance to match the impedance of the plasma chamber in order to minimize or eliminate reflected power. As a result, higher levels of power can be delivered to the plasma chamber. Impedance matching of the power supply and the process chamber load is a key requirement for the performance and safety of RF power delivery and wafer processing. The chamber load is a key design factor that defines the operating envelope as well as the dynamics of the power delivery system.

[0008] Current RF system development relies on some fixed or variable dummy loads. Using such systems allows basic authentication of RF systems. However, such simplistic impedance load architectures are limited because they cannot accurately match the impedance load characteristics of the plasma chamber. Accordingly, extensive and in-depth processing chamber testing is required for comprehensive system validation. This leads to scheduling, resource and cost challenges. Generally speaking, it is very costly to take the processing chamber offline in order to perform system validation of the RF system. BRIEF DESCRIPTION OF THE DRAWINGS

[0009] Figure 1 is a schematic diagram of a processing tool including an RF generator, RF matching, and a plasma chamber according to an embodiment.

[0010] Figure 2A is a schematic diagram of a smart dynamic load emulator with an RF controller, a reverse matching network, and a dummy load according to an embodiment.

[0011] Figure 2B is a schematic diagram of an intelligent dynamic load emulator having an RF controller, a reverse matching network having a VI sensor, and a dummy load according to an embodiment.

[0012] Figure 3 is a schematic diagram of a processing tool having an RF generator, RF matching, a processing chamber, and a smart dynamic load simulator according to an embodiment.

[0013] Figure 4 is a diagram of a software stack for a smart dynamic load simulator according to an embodiment.

[0014] Figure 5 is a diagram illustrating a use case of a smart dynamic load simulator according to an embodiment.

[0015] Figure 6 A block diagram of an exemplary computer system that may be used in conjunction with a processing tool according to an embodiment is illustrated. DETAILED DESCRIPTION

[0016] The systems described herein include a dynamic load simulator for RF power delivery control. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the embodiments. It will be apparent to those skilled in the art that the embodiments can be implemented without these specific details. In other cases, well-known aspects have not been described in detail to avoid unnecessarily obscuring the embodiments. Furthermore, it should be understood that the various embodiments illustrated in the drawings are exemplary representations and are not necessarily drawn to scale.

[0017] As described above, impedance matching of the power supply and the process chamber load is a critical requirement for the performance and safety of RF power delivery and substrate processing. However, existing architectures require extensive verification of the process chamber coupled to the power supply and matching. Since the process chamber is used to verify the power supply, the cost of verifying the power supply is high. That is, when used for verification, the process chamber needs to be offline and the process chamber cannot be used to manufacture production substrates or wafers. In general, when a chamber is taken offline for verification purposes, scheduling, resource allocation and cost challenges must be addressed.

[0018] Accordingly, embodiments disclosed herein include an intelligent dynamic load emulator. The intelligent dynamic load emulator includes a dummy load, a reverse match, and an intelligent RF controller. The intelligent RF controller controls the reverse match to generate a variable impedance trace from the dummy load. The variable impedance trace may be similar to the impedance trace of the processing chamber during operation. Therefore, the RF delivery system (i.e., the RF generator and the RF match) may be electrically coupled to the intelligent dynamic load emulator instead of the processing chamber. Therefore, the processing chamber does not need to be offline for verification purposes.

[0019] In embodiments, various methods may be used to generate the impedance trace. In one method, the impedance trace of a functional plasma chamber is recorded. The smart RF controller may then utilize the recorded impedance trace. In other embodiments, the impedance trace may be generated using a chamber modeling algorithm. That is, the smart RF controller may be used as a digital (impedance) twin of the process chamber in order to provide an impedance trace that matches the impedance trace that the chamber would present under certain parameters. This is particularly useful when investigating corner cases. Extreme conditions may be simulated in order to validate the RF delivery system, rather than pushing to the limits of the process chamber.

[0020] In addition, it should be understood that the use of the intelligent dynamic load simulator can be used in a variety of applications. For example, the intelligent dynamic load simulator can be used throughout the control system life cycle, such as during the development, testing, and operation phases. Accordingly, the cost of the intelligent dynamic load simulator can be spread over a number of different use cases.

[0021] Reference now Figure 1 , a schematic diagram of a semiconductor processing tool 100 is illustrated according to one embodiment. In an embodiment, the semiconductor processing tool 100 may include an RF generator 105. The RF generator 105 may be any suitable RF generator architecture. For example, the RF generator 105 may operate at any desired frequency or frequency range. In a particular embodiment, the RF generator 105 may operate at 13.56 MHz, which is a common frequency for plasma generation. However, it should be understood that other frequencies may also be used.

[0022] In an embodiment, the RF generator 105 may be electrically coupled to an RF matching network 107. The RF matching network 107 may be referred to as an RF match or simply a match. In an embodiment, the match 107 may include circuitry (e.g., a capacitor, an inductor, etc.) configured to provide a desired input impedance to the RF generator 105. In a particular embodiment, the capacitor may include a variable capacitor configured to have a capacitance value that is changed by an actuator, etc. The match 107 may be used to set an impedance equal to the impedance of the load. The load impedance may be determined by the operating conditions of the processing chamber 120.

[0023] In an embodiment, the processing chamber 120 can be any semiconductor processing tool. For example, the processing chamber 120 can be an etching tool, a deposition tool, a surface treatment tool, etc. In a specific embodiment, the processing chamber 120 can be a plasma tool. For example, a plasma 124 can be generated within the chamber enclosure 121. The plasma 124 can be initiated by one or more electrodes. For example, the support 122 can include an electrode electrically coupled to the RF match 107. A second electrode 123 can be provided opposite the support 122. The second electrode 123 can also be coupled to an RF source (not shown).

[0024] In an embodiment, the support 122 may include a pedestal or other chuck structure. For example, the support 122 may include an electrostatic chuck structure to secure the substrate 125. However, in some embodiments, other chuck structures (e.g., a vacuum chuck) may also be used. In an embodiment, the support 122 may also include a thermal control system to control the temperature of the substrate 125. For example, the support 122 may include cooling channels and / or resistive heaters.

[0025] In an embodiment, the substrate 125 may be any suitable substrate form factor and / or material. For example, the substrate 125 may be a wafer having a 300 mm diameter, a 450 mm diameter, or any other standard wafer form factor. In a particular embodiment, the substrate 125 may include silicon or any other semiconductor material. In an embodiment, a layer may be deposited onto the substrate 125, or a layer on the substrate 125 may be in the process of being etched. For example, layers commonly used in semiconductor manufacturing include oxides (e.g., silicon oxide), nitrides (e.g., silicon nitride), metals (e.g., copper, tungsten, etc.), etc.

[0026] Reference now Figure 2A, a schematic diagram of an intelligent dynamic load emulator 240 is shown according to an embodiment. In an embodiment, the intelligent dynamic load emulator 240 may include an impedance load. For example, a dummy load 245 may be provided. In some embodiments, the dummy load 245 may be a static load. That is, the impedance of the dummy load 245 may remain substantially constant. However, in other embodiments, the dummy load 245 may be variable. The impedance of the dummy load 245 may be a real impedance value or a complex impedance value. In an embodiment, the dummy load 245 may include a thermal regulation feature. For example, fan cooling, liquid cooling, etc. may be used to control the temperature of the dummy load 245. In an embodiment, the dummy load 245 may have any specific impedance value.

[0027] In an embodiment, the smart dynamic load simulator 240 may further include a reverse matching network 244. Sometimes, the reverse matching network 244 may be referred to as reverse matching 244. The reverse matching network 244 may have a circuit system similar to the circuit system of the matching 107 (described in more detail above). For example, the reverse matching 244 may include capacitors, inductors, etc. In a specific embodiment, the capacitor may include a variable capacitor configured to have a capacitance value changed by an actuator, etc. In another embodiment, the capacitor may be a solid-state variable capacitor. Since the capacitance in a solid-state variable capacitor changes faster than a capacitor with a physical actuator, the use of a solid-state variable capacitor may facilitate feedback tuning of the load generator. Even when the dummy load 245 is constant, the reverse matching network 244 allows a variable impedance to be provided. In this way, an impedance trace can be generated to match the impedance of the chamber 120. As will be described in more detail below, this allows the RF delivery system to be developed and tested without using the plasma chamber 120.

[0028] In an embodiment, the reverse matching network 244 can be electrically coupled to an RF delivery system (not shown). The reverse matching network 244 can be coupled to the RF delivery system to facilitate development and / or testing of the RF delivery system. In some embodiments, the reverse matching network 244 can also be used during operation of the RF delivery system while processing a substrate in a processing chamber. As will be described in more detail below, the RF delivery system can switch between the reverse matching network 244 of the plasma chamber and the smart dynamic load simulator 240.

[0029] In an embodiment, the intelligent dynamic load emulator 240 may further include a smart RF controller 241. The smart RF controller 241 may include a dynamic load generator 243 and a reverse matching controller 242. In an embodiment, the dynamic load generator 243 may include an algorithm or model that generates a load impedance output based on inputs (including a dummy load value, RF delivery system parameters, and / or other desired or measured processing parameters). In an embodiment, the dynamic load generator 243 may operate in various modes. In a first mode, the dynamic load generator 243 may operate under a constant load. For example, the constant load may be equal to the impedance load of the dummy load 245.

[0030] In the second mode, the dynamic load generator 243 may operate under a variable static load, that is, the impedance load may be set to a static value, and the static value may change over time.

[0031] In a third mode, the dynamic load generator 243 may operate with a predetermined impedance load trace. For example, the impedance load of the process chamber 120 may be recorded during a process recipe. The recorded impedance load may then be replicated by the dynamic load generator 244.

[0032] In a fourth mode, the dynamic load generator 243 may be operated in a fully dynamic mode to simulate a plasma process that links the load impedance to key process variables including RF power delivery parameters. In such embodiments, the dynamic load generator 243 may be used as an impedance twin (i.e., a digital twin) of the plasma chamber 120. Such embodiments may be particularly beneficial in fully validating a control system because the process envelope may be pushed to extremes without risk of damaging the actual plasma chamber 120.

[0033] In an embodiment, the reverse matching controller 242 can be used to ensure the fidelity of the load impedance output defined by the dynamic load generator 243. The reverse matching controller 242 may include any suitable control algorithm. In one embodiment, the reverse matching controller 242 may include an open loop controller. The control of the reverse matching controller 242 of the open loop may be performed via calculation based on a calibration table and / or a circuit model. In another embodiment, the reverse matching controller 242 may include a closed loop controller. The closed loop controller may rely on real-time feedback to provide the necessary control. In such embodiments, a high bandwidth loop including a fast actuator in the reverse matching network 244 may be required to implement closed loop control. In yet another embodiment, an iterative learning controller may be used for the reverse matching controller 242. In an iterative controller, the first run of the process recipe may be used as feedback to more effectively control the second run of the process recipe. The use of an iterative control system can alleviate the need for a high bandwidth loop.

[0034] In the illustrated embodiment, the components of the smart dynamic load emulator 240 are all illustrated within a single enclosure. That is, the smart dynamic load emulator 240 can be a single fully integrated device having a single enclosure surrounding all of the components. However, it should be understood that in other embodiments, different components can be housed in different enclosures. That is, the smart dynamic emulator 240 can include multiple separate components that are coupled together (e.g., via a communication link, via an electrical coupling (e.g., a coaxial cable), etc.). For example, the dummy load 245 can be located in a different enclosure than the reverse matching network 244.

[0035] Reference now Figure 2B , a schematic diagram of an intelligent dynamic load simulator 240 is shown according to an additional embodiment. As shown, in addition to the reverse matching network 244, Figure 2B The intelligent dynamic load simulator 240 in the embodiment may be substantially similar to Figure 2A In the embodiment of the present invention, the reverse matching network 244 may further include a sensor 246. In a specific embodiment, the sensor 246 is a voltage and current (VI) sensor. The VI sensor 246 may be integrated into the reverse matching network 244 for monitoring or control purposes. This ensures the accuracy of the load impedance provided to the RF delivery system. In an embodiment, the VI sensor 246 may be any sensor architecture. For example, the VI sensor 246 may include a conductive ring and a coaxial cable from the RF delivery system passing through the conductive ring.

[0036] Reference now Figure 3 , illustrates a schematic diagram of a processing tool 300 according to an embodiment. In an embodiment, the processing tool 300 may include an RF delivery system, a chamber 320, and an intelligent dynamic load simulator 340. The RF delivery system may include an RF generator 305 and an RF match 307. The RF generator 305 and the RF match 307 may be substantially similar to the similarly named features described in more detail above. In an embodiment, the RF generator 305 and the RF match 307 may be communicatively coupled to the intelligent dynamic load simulator 340, as indicated by the double-arrow connecting line. The RF generator 305 may also be communicatively coupled to a tool controller 350. The tool controller 350 may be a computer system that provides control of processing parameters, executes recipes, enables device tuning, etc.

[0037] In an embodiment, the output of the RF delivery system may be coupled to a switch 309. The switch 309 may be used to switch the output between the chamber 320 and the smart dynamic load simulator 340. In an embodiment, the chamber 320 may be substantially similar to the chamber 120 described in more detail above. For example, the chamber 320 may be a plasma processing chamber for etching, deposition, or plasma processing of a substrate (not shown). When the RF delivery system is electrically coupled to the chamber 320, a given recipe may be used to process the substrate.

[0038] When switch 309 is set to electrically couple the RF delivery system to the smart dynamic load simulator 340, a development and / or tuning process may be performed on tool 300. In a particular embodiment, the RF delivery system is electrically coupled to a reverse matching network 344. Reverse matching network 344 provides a simulated impedance load to RF match 307. Thus, RF match 307 may be developed or tuned without executing a process recipe on chamber 320. This reduces damage and / or wear to chamber 320.

[0039] Although an embodiment with a physical switch 309 is illustrated, it should be understood that in some embodiments, the switch may be a logical switch. For example, the smart dynamic load simulator 340 may be a connector that is compatible with the chamber, although the smart dynamic load simulator 340 may be located in a different location than the chamber 320. For example, the chamber 340 may be located in a clean room while the smart dynamic load simulator 340 may be located in a conventional laboratory. This allows for further reduction in operating costs / challenges.

[0040] In an embodiment, the intelligent dynamic load emulator 340 may include a dummy load 345. The dummy load 345 may be a static load. That is, the impedance of the dummy load 345 may remain substantially constant. However, in other embodiments, the dummy load 345 may be variable. The impedance of the dummy load 345 may be a real impedance value or a complex impedance value. In an embodiment, the dummy load 345 may include a thermal regulation feature. For example, fan cooling, liquid cooling, etc. may be used to control the temperature of the dummy load 345. In an embodiment, the dummy load 345 may have any specific impedance value.

[0041] In an embodiment, the smart dynamic load emulator 340 may further include a reverse matching network 344. The reverse matching network 344 may have a circuit system including a capacitor, an inductor, etc. In a specific embodiment, the capacitor may include a variable capacitor configured to have a capacitance value changed by an actuator, etc. The reverse matching network 344 allows a variable impedance to be provided even when the dummy load 345 is constant. In this way, an impedance trace may be generated so as to match the impedance of the chamber 320.

[0042] In an embodiment, the intelligent dynamic load emulator 340 may further include an intelligent RF controller 341. The intelligent RF controller 341 may include a dynamic load generator 343 and a reverse matching controller 342. In an embodiment, the dynamic load generator 343 may include an algorithm or model that generates a load impedance output based on inputs (including a dummy load value, RF delivery system parameters, and / or other desired or measured process parameters). In an embodiment, the dynamic load generator 343 may operate in various modes (e.g., a constant load, a variable static load, a predetermined impedance load trace, or a fully dynamic mode). Descriptions of the different modes are described in more detail above.

[0043] In an embodiment, the reverse matching controller 342 may be used to ensure the fidelity of the load impedance output defined by the dynamic load generator 343. The reverse matching controller 342 may include any suitable control algorithm (e.g., an open loop controller, a closed loop controller, or an iterative learning controller). Descriptions of different control algorithms are provided in more detail above.

[0044] Reference now Figure 4 , illustrates a schematic diagram of a software stack 460 for an intelligent dynamic load simulator according to an embodiment. In an embodiment, the software stack 460 may include an operating system 461. The operating system 461 may be any suitable operating system. For example, Windows, Raspberry Pi, Linux, macOS, etc. may be used for the operating system 461. In an embodiment, a device driver 462 may also be included in the software stack 460. Different drivers 462 may be used for different components of the intelligent dynamic load simulator. For example, a driver for a dummy load, a driver for reverse RF matching, and a driver for an intelligent RF controller may be provided.

[0045] In an embodiment, the software stack 460 may further include a plasma load model 463. The plasma load model 463 may operate with a dynamic load generator. In an embodiment, the plasma load model 463 may be a model for replicating a previously recorded impedance trace. For example, a process recipe may be executed in a process chamber. The impedance of the process chamber throughout the recipe may be recorded. The plasma load model 463 can then replicate the impedance trace using reverse RF matching. In another embodiment, the plasma load model 463 may be an impedance twin of the process chamber. For example, the plasma load model 463 may be a physics-based model for simulating plasma processing that links load impedance to key process variables including RF power delivery parameters.

[0046] When used as an impedance twin, the plasma loading model 463 can improve tuning and development processes because the plasma loading model 463 can safely implement corner conditions that would otherwise damage the processing chamber or cause excessive wear to the processing chamber.

[0047] In an embodiment, the software stack 460 may further include a reverse matching controller 464 algorithm. In an embodiment, the reverse matching controller 464 may include one or more different control algorithms. In one embodiment, the reverse matching controller 464 includes an open loop controller. The open loop controller may utilize calculations based on calibration tables and / or circuit models. In additional embodiments, the reverse matching controller 464 may include a closed loop control algorithm. In the closed loop control algorithm, real-time feedback may be provided to improve control. In yet another embodiment, an iterative learning control algorithm may be included in the reverse matching controller 464. The iterative learning control algorithm may use the first processing run as input to improve control of the continuous processing run.

[0048] In an embodiment, the software stack 460 may also include a data acquisition (DAQ), storage, and processing module 465. The module 465 may use any suitable circuitry, memory, processor, etc. The module 465 may work in conjunction with the plasma load model 463 and the reverse matching controller 464 to perform various processes using the intelligent dynamic load simulator.

[0049] In an embodiment, the software stack 460 may further include a user interface (UI) 466. The user interface 466 may be provided on a screen or the like for a user to interact with the smart dynamic load simulator. The UI 466 may be designed to have any desired layout or other UI functionality.

[0050] Reference now Figure 5 , illustrates a diagram depicting the flexibility of the intelligent dynamic load simulator 540 according to an embodiment. In particular, Figure 5 The diagram illustrates various operating modes that may be used in conjunction with the intelligent dynamic load simulator 540. That is, the intelligent dynamic load simulator 540 may be used to develop an application 571, test an application 572, and operate an application 573.

[0051] In an embodiment, a system development application 571 may be used to develop a control system for an RF delivery system. Interchangeable simulators and plasma chamber connections to the RF control system being developed may significantly reduce development and / or deployment time. This improvement in development duration is provided because the need for chamber access is reduced. That is, since no chamber is required, the development process may be implemented with more flexible scheduling. Additionally, embodiments allow for overlap of chamber process design and RF control system design / verification. In essence, the RF control system may be designed at the same time as the chamber process is being designed because the RF control system does not require a dedicated process chamber for development.

[0052] In an embodiment, the test application 572 also provides enhancements to existing solutions. For example, the ease and safety of corner condition testing and stress testing are improved. Typically, corner condition testing and stress testing are designed to push the processing chamber to its limits. Therefore, such tests may cause excessive wear and / or damage to the processing chamber. The intelligent dynamic load simulator can replicate the impedance of such tests in order to test the RF control system instead of using physical testing of the chamber. Accordingly, when using the embodiments disclosed herein, the cost and duration of testing can be reduced.

[0053] In addition, embodiments disclosed herein allow for the use of intelligent dynamic load emulators during operation of application 573. For example, a dynamic load model can be used to replace the need for output sensors (e.g., VI sensors) on a matching network. In this way, the cost of the RF control system can be reduced.

[0054] Accordingly, embodiments disclosed herein include an intelligent dynamic load simulator that can be used to model the impedance of a processing chamber for development, testing, or application purposes. Typically, the intelligent dynamic load simulator includes a dummy load, a reverse match, and an intelligent RF controller. The intelligent RF controller controls the reverse match so that a variable impedance trace is generated from the dummy load. The variable impedance trace can be similar to the impedance trace of the processing chamber during operation. For example, the impedance of the chamber recorded during operation can be simulated or the impedance twin function can be used to generate the impedance trace. Therefore, the RF delivery system (i.e., the RF generator and the RF match) can be electrically coupled to the intelligent dynamic load simulator instead of the processing chamber. Therefore, the processing chamber does not need to be offline for verification purposes, or even the processing chamber does not need to be fully developed before the RF delivery system is developed.

[0055] Reference now Figure 6, a block diagram of an exemplary computer system 600 of a processing tool according to an embodiment is illustrated. The exemplary computer system 600 can be used for one or more systems described in more detail above. For example, the exemplary computer system can be used for a tool controller and / or an intelligent RF controller. In an embodiment, the computer system 600 is coupled to and controls the processing in the processing tool. The computer system 600 can be connected (e.g., network connected) to other machines in a local area network (LAN), an intranet, an extranet, or the Internet. The computer system 600 can operate in the capacity of a server or client machine in a client-server network environment, or as a peer machine in a peer (or distributed) network environment. The computer system 600 can be a personal computer (PC), a tablet computer, a set-top box (STB), a personal digital assistant (PDA), a cellular phone, a network appliance, a server, a network router, a switch or a bridge, or any machine capable of executing a set of instructions (sequentially or otherwise) to specify the actions to be taken by the machine. Further, while only a single machine is illustrated with respect to computer system 600, the term "machine" shall also be taken to include any collection of machines (e.g., computers) that individually or jointly execute a set (or multiple sets) of instructions to perform any one or more of the methodologies described herein.

[0056] The computer system 600 may include a computer program product, or software 622, a non-transitory machine-readable medium having instructions stored thereon, which can be used to program the computer system 600 (or other electronic devices) to perform processes according to embodiments. A machine-readable medium includes any mechanism for storing or transmitting information in a form readable by a machine (e.g., a computer). For example, a machine-readable (e.g., computer-readable) medium includes a machine-readable (e.g., computer) storage medium (e.g., read-only memory ("ROM"), random access memory ("RAM"), magnetic disk storage medium, optical storage medium, flash memory device, etc.), a machine-readable (e.g., computer) transmission medium (electrical, optical, acoustic or other form of propagated signals (e.g., infrared light signals, digital signals, etc.)), etc.

[0057] In an embodiment, the computer system 600 includes a system processor 602, a main memory 604 (e.g., read-only memory (ROM), flash memory, dynamic random access memory (DRAM) such as synchronous DRAM (SDRAM) or Rambus DRAM (RDRAM), etc.), a static memory 606 (e.g., flash memory, static random access memory (SRAM), etc.), and a secondary memory 618 (e.g., a data storage device) that communicate with each other via a bus 630.

[0058] The system processor 602 represents one or more general-purpose processing devices, such as a microsystem processor, a central processing unit, etc. More specifically, the system processor may be a complex instruction set computing (CISC) microsystem processor, a reduced instruction set computing (RISC) microsystem processor, a very long instruction word (VLIW) microsystem processor, a system processor implementing other instruction sets, or a system processor implementing a combination of instruction sets. The system processor 602 may also be one or more special-purpose processing devices, such as an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), a digital signal system processor (DSP), a network system processor, etc. The system processor 602 is configured to execute processing logic 626 for performing the operations described herein.

[0059] The computer system 600 may further include a system network interface device 608 for communicating with other devices or machines over a network 661. In addition, the computer system 600 may include peripheral ports (e.g., serial ports, USB ports, etc.) to communicate with other components external to the computer system 600. The computer system 600 may also include a video display unit 610 (e.g., a liquid crystal display (LCD), a light emitting diode display (LED), or a cathode ray tube (CRT)), an alphanumeric input device 612 (e.g., a keyboard), a cursor control device 614 (e.g., a mouse), and a signal generating device 616 (e.g., a speaker).

[0060] The secondary memory 618 may include a machine-accessible storage medium 632 (or more specifically, a computer-readable storage medium) on which is stored one or more sets of instructions (e.g., software 622) that implement any one or more of the methods or functions described herein. The software 622 may also reside, completely or at least partially, within the main memory 604 and / or within the system processor 602 during execution by the computer system 600, the main memory 604 and the system processor 602 also constituting machine-readable storage media. The software 622 may further be transmitted or received over the network 620 via the system network interface device 608. In embodiments, the network interface device 608 may operate using RF coupling, optical coupling, acoustic coupling, or inductive coupling.

[0061] Although the machine-accessible storage medium 632 is illustrated as a single medium in the exemplary embodiment, the term "machine-readable storage medium" should be construed to include a single medium or multiple media (e.g., a centralized or distributed database and / or associated caches and servers) storing one or more sets of instructions. The term "machine-readable storage medium" should also be construed to include any medium capable of storing or encoding a set of instructions for execution by a machine and causing the machine to perform any one or more methodologies. Accordingly, the term "machine-readable storage medium" should be construed to include, but not be limited to, solid-state memory, and optical and magnetic media.

[0062] In the foregoing specification, specific exemplary embodiments have been described. It will be apparent that various modifications may be made to the exemplary embodiments without departing from the scope of the following claims. Accordingly, the specification and drawings are to be regarded in an illustrative rather than a restrictive sense.

Claims

1. A dynamic load simulator, comprising: Impedance load; Reverse matching network; and An intelligent RF controller, wherein the intelligent RF controller comprises: Dynamic load generator; and Reverse matching controller.

2. The dynamic load simulator of claim 1, wherein the reverse matching network further comprises a sensor. 3 . The dynamic load simulator as claimed in claim 2 , wherein the sensor is a voltage sensor and a current sensor. The dynamic load simulator as claimed in claim 1 , wherein the impedance load is a fixed dummy load.

5. The dynamic load emulator of claim 4, wherein the reverse matching network is configured to tune the fixed dummy load to a desired impedance load different from the fixed dummy load.

6. The dynamic load simulator of claim 1, wherein the impedance load is thermally controlled using a cooling system.

7. The dynamic load simulator of claim 1, wherein the dynamic load generator is configured to generate a load impedance output based on inputs including the impedance load, RF delivery system parameters, and other measured process parameters.

8. The dynamic load emulator of claim 7, wherein the reverse matching controller is configured to ensure fidelity of the load impedance generated by the dynamic load generator.

9. The dynamic load simulator of claim 1, wherein the impedance load, the reverse matching network, and the RF controller are components within a single housing.

10. The dynamic load simulator of claim 1, wherein the impedance load, the reverse matching network, and the intelligent RF controller are separate components in different housings.

11. The dynamic load simulator of claim 1, wherein the dynamic load simulator is selectively coupled to an RF delivery system.

12. The dynamic load simulator of claim 11, wherein the RF delivery system is configured to switch between a processing chamber and the dynamic load simulator.

13. An intelligent RF controller, comprising: a dynamic load generator configured to provide a load impedance trace on a reverse matching network coupled to a fixed dummy load; and Reverse matching controller.

14. The intelligent RF controller of claim 13, wherein the hardware of the intelligent RF controller is implemented as a computer system.

15. The intelligent RF controller of claim 13, wherein the impedance trace is a pre-recorded trace of the impedance of the plasma chamber.

16. The intelligent RF controller of claim 13, wherein the load impedance trace is generated by a dynamic model of a plasma chamber.

17. The intelligent RF controller of claim 13, wherein the reverse matching controller is an open loop controller, a closed loop controller, or configured to use iterative learning.

18. A processing tool comprising: RF delivery system, including: RF generator; and RF matching network; and a switch that selectively couples the RF delivery system to a plasma chamber or a dynamic load simulator, wherein the dynamic load simulator comprises: dummy load; Reverse matching network; and An RF controller, wherein the RF controller comprises: Dynamic load generators; and Reverse matching controller.

19. The processing tool of claim 18, wherein the dynamic load generator is configured to generate a simulated impedance trace that matches an impedance trace of the plasma chamber during operation.

20. The processing tool of claim 19, wherein the simulated impedance trace is a pre-recorded trace of the impedance of the plasma chamber during operation, or wherein the simulated impedance trace is generated by a dynamic model of a plasma chamber.

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