Prevention of substrate contamination during pressure changes within the processing system.

Abstract

This provides a mounting configuration that minimizes substrate contamination during pressure changes within a substrate processing system. [Solution] Over the duration of pressure changes (increase or decrease) within the load lock chamber (LLC) of the substrate processing system 200, the gas flow rate out of the chamber is adjusted multiple times to reduce the generation of contaminant particles in the chamber environment, and the gas flow rate is continuously changed using at least one dynamic valve that allows continuous control of the chamber's pneumatics. With the LLC sealed from the external environment, the gas flow is initiated through one or more valves, and the rate of gas flow is matched to each of a plurality of reference flow rates (RFRs) at each of a plurality of time intervals, the plurality of RFRs including at least three RFRs, and determined to minimize the generation of one or more contaminants in the LLC environment.

Description

Technical Field

[0001] This current specification generally relates to improving the quality of substrates (e.g., wafers) in an electronic device manufacturing system, and more specifically, to methods for minimizing the presence of contaminants in the environment of a substrate processing apparatus.

Background Art

[0002] Modern material manufacturing often involves various etching and deposition techniques, including plasma etching techniques, chemical deposition techniques, and physical vapor deposition (PVD) techniques, where one or more selected types of atoms are deposited onto a specially prepared substrate held in a low-vacuum or high-vacuum environment provided by a vacuum deposition chamber. Materials manufactured using this technique include many other substances used in practical applications such as electronic device manufacturing, such as single crystals, semiconductor films, and fine coatings. Many of these applications require certain standards for the purity of the materials grown within the deposition chamber. The need to maintain separation of the environment between chambers and minimize its exposure to the ambient atmosphere and contaminants therein gives rise to various robotic techniques for substrate handling and chamber control. Automated operation often involves robots that move substrates between chambers having very different environments.

[0003] Aspects and embodiments of the present disclosure will be more fully understood from the detailed description and the accompanying drawings provided below, but should not be construed as limiting the disclosure to specific aspects or embodiments. These are for illustrative and understanding purposes only. The drawings are described below for illustrative purposes, but are not necessarily to scale.

Brief Description of the Drawings

[0004] [Figure 1] Schematic diagram of a processing system (e.g., a substrate processing system) according to some embodiments of the present disclosure. [Figure 2]Schematic diagram of a substrate processing system enabling effective prevention of substrate contamination during pressure changes, according to some embodiments of the present disclosure. [Figure 3] Schematic diagram of the type of change in pressure (upper graph) to the load lock chamber and the gas flow rate (lower graph) into the load lock chamber, determined to minimize substrate contamination during the pump-up stage of substrate manufacturing, according to some embodiments of the present disclosure. [Figure 4] Schematic diagram of an example algorithm used to determine target pressures and target flow rates for a pump-up process that reduces the presence of contaminants in a substrate processing system, according to some embodiments of the present disclosure. [Figure 5] Schematic diagram of the type of change in pressure (upper graph) of the load lock chamber and the gas flow rate (lower graph) flowing out of the load lock chamber, determined to minimize liquid condensation during the pump-down stage of a substrate processing system, according to some embodiments of the present disclosure. [Figure 6] Schematic diagram of an example algorithm used to determine target pressures and target flow rates during a pump-down process that reduces liquid condensation in a substrate processing system, according to some embodiments of the present disclosure. [Figure 7A] Diagram of an example valve control system that can be used to prevent product contamination in a substrate processing system during pressure changes, according to some embodiments of the present disclosure. [Figure 7B] Diagram of another example valve control system for preventing product contamination in a substrate processing system during pressure changes, according to some embodiments of the present disclosure. [Figure 8] Flow diagram of a method for defining pressure changes that minimize the generation of contaminants in a substrate processing system, according to some embodiments of the present disclosure. [Figure 9] Flow diagram of a method for moving a substrate from a first section of a substrate processing system to a second section while minimizing exposure of the substrate to contaminants, according to some embodiments of the present disclosure. [Figure 10] This is a flowchart of a method for modeling the types of pressure and flow rate changes that minimize the generation of contaminants in a substrate processing system, according to some embodiments of the present disclosure. [Figure 11] This is a block diagram of an example processing device operation according to one or more aspects of the present disclosure. [Modes for carrying out the invention]

[0005] In a substrate processing system, a substrate (e.g., a silicon wafer) can undergo several processing steps. For example, an unprocessed substrate can be delivered to the processing system in a substrate carrier, such as a forward-opening unified pod (FOUP). The FOUP can be docked to a factory interface (front-end module). A robotic arm of the factory interface robot can remove the substrate from the FOUP and deliver it to a load lock (degassing chamber). Another robotic arm can then be extended from the transfer chamber to remove the substrate from the load lock chamber and deliver it to one or more processing chambers accessible from the transfer chamber for processing. A number of processing chambers can be provided. The substrate can be moved (e.g., by a transfer chamber robot) between various processing chambers, where various processing steps can be performed, such as mask deposition, etching, mask removal, and substrate deposition. After processing, the substrate can be returned to the FOUP (same or different) through, for example, the transfer chamber, load lock chamber, factory interface, etc. Each chamber may have its own environment, such as temperature, pressure, and type of gas. For example, the transfer chamber (and processing chamber) operates under a pressure P much lower than atmospheric pressure. T It can have a low vacuum environment or a high vacuum environment. On the other hand, the factory interface (and FOUP) has a pressure P close to atmospheric pressure. IIt can have a load lock chamber (a venting chamber, or any other chamber) that can therefore function as an airlock between the factory interface and the transfer chamber. Specifically, when the substrate should be moved from the factory interface to the load lock chamber (and then to the transfer chamber), the pressure in the load lock chamber can be controlled to P I From the pressure P inside the transfer chamber T The pressure can be gradually reduced to P. If such a pump-down process is performed rapidly, it can lower the temperature inside the load lock chamber, leading to the condensation of various vapors (e.g., water vapor) on the substrate. The condensates subsequently carried by the substrate to the transfer chamber and processing chamber can negatively impact the manufacturing process and the quality of the final product (e.g., by preventing the deposited material from properly adhering to the substrate). On the other hand, if the pump-down process is performed slowly, it reduces the system's manufacturing output (throughput). Similarly, as the substrate is moved from the transfer chamber to the load lock chamber (and subsequently to the factory interface), the pressure inside the load lock chamber is P T Pressure P in the factory interface IThe pressure gradually increases. If such a pump-up process is performed rapidly, it can release various particles remaining (adsorbed) on the walls of the load lock chamber into the environment of the load chamber. The released particles can settle on the substrate and become contaminants. Slowing down the pump-up process, as in the case of the pump-down process, reduces the number of separated (resuspended) particles but reduces the manufacturing throughput. Existing techniques involve dividing the pump-down process into two phases: a slow first phase and a fast second phase. The first phase is characterized by a first (low) flow rate (vent rate) and a corresponding slow increase in the pressure inside the load lock chamber. The second phase begins by switching the flow rate to a second (increased) flow rate value. The pressure then increases even more rapidly. Such two-stage flow rate control reduces the number of particles that may be separated by limiting the rate at which the pressure increases in the first (and more sensitive) phase of the pump-up process. While it reduces the amount of contaminants released into the load lock chamber environment to some extent, existing two-stage techniques have limitations in flexibility and adjustability because the first and second vent rate values ​​are set empirically.

[0006] The aspects and embodiments of this disclosure address these and other shortcomings of existing pump-down and pump-up techniques used in substrate manufacturing. This specification describes, among other things, implementations that enable the determination of the optimal type of change in pressure P(t) within the load lock chamber during both the pump-down and pump-up processes to minimize the release of contaminants into the environment from the load lock chamber. In some embodiments, the minimization of contaminants is based on simulations that consider actual physical processes determining the resuspending of particles into the environment during the pump-up phase and actual physical processes determining vapor condensation during the pump-down phase. In addition, dynamic valve control settings are described that enable setting and controlling the flow rate F(t) of gas flowing into or out of the load lock chamber at multiple time points (time points) in each process. In some embodiments, each of the pump-up and pump-down phases may involve setting three, four, or other different flow rates calculated to minimize the generation of contaminants within the load lock chamber. In some embodiments, each of the pump-up and pump-down stages may involve setting the flow rate F(t) continuously or semi-continuously, which may involve setting (or adjusting) the flow rate F(t) at a large number N (e.g., N=10, 20, 50, etc.) over the duration of each stage.

[0007] Figure 1 illustrates a schematic diagram of a processing system 100 (e.g., a substrate processing system) according to some embodiments of the present disclosure. The processing system 100 includes a factory interface (FI) 101 and load ports 128 (e.g., load ports 128A-D). In some embodiments, load ports 128A-D are installed directly on the FI 101 (e.g., sealed to the FI 101). Enclosure systems 130 (e.g., cassettes, FOUPs, processing kit enclosure systems, etc.) are configured to be detachably coupled (e.g., docked) to load ports 128A-D. Referring to Figure 1, enclosure system 130A is coupled to load port 128A, enclosure system 130B is coupled to load port 128B, enclosure system 130C is coupled to load port 128C, and enclosure system 130D is coupled to load port 128D. In some embodiments, one or more enclosure systems 130 are coupled to a load port 128 to move substrates and / or other products into and out of the processing system 100. Each of the enclosure systems 130 may be sealed to its respective load port 128. In some embodiments, a first enclosure system 130A is docked to a load port 128A. Once one or more such operations are performed, the first enclosure system 130A is detached from the load port 128A, and then a second enclosure system 130B (e.g., a FOUP containing a substrate) is docked to the same load port 128A. In some embodiments, an enclosure system 130 (e.g., enclosure system 130A) is a system for performing calibration and diagnostic operations. In some embodiments, the enclosure system 130 (e.g., enclosure system 130B) is a process kit enclosure system for moving contents 110, such as a process kit ring, into and out of the processing system 100.

[0008] In some embodiments, the load port 128 includes a front interface that forms an opening. The load port 128 additionally includes a horizontal plane that supports the enclosure system 130. Each enclosure system 130 has a front interface that forms a vertical opening. The front interface of the enclosure system 130 is sized to interface with the front interface of the load port 128 (for example, the vertical opening of the enclosure system 130 is approximately the same size as the vertical opening of the load port 128). The enclosure system 130 is positioned on the horizontal plane of the load port 128, and the vertical opening of the enclosure system 130 coincides with the vertical opening of the load port 128. The front interface of the enclosure system 130 interconnects with the front interface of the load port 128 (for example, by crimping, fixing, or sealing). The bottom plate (e.g., base plate) of the enclosure system 130 has a mechanism that engages with the horizontal surface of the load port 128 (a loading mechanism such as a recess or receptacle that engages with the kinematic pin mechanism of the load port, the load port mechanism for the pin gap, and / or the enclosure system docking tray latch clamp mechanism). The same load port 128 is used for different types of enclosure systems 130.

[0009] In some embodiments, the enclosure system 130B (e.g., a process kit enclosure system) includes one or more contents 110 (e.g., one or more of a process kit ring, an empty process kit ring carrier, a process kit ring placed on the process kit ring carrier, a placement confirmation wafer, etc.). In some examples, the enclosure system 130B is coupled to the FI 101 (e.g., via a load port 128) to allow the process kit ring on the process kit ring carrier to be automatically moved into the processing system 100 for replacement of a used process kit ring.

[0010] In some embodiments, the processing system 100 also includes first vacuum ports 103a, 103b that connect FI 101 to their respective load lock chambers 104a, 104b. Second vacuum ports 105a, 105b are connected to their respective load lock chambers 104a, 104b and positioned between the load lock chambers 104a, 104b and the transfer chamber 106 to facilitate the transfer of substrates and other contents 110 (e.g., process kit rings) to the transfer chamber 106. In some embodiments, the processing system 100 includes and / or uses one or more load lock chambers 104 and a corresponding number of vacuum ports 103, 105 (e.g., the processing system 100 includes a single load lock chamber 104, a single first vacuum port 103 and a single second vacuum port 105). The transfer chamber 106 includes a plurality of processing chambers 107 (e.g., four processing chambers 107, six processing chambers 107, etc.) arranged around it and connected thereto. The processing chamber 107 is coupled to the transfer chamber 106 through its respective ports 108, such as slit valves. In some embodiments, the FI 101 is at a higher pressure (e.g., atmospheric pressure) and the transfer chamber 106 is at a lower pressure (e.g., vacuum). Each load lock chamber 104 (e.g., a venting chamber) has a first door (e.g., a first vacuum port 103) to seal the load lock chamber 104 from the FI 101 and a second door (e.g., a second vacuum port 105) to seal the load lock chamber 104 from the transfer chamber 106. While the first door is open and the second door is closed, the contents are to be moved from the FI 101 into the load lock chamber 104; when the first door is closed and the pressure inside the load lock chamber 104 is reduced to match that of the transfer chamber 106, the second door is opened and the contents are moved out of the load lock chamber 104. A local centering (LCF) device should be used to align the contents with the transfer chamber 106 (for example, before entering the processing chamber 107 and after leaving the processing chamber 107).

[0011] In some embodiments, the processing chamber 107 includes one or more of the following: an etch chamber, a deposition chamber (including atomic layer deposition, chemical vapor deposition, physical vapor deposition or plasma-enhanced versions thereof), an annealing chamber, etc.

[0012] The factory interface 101 includes a factory interface robot 111. The factory interface robot 111 includes a robot arm, such as a Selective Compliance Assembled Robot Arm (SCARA) robot. Examples of SCARA robots include a 2-link SCARA robot, a 3-link SCARA robot, a 4-link SCARA robot, and the like. The factory interface robot 111 includes an end effector at one end of the robot arm. The end effector is configured to lift and handle specific objects, such as wafers. Alternatively, or additionally, the end effector may be configured to handle objects such as calibration substrates and process kit rings (edge ​​rings). The robot arm has one or more connecting parts or members (e.g., a wrist member, an upper arm member, a forearm member) configured to move the end effector in different orientations and to different locations.

[0013] The factory interface robot 111 is configured to move an object between the enclosure system 130 (e.g., a cassette, FOUP) and the load lock chambers 104a, 104b (or load ports). The factory interface robot 111 is taught a fixed position relative to the load port 128 using the enclosure system 130 in the embodiments. In one embodiment, the fixed position corresponds to the center position of the enclosure system 130A located at a particular load port 128, which in the embodiments also corresponds to the center position of the enclosure system 130B located at a particular load port 128. Alternatively, the fixed position may correspond to other fixed positions within the enclosure system 130, such as in front of or behind the enclosure system 130. In some embodiments, the factory interface robot 111 is calibrated using the enclosure system 130. In some embodiments, the factory interface robot 111 is diagnosed using the enclosure system 130.

[0014] The transfer chamber 106 includes a transfer chamber robot 112. The transfer chamber robot 112 includes a robot arm with an end effector at one end of the robot arm. The end effector is configured to handle specific objects, such as wafers. In some embodiments, the transfer chamber robot 112 is a SCARA robot, but in some embodiments, it may have fewer connections and / or fewer degrees of freedom than the factory interface robot 111.

[0015] The controller 109 controls various aspects of the processing system 100. The controller 109 is a computing device such as a personal computer, a server computer, a programmable logic controller (PLC), or a microcontroller, or includes such a computing device. The controller 109 includes one or more processing devices, which in some embodiments are general-purpose processing devices such as a microprocessor or a central processing unit. More specifically, in some implementations, the processing device is a composite instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, or a processor that implements other instruction sets or combinations of instruction sets. In some embodiments, the processing device is one or more special-purpose processing devices such as an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), or a network processor. In some embodiments, the controller 109 includes data storage devices (e.g., one or more disk drives and / or solid-state drives), main memory, static memory, a network interface, and / or other components. In some embodiments, the controller 109 executes instructions to perform one or more of the methods or processes described herein. The instructions are stored in a computer-readable storage medium, which (during instruction execution) includes main memory, static memory, secondary storage and / or processing devices. In some embodiments, the controller 109 receives signals from the factory interface robot 111 and the wafer transfer chamber robot 112 and transmits controls to them.

[0016] According to one aspect of the disclosure, in order to move the contents 110 (e.g., a substrate or process kit ring) into the processing chamber 107, the contents 110 are removed from the process kit enclosure system 130B via a factory interface robot 111 located in FI 101. The factory interface robot 111 moves the contents 110 into the respective load lock chambers 104a, 104b through one of the first vacuum ports 103a, 103b. A transfer chamber robot 112 located in the transfer chamber 106 removes the contents 110 from one of the load lock chambers 104a, 104b through a second vacuum port 105a or 105b. The transfer chamber robot 112 moves the contents 110 into the transfer chamber 106, where the contents 110 are transferred to the processing chamber 107 through the respective ports 108. After processing, the processed contents 110 (e.g., a used process kit ring) are removed from the processing system 100 in the reverse manner described herein.

[0017] The processing system 100 includes a chamber such as FI101 (e.g., an apparatus front-end module, EFEM) and adjacent chambers adjacent to FI101 (e.g., a load port 128, an enclosure system 130, an SSP, a load lock chamber 104 such as a venting chamber). Some or all of the chambers can be sealed. In some embodiments, an inert gas (e.g., one or more of nitrogen, argon, neon, helium, krypton, or xenon) is supplied to one or more of the chambers (e.g., FI101 and / or adjacent chambers) to create one or more inert environments. In some examples, FI101 is an inert EFEM that maintains an inert environment (e.g., an inert EFEM mini-environment) within FI101, so that the user does not need to enter FI101 (e.g., the processing system 100 is configured so that there is no human access to FI101).

[0018] In some embodiments, a gas flow (e.g., an inert gas, nitrogen) is supplied into one or more chambers (e.g., FI101) of the processing system 100. In some embodiments, the gas flow is greater than the leakage through one or more chambers in order to maintain positive pressure in one or more chambers. In some embodiments, the inert gas in FI101 is recirculated. In some embodiments, a portion of the inert gas is exhausted. In some embodiments, in order to maintain positive pressure of the inert gas in FI101, the gas flow of gas that is not recirculated into FI101 is greater than the exhausted gas flow and gas leakage. In some embodiments, FI101 is coupled to one or more valves and / or pumps to provide gas flow into and out of FI101. A processing device (e.g., controller 109) controls the gas flow into and out of FI101. In some embodiments, the processing device receives sensor data from one or more sensors (e.g., an oxygen sensor, a moisture sensor, a motion sensor, a door operation sensor, a temperature sensor, a pressure sensor, etc.) and determines the flow rate of inert gas into and out of the FI101 based on the sensor data.

[0019] The enclosure system 130 can also be used to teach, calibrate, and / or diagnose a robotic arm (e.g., a factory interface robot) without opening the sealed environment within the FI 101 and adjacent chambers. The enclosure system 130 seals to the load port 128 in response to docking onto the load port 128. The enclosure system 130 provides purge port access so that the interior of the enclosure system 130 can be purged before opening the enclosure system 130 in order to minimize disturbance to the inert environment within the FI 101.

[0020] Figure 2 illustrates a schematic diagram of a substrate processing system 200 that enables effective prevention of substrate contamination during pressure changes, according to some embodiments of the present disclosure. The electronic device processing system 200 includes an FI 101 (or device front-end module, EFEM), which interfaces with one or more substrate carriers, e.g., a FOUP (not shown). In addition, the FI 101 interfaces with a load lock chamber 104 via a first vacuum port 103. The load lock chamber 104 further interfaces with a transfer chamber 106 via a second vacuum port 105. The transfer chamber 106 enables access to one or more processing chambers (not shown in Figure 2). The FI 101 and the transfer chamber 106 include robots 111 and 112, respectively, for moving substrates 201 and 202 between the FI 101, the load lock chamber 104, the transfer chamber 106, and the processing chambers.

[0021] The load lock chamber 104 includes various equipment for monitoring and controlling the environment within it. More specifically, the load lock chamber 104 has a dynamic valve 204 for setting the gas flow 206 into (solid arrow) or out (dotted arrow) the load lock chamber 104 to a gas flow rate F(t). The dynamic valve 204 is a fast-response valve capable of setting the flow rate F(t) continuously or semi-continuously in response to an input control signal, as will be described in more detail below. The gas may be nitrogen, argon, xenon, krypton, or any other suitable gas whose flow rate is controlled by the dynamic valve 204, for example, a low-reactivity gas that does not react with the substrates 201 and 202. The setting of the dynamic valve 204 indirectly controls the pressure P(t) within the load lock chamber 104. The load lock chamber 104 has a pressure sensor 208 for monitoring the pressure within the load lock chamber 104. For simplicity, only one pressure sensor 208 is shown within the load lock chamber 104, but multiple pressure sensors may be placed at various locations within the load lock chamber 104. Various other sensors may also be used. For example, monitoring the environment within the load lock chamber 104 can be done using one or more temperature sensors to measure the temperature at one or more locations within the load lock chamber 104, one or more chemical sensors to detect the presence (and / or concentration) of contaminants at various locations within the load lock chamber 104, one or more optical sensing devices (e.g., to monitor the presence of contaminant particles), and so on.

[0022] The substrate processing system 200 includes a computing device 210 for implementing the pump-up and pump-down variations described herein. The computing device 210 may be a desktop computer, laptop computer, workstation, wearable device (tablet, smartphone, etc.), cloud-based computing service, etc. In some embodiments, the computing device 210 is a dedicated microcontroller that operates independently or in conjunction with another computing device. In some embodiments, the computing device 210 controls numerous stages of substrate manufacturing, including receiving substrates in FI 101, delivering substrates to the transfer chamber 106 and processing chambers, performing various processes therein (masking, etching, deposition, imaging, quality control, etc.), and recovering processed substrates from the processing chambers. In addition to the operations listed above, the computing device 210 performs more specific functions related to monitoring and controlling the pressure inside the load lock chamber 104.

[0023] In detail, the computing device 210 has a pressure monitoring component 220, which collects pressure data (e.g., P LL The computing device 210 further includes a valve control module 222 to regulate the amount of gas flow F(t) 206 into (or out of) the load lock chamber 104 by providing a signal (e.g., analog or digital) to the dynamic valve 204. The pressure monitoring module 220 and the valve control module 222 work in conjunction with pressure and flow modeling 224 to identify target pressure P(t) and target flow rate F(t) representing the desired (e.g., optimal or near-optimal) type of change in the pump-down and / or pump-up processes to be carried out within the load lock chamber 104.

[0024] In one embodiment, the modules and components of the computing device operate as follows. In some embodiments, the computing device 210 executes a technical process involved in the substrate processing system 200. In other embodiments, the computing device 210 recognizes a technical process controlled by some other computing device and performs only a part of the whole process. For example, the computing device 210 controls the environment of the load lock chamber 104 and seals and opens the load lock chamber 104, etc., before and after the pump - down process / pump - up process. In some embodiments, the computing device 210 determines that the substrate 202 is ready to be moved from the transfer chamber 106 to one of the FOUPs docked to FI101 after being processed in one or more processing chambers. The computing device 210 then identifies in the current technical process that a given gas is present in the transfer chamber 106 maintained at pressure P T . The computing device 210 finally further determines that the opening of the load lock chamber 104 opens the first vacuum port 103, and thus the current pressure in the load lock chamber 104 is, or is close to, the factory interface pressure P I , which may be comparable to the atmospheric pressure. Thus, before the second vacuum port 105 can be opened for the passage of the substrate 202, the pressure in the load lock chamber 104 needs to be reduced from P I to P T . The computing device 210 further identifies that the pump - down process should complete within the time range of τ. The type of gas, the initial pressure (in this example, P I ), the final pressure (in this example, P TThe time τ is then input to the pressure and flow modeling 224 for determining the target pressure profile P(t) by the methods and techniques described below. In addition, the pressure and flow modeling 224 determines the target gas flow F(t) to be performed by the dynamic valve 204 to maintain the target pressure profile P(t). In some implementations, the determination by the pressure and flow modeling 224 is performed before the start of the pump-down / pump-up process, and the target F(t) and P(t) are stored in the memory of the computing device 210.

[0025] When the valve control module 222 receives instructions to perform a target flow rate F(t) and a target pressure P(t), for example from the pressure and flow rate modeling 224 (or retrieves such instructions from memory that have been pre-stored as target profiles F(t) and P(t)), it outputs a control signal to the dynamic valve 204 to set and adjust the target flow rate F(t). In some executions, the control signal is output continuously. For example, the valve control module 222 can continuously control the flow rate through the dynamic valve 204 by outputting a current I(t) (or voltage V(t)). In some executions, the valve control module 222 outputs a signal quasi-continuously, for example, by changing the intensity of the current (or voltage) signal for each portion Δτ of the total duration τ of the pump-down (or pump-up) process. In some executions, the signal intensity changes many times over the total duration (such that Δτ≪τ). Meanwhile, the pressure monitoring component 220 also monitors the actual pressure P inside the load lock chamber 104 in real time. LL Monitor (t), for example, difference ΔP(t)=P LL By calculating (t)-P(t), the actual pressure is compared to the target pressure profile P(t). Depending on the sign and magnitude of the difference ΔP(t), the valve control module 222 changes the signal output to the dynamic valve 204 to correct the gas flow 206 and the actual pressure P LLThe valve control module 222 directs the dynamic valve 204 to increase the gas flow F(t) from the load lock chamber 104 if ΔP(t)>0 is detected during the pump-down process. Conversely, if ΔP(t)<0 is detected, the valve control module 222 directs the dynamic valve 204 to decrease the gas flow F(t). A similar process continues during the pump-up process. For example, if ΔP(t)>0 is detected during the pump-up process, the valve control module 222 directs the dynamic valve 204 to decrease the gas flow F(t) into the load lock chamber 104. Conversely, if ΔP(t)<0 is detected, the valve control module 222 directs the dynamic valve 204 to increase the gas flow F(t) into the load lock chamber 104.

[0026] While the above examples and the remainder of the disclosure refer to processes performed to equalize pressure between a load lock chamber and a transfer chamber (pump-down phase) or between a load lock chamber and a factory interface (pump-up phase), the methods and systems disclosed are applicable to equalizing pressure between any two or more chambers in various manufacturing systems in particle-sensitive environments.

[0027] Figure 3 schematically illustrates the types of pressure (upper graph) and gas flow rate into the load lock chamber (lower graph) changes determined to minimize substrate contamination during the pump-up phase of substrate manufacturing, according to some embodiments of this disclosure. The drawn pressure curve P(t) is further divided into three phases for ease of consideration. In Phase 1, the pressure in the load lock chamber is relatively low (around 1 Torre, or even lower P). T(Starting with (t)). When the pressure inside the chamber is low, the likelihood of particle separation from the surface (resuspendion) is higher than when the pressure is high. In addition, at low pressure, the rapid increase in pressure P(t) caused by a large flow rate of gas F(t) creates considerable aerodynamic resistance near the particles adsorbed on the surface, which also makes particle separation more likely. For example, if the flow rate F(t) is in units of volume per hour (e.g., cm 3 When measured at a rate of 1 / second, in the case of an adiabatic increase in pressure, dP(t) / dt = γP(t)F(t) / V, where V is the volume of the chamber and γ is the adiabatic index (e.g., γ = 7 / 5 for nitrogen molecules). In the case of an isothermal increase, dP(t) / dt = P(t)F(t) / V. Thus, as seen by the graph at the bottom of Figure 3, Phase 1 is characterized by a relatively low (but continuously increasing) flow rate F(t) and pressure P(t). Phase 1 ("slow vent" phase) continues until a certain level of pressure P(Phase 2), depicted as P6 in Figure 3, is achieved. In some embodiments, the pressure P(Phase 2) is 20-25 Torre, but the pressure P(Phase 2) may vary depending on the volume of the chamber V, the type of gas used, the type and quality of the chamber surface, and the types of adsorbed particles that may be present in the chamber environment. After reaching pressure P (Phase 2), the likelihood of resuspension decreases, allowing for the use of higher flow rates without resuspending many additional particles. As a result, pressure P (Phase 2) ("fast venting") begins. In some implementations, during Phase 2, the flow rate increases relatively rapidly to the maximum amount F max It increases up to a certain level and then is maintained at that level. In some implementations, the flow rate in phase 2 is the maximum amount specified by a human (e.g., a system engineer). In some embodiments, the maximum amount F max This is calculated by pressure and flow rate modeling 224 based on the target duration τ of the pump-up process. In some embodiments, the target duration τ may be determined based on the target throughput (the number of substrates processed within a specified time). In some embodiments, the maximum flow rate F maxThe extreme flow rate F is supported by the dynamic valve 204 and the valve control module 222. ult This is a flow rate comparable to, for example, F max / F ult The values ​​are 0.8, 0.85, 0.9, etc. The ultimate flow rate F ult A somewhat lower maximum flow rate F max The actual pressure P LL (t) lags behind the target curve P(t), and F is used to bring the current pressure dynamics closer to the target curve. max It can be used in examples where an increase in flow rate exceeding a certain threshold is used. In some implementations, when the pressure P(t) approaches the target pressure, for example, the pressure P in the factory interface I When it approaches this point, Phase 3 ("the tail") begins. In Phase 3, the flow rate F(t) is smooth but rapid compared to the flow rate used in Phase 2 (e.g., the maximum pressure F). max ) decreases to zero. For example, the duration of phase 3 is when the pressure is P I Without exceeding the intended pressure P at the intended stage of time τ (counted from the start of the pump-up process) I It is selected in a way that reaches F. For example, assume the time to shut off the dynamic valve so that Δt (this time can be known from the valve specifications or can be determined through empirical testing), and the average flow rate in phase 3 is F. max Assuming a ratio of 2, the average pressure increase in Phase 3 (in the case of isothermal pump-up) is It can be estimated as TIFF2026048632000002.tif11170, In the formula, the pressure at the start of phase 3 is the final pressure P. I It can be further estimated that this is not so different. Therefore, in phase 3, once the pressure in the chamber is It can be started when TIFF2026048632000003.tif11170 is reached. This example is intended to be illustrative only, and many other flow profiles F(t) can achieve implementation forms that have a nearly similar purpose of effective tailing of the pump-up process. There are two advantages to having Phase 3. On the one hand, when P(t) is at any time during the pump-up process P I Even if it exceeds P I No time is wasted lowering the pressure. On the other hand, in Phase 3, the pressure in the load lock chamber and the pressure in the factory interface become exactly equal, and when the gate between the chambers is opened, there is no disturbance in the environment of either chamber (which would otherwise occur if the two pressures were different).

[0028] In some embodiments, the flow rate F(t) is the flow rate F j It is set to a quasi-continuous manner by specifying a separate set of (drawn as black triangles and dotted lines in the graph below Figure 3), for example, when the pressure in the chamber is set to a target pressure value P j To ensure that we follow the set (shown as black circles in the graph above in Figure 3), time t j It can be set by a dynamic valve at a predetermined stage. Several flow rates F (e.g., a few, like three, to dozens or more) j You can specify this. For example, as shown in the unrestricted example in Figure 3, 13 different flow rates are specified over the duration of the pump-up process, where values ​​F0 to F5 perform Phase 1 (corresponding to target pressure values ​​P1 to P6), value F6 performs Phase 2 (corresponding to target pressure values ​​P6 and P7), and values ​​F7 to F 12 This involves implementing Phase 3 (intended pressure P). I (This leads to...)

[0029] Figure 4 is a schematic diagram of an example algorithm 400 used to determine target pressure and target flow rate for a pump-up process that reduces the presence of contaminants in a substrate processing system, according to some embodiments of the present disclosure. The example algorithm 400 can ensure the accuracy of predictions under realistic modeling conditions by using a number of physical and statistical models. In some embodiments, the example algorithm 400 includes a drag force model 410 based on aerodynamic equations. In one example, the drag force model 410 uses the particle size (e.g., diameter) and viscosity (e.g., dynamic or kinematic viscosity) of the gas. The drag force model 410 determines, for example, the aerodynamic flow rate profile near the surface of the chamber (e.g., fluctuations in flow velocity related to distance from the surface) based on the viscosity of the gas, and further determines the force acting on particles adhering to the surface.

[0030] In some embodiments, an example algorithm 400 includes a surface adhesion model 420 that determines the magnitude of the force to be applied to a given particle to separate it from a surface. The particle is characterized by its size, density, and shape (e.g., spherical, elliptical, rod-shaped, etc.). The surface is characterized by its surface roughness, which can include variations in the scale of the sides of the surface profile, the scale of the perpendicular (orthogonal to the surface) of the surface profile, etc. The interaction between the surface and the particle can be modeled using various mechanisms. For example, in one mechanism, the adhesion of the particle to the surface is modeled using a spring model.

[0031] In some embodiments, static or dynamic models are used. In a dynamic model, the resistance is a fluctuating, for example, random function of time, having a specific average value (in the direction of gas flow) and fluctuations before and after that average value (which in itself depends on the average velocity of the gas flow).

[0032] In some embodiments, the output of a resistance force model 410 (characterizing the resistance experienced by particles of various sizes) and a surface adhesion model 420 (characterizing the conditions for particle separation) are used to determine the probability of resuspension for a given particle (block 430). For example, a particle of a given size, placed in a given flow of gas (determined by a specified flow rate F(t) considering a particular chamber geometry), undergoes motion with a specific probability of reaching the conditions for separation from the surface. For example, the resistance force calculated using the resistance force 410 and applied as input to the surface adhesion model 420 can produce a characteristic spring extension Δl(t) as a function of time. Based on the probability that Δl(t) exceeds the threshold extension for particle separation, the probability of resuspension per unit time 430 is determined. In some embodiments, the probability of resuspension (separation) p(F t / F d ) is (i) the threshold force F required to pull a particle away from the surface. t (ii) the actual resistance force F acting on the particle d It is a function (for example, a model function) that depends on the ratio of and . Function p(F t / F d ) can be an exponential function, a power function, or some other function. In some embodiments, p(F t / F d ) is F t / F d As it gets larger (weak resistance), it approaches zero, F t / F d It increases when the resistance decreases (stronger resistance).

[0033] The probability of resuspension 430 can be determined for specific particles (size, shape, etc.) and specific surface conditions (adhesion energy, surface elastic properties, surface roughness, etc.). The probability of resuspension 430 may be used in statistical set averaging 440. Inputs to statistical set averaging 440 also include particle size distribution 450, surface roughness distribution 460, adhesion energy distribution, etc. Statistical set averaging applied to the probability of resuspension determines the average probability of resuspension for the aggregate or particles adhered to the chamber surface. Based on statistical set averaging 440, an integral over time is performed to determine the proportion of remaining particles 470 as a function of time.

[0034] In some embodiments, the proportion of remaining particles is 470, for example, η(t) = η[F(t), V, P T , P I ] is determined considering the type of change in the selected flow rate F(t) with respect to the chamber, which is the initial pressure (e.g., transfer chamber pressure) P T It starts with the final pressure (e.g., factory interface pressure) P IThis determines the dynamics of the pressure P(t) inside the chamber (with respect to the known volume V of the chamber). Various models and blocks of algorithm 400 can be repeated any number of times, for example, within a time increment Δt. For each time increment, the updated conditions after resuspension can be recalculated based on the current pressure P(t) and the newly updated flow rate (F(t+Δt)). The new resistance and the probability of new resuspension are then determined by each block of algorithm 400, and statistical set averaging 440 is performed to obtain the derivative of the percentage of remaining particles, -Δη(t) / Δt. Based on the value of the derivative at each time increment, the final percentage of remaining particles at the end of the pump-up process, η(τ), is determined. As a result, using simulations performed by blocks 410-470, flow rate and pressure optimization 480 identifies the target flow rate F(t) considering the target duration τ and the target percentage of particles remaining adsorbed (adhered to the surface) η(Target). The target percentage of particles depends on the specific technical process being implemented (e.g., by the target quality of the product being manufactured) and can be 70%, 80%, 90%, or any other value.

[0035] Figure 5 illustrates the schematic variations in pressure (upper graph) and gas flow rate (lower graph) from the load lock chamber, determined to minimize liquid condensation during the pump-down phase of substrate manufacturing, according to some embodiments of the present disclosure. A target pressure curve P(t), which can be determined as described below in relation to Figure 6, is shown. The target pressure curve P(t) is determined from the initial pressure P I It starts with, which may be the pressure within the factory interface, and the final pressure P T This continues until it reaches a certain pressure, which may be the pressure inside the transfer chamber. The target flow rate F(t) of the gas flow out of the load lock chamber (used to implement the target pressure P(t)) is schematically shown in the graph below, where the negative sign of the flow rate emphasizes that the gas flow is flowing out of the chamber.

[0036] In some embodiments, the flow rate F(t) is, for example, a predetermined time step t. j A discrete set of flow rates F, such as one set by the controller via a dynamic (continuous) valve. j By specifying (drawn with a dotted line in a black triangle), it is set quasi-continuously. Flow rate F j The pressure inside the chamber reaches the target pressure value P. j The settings are configured to ensure that the flow follows a set of parameters (shown as black circles in the top graph of Figure 5). Flow rate F j The number of these can be at least three, and sometimes even dozens or more.

[0037] Figure 6 schematically illustrates an example algorithm 600 used to determine the target pressure and target flow rate during a pump-down process to reduce liquid condensation in a substrate processing system, according to some embodiments of the present disclosure. The example algorithm 600 can ensure the accuracy of predictions under realistic modeling conditions by using various physical models. In some embodiments, the example algorithm 600 determines a pumping time constant (block 610), which may be the ratio of the chamber volume to the (instantaneous) flow rate F(t). Although referred to as a “constant,” the pumping time constant actually fluctuates with the flow rate. In some embodiments, the example algorithm 600 further determines the ratio of the chamber volume to the surface area for a specific chamber being modeled (block 620). In some embodiments, the example algorithm 600 also determines the heat transfer coefficient (block 630). The heat transfer coefficient indicates how heat is efficiently exchanged between different regions of the chamber (e.g., via convective exchange).

[0038] The determined pumping time constant, chamber volume-to-surface ratio, and heat transfer coefficient can be combined to obtain a dimensionless pumping speed Z (block 640). The dimensionless pumping speed is equal to the threshold humidity RH (for a given value of Z). T(Z) may be used to determine (in block 650). In block 660, the actual input relative humidity RH (block 670) is compared to the threshold humidity. The target flow rate F(t) and target pressure P(t) are then set so that the actual humidity is such that the threshold humidity RH ≤ RH at various (e.g., all) stages of the pump-down process. T The conditions under which (Z) remains below are determined (block 680). In some embodiments, the target flow rate F(t) and target pressure P(t) are determined under the modified condition RH = α·RH T (Z) is obtained, and in this case, a coefficient α < 1 is used so that α = 0.95, 0.9, 0.85, etc., to enhance safety. This additional safety factor can be used as a safety cushion to prevent condensation formation in the event of an unexpected deviation of the pressure inside the chamber from the target pressure (or various other fluctuations in the chamber environment).

[0039] Figure 7A shows an example valve control system 700 that can be used to prevent contamination of products in a substrate processing system during pressure changes, according to some embodiments of the present disclosure. The valve control system 700 uses the same gas flow path during the pump-down and pump-up processes. In some embodiments, the valve control system 700 achieves a type of target flow rate / pressure change determined for a particular manufacturing process by algorithm 400 in Figure 4 and / or algorithm 600 in Figure 6. A load lock chamber 104 is shown in Figure 7A that receives a gas flow 706 from the pump 708 via a continuous (dynamic) valve 710 during the pump-up phase (in the pump-down phase, the direction of the gas flow 706 is reversed). A controller 720 controls the operation of the continuous valve 710. In various implementations, the continuous valve 710 may be a solenoid valve, a butterfly valve, or any other valve capable of continuous flow control. The controller 720 includes one or more processing devices, such as a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), or a network processor. The processing devices are communicatively connected to one or more memory devices, such as read-on memory (ROM), flash memory, static memory, or dynamic random access memory (DRAMA). The controller 720 may be part of a desktop computer, laptop computer, workstation, wearable device (e.g., tablet, smartphone), or cloud-based computing device. In some embodiments, the controller 720 is a dedicated microcontroller configured to perform pump-up and / or pump-down processes in a board processing system. In some embodiments, the controller 720 is part of a larger network of computing devices. In some embodiments, an external computing device communicating with the controller 720 can reconfigure the controller 720 (e.g., change settings, update memory, or otherwise reprogram it).

[0040] In one embodiment, the controller 720 outputs a control signal (e.g., an analog signal) to a power element 722 that provides a voltage or current input to the continuous valve 710. The input provided by the power element 722 changes the internal state of the continuous valve 710. For example, the current output by the power element 722 increases or decreases the magnetic field of a solenoid, causing a magnetically actuated plunger to partially close the opening in order to alter the gas flow 706 to a desired degree. Various other dynamic valves (e.g., ball valves, butterfly valves, flap valves) are possible if continuous control of the gas flow can be used instead of a solenoid valve. The power element 722 may include a battery, generator, capacitor, rechargeable battery, or any other source of current. The power element 722 may further include one or more circuit elements to enable precise control of the output current (or voltage), such as a current / voltage divider, stabilizer, bridge, feedback loop, ammeter, or voltmeter. In some embodiments, the power element 722 includes a DC source. In some embodiments, the power element 722 includes an AC source, which is further used in conjunction with a transformer, rectifier, and other elements.

[0041] The controller 720 (as indicated by the dotted arrow) can perform additional control over the continuous valve 710 using the valve gauge 724. The valve gauge 724 may be (or may include) any sensor that collects data about the internal state of the continuous valve 710. The valve gauge 724 can monitor (e.g., in real time) internal valve metrics that indicate interference with the gas flow 706 by the valve mechanism, which may include the plunger position, flap angle, and the velocity of the gas flow 706 near the compressed region of the valve. The valve gauge 724 acts as an additional check to the controller 720 to verify the settings of the continuous valve 710 and as part of a feedback loop to improve the accuracy of the set gas flow 706. In one example, the controller 720 instructs the power element 722 to output a current I to the continuous valve 710, thereby allowing the gas flow F(I) to pass through it. Meanwhile, the valve gauge 724 indicates that a flow rate F(I)-ΔF smaller than intended is set by the valve gauge 724. The controller 720 then instructs the power element 722 to increase the current to I+ΔI (or decrease it to I-ΔI, depending on the valve design) to compensate for the deficit ΔF. In some examples, compensation is achieved iteratively by incrementing or decrementing the current ΔI (or other signal) multiple times. In some embodiments, instead of (or in addition to) adjusting the signal output by the power element 722, the controller 720 adjusts the settings of the pump 708 to increase the gas flow through the continuous valve 710.

[0042] In some embodiments, the secondary valve 726 allows for additional control over the operation of the continuous valve 710, further improving the precision with which the rate of gas flow into the load lock chamber 104 is set. The secondary valve 726 can be used to control any additional state of the continuous valve 710, the gas flow 706, or the delivery system delivering the gas flow 706. In some embodiments, the secondary valve 726 is integrated with the continuous valve 710, for example, as part of the internal mechanism of the continuous valve 710. For example, the secondary valve 726 can control the size of the opening, the shape of the opening, the distance between the opening and the moving parts of the continuous valve 710, etc. In some embodiments, the secondary valve 726 is located outside the continuous valve 710. For example, the secondary valve 726 can be used to control the cross-sectional area of ​​the delivery line delivering gas from the pump 708 to the continuous valve 710, or the cross-sectional area of ​​the delivery line delivering gas from the continuous valve 710 to the load lock chamber 104. In some embodiments, the secondary valve 726 is connected in parallel to the continuous valve 710, and for example, the secondary valve 726 controls the gas flow through a bypass around the continuous valve 710. In some embodiments, the secondary valve 726 is also a continuous valve, such as a proportional valve, whose settings are determined proportionally to a signal from the controller 720. In some embodiments, the secondary valve 726 has several distinct settings. For example, when the gas flow 706 is increased (or decreased), the controller 720 causes the secondary valve 726 to discontinuously change the size (e.g., cross-section) of the opening of the continuous valve 710 (e.g., by an increment of ΔA). At the same time, the control signal provided to the continuous valve 710 is also discontinuously changed (e.g., by shortening the distance from the solenoid plunger to the opening) to compensate for the change in the opening and ensure that the gas flow rate increases continuously even as the opening changes. Subsequently, the setting of the secondary valve 726 remains fixed for a period of time, and the setting of the continuous valve 710 changes continuously until the next change in a different setting of the secondary valve 726. This process is repeated until that stage (pump-down or pump-up) is complete.

[0043] The pressure sensor 208 enables overall control over the pump-up and pump-down processes described above in relation to Figures 3 and 5. The pressure readings from the pressure sensor 208 received by the controller 720 enable the controller 720 to determine whether the pump-up or pump-down process is being carried out according to the target profile P(t) identified in relation to Figures 4 and 6. Depending on whether the process is ahead or behind the target schedule, the controller 720 increases or decreases the flow rate by adjusting the settings of the continuous valve 710 and optionally the secondary valve 726.

[0044] Figure 7B shows another example of a valve control system 701, which can be used to prevent contamination of products in a substrate processing system during pressure changes, according to some embodiments of the present disclosure. The valve control system 701 uses different gas flow paths during the pump-down and pump-up processes. As schematically depicted, during the pump-up phase, the gas flow 716 to the load lock chamber 104 can be provided by a gas supply source 718, which may be (or include) a pressurized gas container, a pump, and / or other suitable components and devices. The gas flow 716 can be controlled by any continuous valve, similar to how the continuous valve 710 of the valve control system 700 depicted in Figure 7A controls the gas flow 706 (e.g., using a power element 722 that receives a control signal from the controller 720). The continuous valve may be a solenoid valve 730 (as depicted), a proportional valve, a butterfly valve, or any other valve that allows continuous (or semi-continuous) adjustment of the flow rate. The state of the solenoid valve 730 can be monitored by the controller 720 using a valve gauge 724.

[0045] During the pump-down phase, the controller 720 can close the solenoid valve 730 (or any other continuous valve) to stop the gas flow 716 from flowing into the load lock chamber 104. The controller 720 can also initiate the gas flow 736 out of the load lock chamber 104 by having another continuous valve, such as a butterfly valve 732, control the gas flow 736. The butterfly valve 732 is shown in Figure 7B, but the gas flow 736 may also be controlled by, for example, a solenoid valve, a proportional valve, or any continuous valve capable of continuous (or semi-continuous) flow rate adjustment. The gas flow 736 can be sustained by a pump 709, which can be separated from the gas supply source 718. In some embodiments, the pump 709 can direct the gas flow to the gas supply source 718, which is to be reused during the subsequent pump-up phase. In some embodiments, the gas flow may be directed to an exhaust port (not shown) and not reused during the pump-up phase. The state of the butterfly valve 732 can be set by a power element 723 controlled by a controller 720. The power element 723 can be separated from the power element 722 (as depicted), and in some embodiments, the power elements 723 and 722 can be combined into a single power source. The state of the butterfly valve 732 can be monitored by the controller 720 using a valve gauge 725. In some embodiments, additional (secondary) valves may be connected in parallel or in series to the solenoid valve 730 and / or butterfly valve 732, as described more in detail above in relation to Figure 7A.

[0046] Figures 8 to 10 are flowcharts of methods 800, 900, and 1000, respectively, for implementing effective contamination prevention during pressure changes in a substrate processing system. In some embodiments, methods 800, 900, and 1000 are performed using the systems and components shown in Figures 1, 2, and 7 or any combination thereof. In some embodiments, methods 800, 900, and 1000 are performed by the computing device 210 in Figure 2 or the controller 720 in Figures 7A and 7B. Methods 800, 900, and 1000 can be performed by one or more processing units (e.g., CPU and / or GPU), which include (or communicate with) one or more memory devices. In some embodiments, methods 800, 900, and 1000 are performed by a number of processing threads (e.g., CPU threads and / or GPU threads), each thread performing one or more individual functions, routines, subroutines, or operations of the method. In some embodiments, the processing threads that perform methods 800, 900, and 1000 are synchronized (e.g., using semaphores, critical areas, and / or other thread synchronization mechanisms). Alternatively, the processing threads that perform methods 800, 900, and 1000 are performed asynchronously with respect to each other. The various operations of methods 800, 900, and 1000 are performed in a different order than the order shown in Figures 8 to 10. Some operations of the methods may be performed simultaneously with others. In some embodiments, one or more operations shown in Figures 8 to 10 are not always performed.

[0047] Figure 8 is a flowchart of Method 800, which defines a pressure change to minimize contamination within a substrate processing system, according to some embodiments of the present disclosure. In some embodiments, Method 800 defines a pressure change within a load lock chamber (LLC) of a substrate processing system (SPS), but it should be understood that Method 800 (and Methods 900 and 1000 described below) can also be used in relation to pressure changes within any other sealable chamber or compartment of the SPS.

[0048] In block 810, method 800 includes sealing a chamber (hereinafter referred to as the first chamber) from an external environment, the external environment including any other chambers (e.g., the second chamber) or compartments of the SPS adjacent to or otherwise coupled to the first chamber. For example, a gate can be configured to separate the first chamber from the second chamber so as to selectively seal and open the first chamber from the second chamber. The gate may be communicably connected to a controller that causes the gate to selectively seal and open the first chamber.

[0049] In block 820, method 800 may include a processing device that continuously regulates the flow of gas into a first chamber over a target time period (e.g., using the systems and components depicted in Figures 7A and 7B). The target time period may be set by the user / operator of the SPS and / or specified by the technical process being performed using the SPS. The regulation of the gas flow rate may be facilitated by a valve (hereinafter referred to as the first valve) configured to continuously regulate the flow of gas into the first chamber. The first valve may also be communicably connected to a controller (e.g., directly or via an intermediate electronic circuit, the intermediate electronic circuit may include power elements or other electronic circuits). In some implementations, the first valve is a proportional valve or any other valve that continuously regulates the flow of gas passing through it in response to a continuous control signal input to the first valve. In a non-limiting example, the first valve comprises a coil (solenoid). The input signal (referred to herein as the first input signal) is configured to cause the coil to generate a magnetic field that fluctuates continuously over a target time period.

[0050] In some embodiments, the system performing method 800 further includes a second valve configured to adjust the internal state of a first valve, such as the opening of the first valve. The second valve can be used for additional adjustability of the first valve. More specifically, the controller causes the second valve to receive a second input signal configured to cause the second valve to adjust the opening of the first valve. In some embodiments, the first and second input signals are received simultaneously by the respective valves.

[0051] In some embodiments, for example in the pump-up process, the gas flow into the first chamber is regulated by a first valve so that it increases from a relatively small value to a higher target flow after the pressure inside the first chamber exceeds a target pressure. The target pressure, e.g., 20-25 Torre, can depend on the volume and shape of the first chamber. The target pressure can be determined using experimental testing, simulation, or both, and can be based on the observation that the rate of resuspendion of adsorbed particles decreases after the pressure increases above a certain value.

[0052] In block 830, method 800 determines the pressure in the first chamber to minimize the generation of one or more contaminants in the first chamber of the SPS using a time curve (e.g., P(t)) or a target pressure value (e.g., P j This includes following a temporal sequence of the actual pressure (e.g., P) in the first chamber. In some embodiments, this includes following a temporal sequence of the actual pressure (e.g., P) in the first chamber. LLTo monitor how closely (t) follows a temporal curve (or temporal sequence of target pressure values), a system performing Method 800 further includes a pressure sensor that continuously detects the pressure inside the first chamber and transmits the detected pressure to a controller. Upon receiving the detected pressure, the controller adjusts the first input signal taking the transmitted pressure into account. Additionally, a system performing Method 800 may include a gauge that continuously detects the state of a first valve and transmits the detected state of the first valve to a controller. Upon receiving the detected state, the controller adjusts the first input signal taking the transmitted state of the first valve into account. The adjustment of the first input signal causes the pressure inside the first chamber of the SPS to follow a temporal curve (or temporal sequence of target pressure values) determined to minimize the generation of one or more contaminants in the first chamber.

[0053] In some embodiments, the temporal sequence of target pressure values ​​is determined to reduce the degree of particle resuspension in the first chamber of the SPS during a first time period. For example, the first time period may be the duration of the pump-up process. In some embodiments, in addition to the pump-up process, method 800 is also used during the pump-down process. For example, during a second time period, the controller causes a first valve to receive a second input signal. The second input signal may be configured to cause the first valve to continuously regulate the flow of gas out of the first chamber of the SPS over the second time period. More specifically, the second input signal may be configured so that the pressure inside the first chamber follows another temporal curve (or another temporal sequence of target pressure values) determined to reduce condensation (aerosolization) inside the first chamber of the SPS during the second time period.

[0054] Figure 9 is a flowchart of a method 900 for moving a substrate from a first compartment of an SPS to a second compartment of an SPS, according to some embodiments of the present disclosure, while minimizing the substrate's exposure to contaminants. The term “compartment” refers to any chamber of an SPS, or any other part or component of an SPS, that can be isolated from other parts or components of the SPS. The movement of the substrate can be carried out through an intermediate third compartment (e.g., a load lock chamber, an air lock chamber, a transfer chamber, etc.). In block 910, the method 900 includes opening a first gate between the first compartment and the third compartment, for example, between the transfer chamber and the load lock chamber. In block 920, the method 900 continues by moving the substrate from the first compartment to the third compartment. With the substrate in the third compartment, in block 930, the first gate is closed to isolate the third compartment from the first compartment, and in block 940, a second gate is controlled to isolate the third compartment from the second compartment. All or part of blocks 910-940 can be performed based on instructions from a processing device that implements method 900. In block 950, method 900 includes the processing device initiating a gas flow. In the case of a pump-up process, the gas flow flows into the third compartment, while in the case of a pump-down process, the gas flow flows out of the third compartment.

[0055] In block 960, method 900 continues by ensuring that the processing device, in each of multiple cycles, has a gas flow rate that corresponds to a target reference flow rate (RFR) for each of several RFRs. The multiple RFRs can be determined based on modeling that minimizes the generation of contaminating particles in the third compartment caused by the gas flow. Due to the gas flow, the pressure in the third compartment changes from an initial pressure to a final pressure. In an unrestricted example, during the pump-up process, the initial pressure is less than 10 Torr and the final pressure is greater than 700 Torr. Similarly, during the pump-down process, the initial pressure is greater than 700 Torr and the final pressure is less than 10 Torr.

[0056] Method 900 may then be continued by the processing device opening the second gate (block 970) and moving the substrate from the third compartment to the second compartment (block 980) in response to the pressure in the third compartment changing from the initial pressure to the final pressure.

[0057] Figure 10 is a flowchart of Method 1000, according to some embodiments of the present disclosure, which models the types of pressure and flow rate changes that minimize the generation of contaminants in a substrate processing system. Method 1000 may be performed by the computing device 210 in Figure 3 or any other computing device. Method 1000 may be performed in conjunction with Method 800 in Figure 8 and / or Method 900 in Figure 9. In some embodiments, Method 1000 may be performed in real time concurrently with Method 800 and / or Method 900. In some embodiments, Method 1000 may be performed before Method 800 and / or Method 900, with the output of Method 1000 (e.g., target pressure dynamics and target flow dynamics) stored and used while Method 800 and / or Method 900 are being executed.

[0058] In some embodiments, Method 1000 determines a target pressure P(t) and a target flow rate F(t) with respect to the pump-up phase of operation of the load lock chamber or any other compartment of the substrate processing system. In block 1010, Method 1000 includes using a first model to characterize the resistive force acting on contaminant particles adsorbed on the surface of the chamber (e.g., the third compartment of Method 900). In some embodiments, inputs to the first model include various other parameters such as the viscosity of the gas (e.g., kinematic viscosity), the velocity of the gas near the surface of the compartment, and parameters characterizing the geometry of the chamber (e.g., volume, area, and shape), the density of the gas, the temperature of the gas, and the type of gas (monatomic, diatomic, etc.). In some embodiments, the velocity of the gas near the surface of the chamber is determined based on the rate of gas flow into the chamber.

[0059] In block 1020, method 1000 continues by characterizing the affinity of contaminating particles to the chamber surface using a second model. In some embodiments, the second model determines a threshold force for the separation of contaminating particles from the chamber surface. The threshold force may depend on the radius of the contaminating particles, which is used as an input to the second model. Other inputs may include the strength of the attractive force (e.g., van der Waals interaction) between the contaminating particles and the chamber surface. For example, the strength of the attractive force may be parameterized using an adhesion energy that depends on the type of material of the contaminating particles, the radius of the contaminating particles (or any other dimensions), the roughness of the chamber surface, etc.

[0060] In block 1030, method 1000 continues by using the outputs of the first and second models to determine the instantaneous probability of resuspending contaminating particles from the surface of the third compartment. The instantaneous probability of resuspending refers to the probability that contaminating particles (e.g., particles of a certain size) will resuspend from the surface, assuming specific instantaneous values ​​of the gas pressure and temperature, as well as the gas flow rate into the chamber. As the instantaneous values ​​change (e.g., over the duration of the pump-up process), the instantaneous probability of resuspending also changes.

[0061] In block 1040, method 1000 continues by determining the percentage of contaminating particles remaining adsorbed on the chamber surface after a target duration for which the pressure changes from the initial pressure to the final pressure. The operation of block 1040 can use instantaneous probability (determined during the operation of block 1030) as input, and further use expected flow rate F1(t) (and dynamics P1(t) occurring immediately after the pressure in the chamber) as additional inputs. Various other expected flow rates F2(t), F3(t), ... (and their respective pressure dynamics P(t), P3(t), ...) can be used as other inputs. Different input flow rates can correspond to different durations of the pump-up process. Some processes may be relatively short (and thus have relatively high maximum flow rates), while others may be longer (and correspondingly have lower maximum flow rates). For each input, a processing device performing method 1000 can calculate the percentage of contaminating particles remaining on the surface. For example, a shorter, and therefore more aggressive, pump-up process may have a smaller percentage of particles remaining adsorbed on the surface.

[0062] In block 1050, method 1000 continues by the processing device selecting a target change in flow rate F(t) (and pressure P(t)) from a variety of possible input change types. In some embodiments, a continuous curve F(t) (and the respective curves P(t)) can be selected. In other embodiments, a plurality of distinct target flow rates F(t1), F(t2), ... (reference flow rates) can be selected. The selected (continuous or distinct) flow rates F(t) (and pressure P(t)) can then be stored for use in the pump-down process (e.g., as described in relation to methods 800 and 900 above). The (continuous or distinct) target flow rates are therefore determined based on (i) the target duration for changing the pressure in the chamber from the initial pressure to the final pressure, and (ii) the target percentage of contaminating particles that remain adsorbed on the surface of the chamber. The target percentage may depend on the details of the particular technical process being implemented and the corresponding requirements for the quality of the resulting product (e.g., wafers).

[0063] Figure 11 shows a block diagram of an example computing device 1100 operating according to one or more embodiments of the present disclosure. The computing device 1100 may be the computing device 210 in Figure 2, or the controller 720 in Figures 7A and 7B, or any other processing device or combination of processing devices that perform the method 800 for defining pressure changes to minimize the generation of contaminants in a manufacturing system, the method 900 for moving a substrate from a first compartment to a second compartment of an SPS, and / or the method 1000 for modeling the types of pressure and flow rate changes to minimize the generation of contaminants in a substrate processing system.

[0064] One example computing device 1100 may be connected to other processing devices in a LAN, intranet, extranet and / or the Internet. The computing device 1100 may be a personal computer (PC), a set-top box (STB), a server, a network router, a switch or bridge, or any device capable of executing a set of instructions (sequential or not) that specify the actions that the device should take. Furthermore, although only one example processing device is illustrated, the term “processing device” should also be interpreted to include any set of processing devices (e.g., computers) that individually or collectively execute a set of instructions (or more sets) to perform one or more of the methods considered herein.

[0065] An example computing device 1100 may include a processing device 1102 (e.g., a CPU), main memory (e.g., read-only memory (ROM), flash memory, dynamic random access memory (DRAMA) such as synchronous DRAM (SDRAM), static memory 1106 (e.g., flash memory, static random access memory (SRAM), etc.), and secondary memory (e.g., a data storage device 1108) that can communicate with each other via a bus 1130.

[0066] The processing device 1102 represents one or more general-purpose processing devices, such as a microprocessor or a central processing unit. More specifically, the processing device 1102 may be a composite instruction set computing (CISC) microprocessor, a reduced instruction set computing (RISC) microprocessor, a very long instruction word (VLIW) microprocessor, a processor that implements other instruction sets, or a processor that implements a combination of instruction sets. The processing device 1102 may also be one or more special-purpose processing devices, such as an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), a digital signal processor (DSP), or a network processor. According to one or more aspects of this disclosure, the processing device 1102 may include processing logic 1126 that may be configured to execute instructions for a method 800 that defines pressure changes to minimize the generation of contaminants in a manufacturing system, a method 900 that moves a substrate from a first compartment to a second compartment of an SPS, and / or a method 1000 that models the type of pressure and flow rate changes that minimize the generation of contaminants in a substrate processing system.

[0067] An example computing device 1100 may further include a network interface device 1108, which may be communicatively connected to a network 1120. An example computing device 1100 may further include a video display 1110 (e.g., a liquid crystal display (LCD), a touchscreen or a cathode ray tube (CRT)), a character / number input device 1112 (e.g., a keyboard), an input control device 1114 (e.g., a cursor control device, a touchscreen control device, a mouse), and a signal generation device 1116 (e.g., an acoustic speaker).

[0068] The data storage device 1118 may include a computer-readable storage medium (or more specifically, a non-temporary computer-readable storage medium) 1128 in which one or more sets of executable instructions 1122 are stored. According to one or more aspects of the present disclosure, the executable instructions 1122 may include executable instructions that perform a method 800 for defining pressure changes to minimize the generation of contaminants in a manufacturing system, a method 900 for moving a substrate from a first compartment to a second compartment of an SPS, and / or a method 1000 for modeling types of pressure and flow rate changes to minimize the generation of contaminants in a substrate processing system.

[0069] The executable instruction 1122 may also be fully or at least partially present in the main memory 1104 and / or the processing device 1102 during its execution by an example computing device 1100, main memory 1104, and processing device 1102. The executable instruction 1122 may also be further transmitted or received over a network via the network interface device 1108.

[0070] Although the computer-readable storage medium 1128 is shown as a single medium in Figure 11, the term “computer-readable storage medium” should be interpreted to include single or multiple mediums (e.g., centralized or distributed databases and / or associated caches and servers) that store one or more sets of operational instructions. The term “computer-readable storage medium” should also be interpreted to include any medium capable of storing or encoding a set of instructions for execution by a machine, causing the machine to perform any one or more of the methods described herein. The term “computer-readable storage medium” should therefore be interpreted to include, but not limited to, solid-state memory, as well as optical and magnetic media.

[0071] The following examples illustrate further implementations of the current disclosure.

[0072] In Example 1, the system includes a load lock chamber (LLC) of a substrate processing system, which includes one or more valves that regulate the flow of gas that is guided into or out of the LLC, and a controller configured to initiate the flow of gas through one or more valves while the LLC is sealed from the external environment, and to match the rate of gas flow to each of a plurality of reference flow rates (RFRs) at each of a plurality of time intervals, wherein the plurality of RFRs include at least three RFRs and are determined to minimize the generation of one or more contaminants in the environment of the LLC.

[0073] In Example 2, in the system of Example 1, multiple RFRs are determined considering the initial pressure, the final pressure, and the target duration of the transition of the LLC environment from the initial pressure to the final pressure.

[0074] In Example 3, in the system of Example 1, one or more contaminants appear in the LLC environment during the transition of the LLC environment from initial pressure to final pressure.

[0075] In Example 4, the system of Example 3 further includes a pressure sensor communicatively connected to a controller, the controller further receives a current pressure reading from the pressure sensor, obtains the difference between the received current pressure reading and each of a plurality of reference pressure values, each of which is associated with the current stage of time, and is configured to adjust the rate of gas flow through one or more valves to mitigate the obtained difference.

[0076] In Example 5, in the system of Example 1, one or more valves are configured to continuously regulate the gas flow.

[0077] In Example 6, in the system of Example 1, the gas flow is guided into the LLC, and multiple RFRs are selected to minimize the resuspension of particulate matter from the inside of the LLC within the LLC environment.

[0078] In Example 7, in the system of Example 1, the gas flow is guided to flow out of the LLC, and multiple RFRs are selected to prevent aerosol formation in the LLC environment.

[0079] In Embodiment 8, the system includes a substrate processing system (SPS) comprising a first chamber and a second chamber; a first gate configured to selectively seal and open the first chamber of the SPS from the second chamber of the SPS; a first valve configured to continuously regulate the flow of gas into the first chamber of the SPS; and a controller communicatively connected to the first gate and the first valve, wherein the first gate is configured to seal the first chamber of the SPS from the second chamber of the SPS, and the first valve is configured to receive a first input signal, the first input signal causing the first valve to continuously regulate the flow of gas into the first chamber of the SPS over a first time period.

[0080] In Example 9, in the system of Example 8, the first input signal is configured such that the pressure inside the first chamber of the SPS follows a temporal sequence of target pressure values.

[0081] In Example 10, in the system of Example 9, the temporal sequence of target pressure values ​​is determined to reduce the degree of particle resuspension in the first chamber of the SPS during the first time period.

[0082] In Example 11, in the system of Example 8, the controller is further configured to cause the first valve to receive a second input signal, which causes the first valve to continuously adjust the flow of gas out of the first chamber of the SPS over a second time period.

[0083] In Example 12, in the system of Example 11, the second input signal is configured such that the pressure inside the first chamber of the SPS follows a temporal sequence of target pressure values, and the temporal sequence of target pressure values ​​is determined to reduce condensation inside the first chamber of the SPS during the second time period.

[0084] In Example 13, the first valve in the system of Example 8 is a proportional valve.

[0085] In Example 14, in the system of Example 13, the first valve includes a coil, and the first input signal is configured to cause the coil to generate a magnetic field that fluctuates continuously over a first time period.

[0086] In Example 15, the system of Example 8 further includes a second valve configured to adjust the opening of a first valve, the controller further configured to cause the second valve to receive a second input signal, the second input signal configured to cause the second valve to adjust the opening of the first valve.

[0087] In Example 16, in the system of Example 8, the gas flow into the first chamber of the SPS over a first time period is increased to a target flow rate after the pressure inside the first chamber of the SPS exceeds the target pressure.

[0088] In Example 17, the system of Example 8 further includes a pressure sensor that continuously detects the pressure inside the first chamber of the SPS and transmits the detected pressure to a controller, the controller being configured to adjust a first input signal in consideration of the transmitted pressure.

[0089] In Example 18, in the system of Example 17, the first input signal is adjusted so that the pressure inside the first chamber of the SPS follows a time curve determined to minimize the generation of one or more contaminants inside the first chamber of the SPS.

[0090] In Example 19, in the system of Example 8, the first valve includes a gauge that continuously detects the state of the first valve and transmits the detected state of the first valve to a controller, and the controller is configured to adjust the first input signal taking into account the transmitted state of the first valve.

[0091] In Example 20, the system of Example 8 further includes a second gate configured to selectively seal and open a first chamber of the SPS from a third chamber of the SPS, and a second valve configured to continuously regulate the flow of gas out of the first chamber of the SPS, wherein the controller is further configured to communicate with the second gate and the second valve, and is configured to cause the second gate to seal the first chamber of the SPS from the third chamber of the SPS, and the second valve to receive a first input signal, the first input signal causing the second valve to continuously regulate the flow of gas out of the first chamber of the SPS over a second time period.

[0092] In Example 21, the method includes sealing the chamber of the substrate processing system (SPS) from the external environment, continuously adjusting the flow of gas into or out of the chamber over a target time period, and ensuring that the pressure inside the chamber of the SPS follows a time curve determined to minimize the generation of one or more contaminants inside the chamber of the SPS.

[0093] In Example 22, the method for moving a substrate from a first compartment of a substrate processing system (SPS) to a second compartment of the SPS is to open a first gate between the first and third compartments of the SPS, move the substrate from the first compartment to the third compartment, close the first gate to isolate the third compartment from the first compartment, control the second gate to isolate the third compartment from the second compartment, and start a gas flow, wherein the gas flow is (i) a gas flow into the third compartment, or (ii) a gas flow out of the third compartment. One of these is to initiate and ensure that the rate of gas flow has a target reference flow rate (RFR) for each of several RFRs at each of several time points, wherein the RFRs have a target reference flow rate (RFR) for each of several RFRs, which is determined based on modeling to minimize the generation of contaminating particles in a third compartment caused by the gas flow, and to open a second gate and move the substrate from the third compartment to the second compartment in response to a change in pressure in the third compartment from an initial pressure to a final pressure.

[0094] In Example 23, in the method of Example 22, the gas flow is to a third compartment, and the modeling includes a first model that characterizes the resistance force acting on contaminant particles adsorbed on the surface of the third compartment.

[0095] In Example 24, in the method of Example 23, the input to the first model includes the viscosity of the gas and the velocity of the gas near the surface of the third compartment, the gas velocity being determined based on the rate of gas flow into the third compartment.

[0096] In Example 25, the modeling in the method of Example 23 includes a second model that characterizes the affinity of contaminating particles to the surface of the third compartment.

[0097] In Example 26, the modeling in the method of Example 25 includes determining the instantaneous probability of resuspending contaminating particles from the surface of the third compartment using the outputs of the first and second models.

[0098] In Example 27, the modeling in the method of Example 23 includes determining the percentage of contaminating particles that remain adsorbed on the surface of the third compartment after a target duration for which the pressure in the third compartment changes from an initial pressure to a final pressure.

[0099] In Example 28, in the method of Example 23, the number of RFRs is further determined based on (i) the target duration for changing the pressure in the third compartment from the initial pressure to the final pressure, and (ii) the target percentage of contaminating particles that remain adsorbed on the surface of the third compartment.

[0100] In Example 29, in the method of Example 22, the initial pressure is one of a first pressure less than 10 Torre or a second pressure greater than 700 Torre, and the final pressure is another one of a first pressure less than 10 Torre or a second pressure greater than 700 Torre.

[0101] In Example 30, in the method of Example 22, the gas flow exits from the third compartment, and the contaminants are water particles.

[0102] In Example 31, the modeling in the method of Example 30 includes determining the threshold pressure of each of several threshold pressures related to the condensation of water particles at each of several time points.

[0103] In Example 32, in the method of Example 31, each of the target RFRs is at or below its respective threshold pressure.

[0104] In Example 33, the system includes a substrate processing system comprising a first compartment, a second compartment and a third compartment, a first gate that isolates the third compartment from the first compartment, a second gate that isolates the third compartment from the second compartment, a valve configured to adjust the flow rate of gas to the third compartment, wherein the gas flow is either (i) a gas flow into the third compartment or (ii) a gas flow out of the third compartment, and a valve that starts the gas flow, wherein the gas flow is either (i) a gas flow into the third compartment or (ii) ii) A controller comprising one of the gas flows out of a third compartment, the proportion of which the gas flow has a target RFR for each of a plurality of reference flow rates (RFRs), the plurality of RFRs being determined based on modeling to minimize the generation of contaminating particles in the third compartment caused by the gas flow, and which opens a first gate and a second gate in response to a change in pressure in the third compartment from an initial pressure to a final pressure, so that the substrate moves from the first compartment to the second compartment through the third compartment.

[0105] In Example 34, in the system of Example 33, the gas flow enters a third compartment, and the modeling includes a first model that characterizes the resistance force acting on contaminant particles adsorbed on the surface of the third compartment.

[0106] In Example 35, the modeling in the system of Example 34 includes a second model that characterizes the affinity of contaminating particles to the surface of the third compartment.

[0107] In Example 36, in the system of Example 33, the gas flow exits from a third compartment, the contaminants are water particles, and the modeling involves determining the threshold pressure of each of several threshold pressures associated with the condensation of water particles at each of several time points.

[0108] In Example 37, in the system of Example 36, each of the target RFRs is at or below its respective threshold pressure.

[0109] In Example 38, a non-temporary computer-readable memory storing instructions, when executed by a processing device, instructs the processing device to isolate a first section of the substrate processing system (SPS) from a second section of the SPS at a first gate, isolate a third section of the SPS from a second section of the SPS at a second gate, initiate a gas flow, the gas flow being either (i) a gas flow into the second section, or (ii) a gas flow out of the second section, the rate of the gas flow being such that, at each of several time points, each of several RFRs has a target reference flow rate (RFR), the RFRs being determined based on modeling to minimize the generation of contaminating particles in the second section caused by the gas flow, and to open the first and second gates in response to a change in pressure in the third section from an initial pressure to a final pressure, thereby moving the substrate from the first section to the third section via the second section.

[0110] In Example 39, in the non-temporary computer-readable memory of Example 38, the gas flow flows into a second compartment, and the modeling includes a first model characterizing the resistance force acting on contaminant particles adsorbed on the surface of the second compartment, and a second model characterizing the affinity of the contaminant particles to the surface of the second compartment.

[0111] In Example 40, in the non-temporary computer-readable memory of Example 38, the gas flow exits from a second compartment, the contaminating particles are water particles, and the modeling involves determining the respective threshold pressures of multiple threshold pressures associated with the condensation of water particles at each of multiple time points.

[0112] It should be understood that the above description is intended to be illustrative and not limiting. Many other implementation examples will be apparent to those skilled in the art upon reading and understanding the above description. While this disclosure describes specific embodiments, it should be understood that the systems and methods of this disclosure are not limited to the embodiments described herein and may be implemented in modified forms within the scope of the appended claims. Therefore, the specification and drawings should be considered illustrative, not limiting. The scope of this disclosure should therefore be determined by referring to the appended claims, along with the entire scope of the equivalent for which such claims are granted.

[0113] The methods, hardware, software, firmware, or code implementations described above may be carried out by the processing element via machine-accessible media, machine-readable media, computer-accessible media, or instructions or code stored on computer-readable media. "Memory" includes any mechanism that provides (i.e., stores and / or transmits) information in a format readable by a machine, such as a computer or electronic system. For example, "memory" includes random-access memory (RAM), such as static RAM (SRAM) or dynamic RAM (DRAM), ROM, magnetic or optical storage media, flash memory devices, electrical storage devices, optical storage devices, acoustic storage devices, and any type of existing machine-readable media suitable for storing or transmitting electronic instructions or information in a format readable by a machine (e.g., a computer).

[0114] Throughout this specification, any reference to “one embodiment” or “one embodiment” means that certain features, structures, or characteristics described in connection with this embodiment are included in at least one embodiment of this disclosure. Thus, the phrases “in one embodiment” or “in one embodiment” appear in various places throughout this specification, but they do not all necessarily refer to the same embodiment. Furthermore, certain features, structures, or characteristics may be combined in any preferred manner in one or more embodiments.

[0115] In the above-mentioned specification, detailed descriptions are provided with reference to specific example embodiments. However, it will be apparent that various modifications and changes may be made thereto without departing from the broader spirit and scope of this disclosure as described in the appended claims. The specification and drawings should therefore be considered illustrative, not restrictive. Furthermore, the above-mentioned uses of embodiments, embodiments and / or other exemplary phrases do not necessarily refer to the same embodiment or example, but may refer to different distinct embodiments, and similarly, in some cases, to the same embodiment.

[0116] The phrases “example” or “illustration” are used herein to mean that they serve as embodiments, examples, or illustrations. No aspect or design described herein as “example” or “illustration” should necessarily be construed as being preferable or advantageous to any other aspect or design. Rather, the phrases “example” or “illustration” are intended to present a concept in a practical way. When used in this application, the term “or” is intended to mean inclusive “or” rather than exclusive “or.” That is, unless otherwise specified or is not evident from the context, “X includes A or B” is intended to mean any of the natural inclusive permutations. That is, if X includes A, X includes B, or X includes both A and B, then “X includes A or B” is satisfied under any of the examples above. In addition, the articles “a” and “an,” as used in this application and in the attached claims, should be broadly interpreted as meaning “one or more,” unless otherwise specified or it is clear from the context that they are to be singular. Furthermore, the use of the terms “a certain embodiment” or “one implementation” or “a certain embodiment” or “one embodiment” throughout this document is not intended to mean the same embodiment or embodiment unless otherwise stated. Also, terms such as “first,” “second,” “third,” “fourth,” as used herein, mean indicators for distinguishing different elements and do not necessarily mean an order by numerical designation.

Claims

1. A load lock chamber (LLC) for a substrate processing system, having one or more valves that regulate the flow of gas that is guided to flow into or out of the LLC, It is a controller, With the LLC sealed from the external environment, the flow of gas through one or more valves is started. The rate of gas flow is matched to each of several reference flow rates (RFRs) at each of several time periods, and the several RFRs include at least three RFRs and are determined to minimize the generation of one or more contaminants in the environment of the LLC. A system comprising a controller configured in such a way.

2. The system according to claim 1, wherein the plurality of RFRs are determined taking into consideration the initial pressure, the final pressure, and the target duration of the transition of the environment of the LLC from the initial pressure to the final pressure.

3. The system according to claim 1, wherein one or more contaminants appear in the environment of the LLC during the transition of the environment of the LLC from initial pressure to final pressure.

4. The controller further comprises a pressure sensor that is communicably connected to the controller, and the controller further comprises The current pressure reading is received from the aforementioned pressure sensor. The difference between the received current pressure reading and each of the multiple reference pressure values ​​is obtained, and each of the reference pressure values ​​is associated with the current time. To mitigate the difference obtained, adjust the ratio of the gas flow through one or more valves. The system according to claim 3, configured as described above.

5. The system according to claim 1, wherein one or more valves are configured to continuously regulate the flow of gas.

6. The system according to claim 1, wherein the flow of gas is guided into the LLC, and the plurality of RFRs are selected to minimize the resuspension of particulate matter from the inner surface of the LLC within the environment of the LLC.

7. The system according to claim 1, wherein the flow of gas is guided to flow out of the LLC, and the plurality of RFRs are selected to prevent aerosol formation of the LLC in the environment.

8. A substrate processing system (SPS) including a first chamber and a second chamber, A first gate configured to selectively seal and open the second chamber of the SPS from the first chamber of the SPS, A first valve configured to continuously adjust the gas flow of the SPS into the first chamber, A controller that is communicatively connected to the first gate and the first valve, The first gate seals the first chamber of the SPS away from the second chamber of the SPS. A system comprising a controller, the first valve being configured to receive a first input signal, the first input signal being configured to cause the first valve to continuously adjust the flow of gas from the SPS into the first chamber over a first time period.

9. The system according to claim 8, wherein the first input signal is configured such that the pressure inside the first chamber of the SPS follows a temporal sequence of target pressure values.

10. The system according to claim 9, wherein the temporal sequence of the target pressure values ​​is determined to reduce the degree of particle resuspension in the first chamber of the SPS during the first time period.

11. The system according to claim 8, wherein the controller is further configured to cause the first valve to receive a second input signal, and the second input signal causes the first valve to continuously adjust the flow of gas flowing out of the first chamber of the SPS over a second time period.

12. The second input signal is configured such that the pressure inside the first chamber of the SPS follows a temporal sequence of target pressure values. The system according to claim 11, wherein the temporal sequence of the target pressure values ​​is determined to reduce condensation of the SPS in the first chamber during the second time period.

13. The system according to claim 8, wherein the first valve is a proportional valve.

14. The system according to claim 13, wherein the first valve comprises a coil, and the first input signal is configured to cause the coil to generate a magnetic field that fluctuates continuously over a first time period.

15. The system according to claim 8, further comprising a second valve configured to adjust the opening of the first valve, wherein the controller is further configured to cause the second valve to receive a second input signal, the second input signal being configured to cause the second valve to adjust the opening of the first valve.

16. The system according to claim 8, wherein the flow of gas into the first chamber of the SPS over the first time period is increased to a target flow rate after the pressure inside the first chamber of the SPS exceeds a target pressure.

17. The system according to claim 8, further comprising a pressure sensor that continuously detects the pressure inside the first chamber of the SPS and transmits the detected pressure to the controller, wherein the controller is configured to adjust the first input signal in consideration of the transmitted pressure.

18. The system according to claim 17, wherein the first input signal is adjusted so that the pressure inside the first chamber of the SPS follows a time curve determined to minimize the generation of one or more contaminants inside the first chamber of the SPS.

19. The system according to claim 8, wherein the first valve is equipped with a gauge that continuously detects the state of the first valve and transmits the detected state of the first valve to the controller, and the controller is configured to adjust the first input signal taking into consideration the transmitted state of the first valve.

20. The aforementioned SPS is A second gate is configured to selectively seal and open the first chamber of the SPS from the third chamber of the SPS, The SPS further comprises a second valve configured to continuously adjust the flow of gas flowing out of the first chamber, The controller is communicated with the second gate and the second valve, and further, The second gate seals the first chamber of the SPS away from the third chamber of the SPS. The second valve is configured to receive a first input signal, and the first input signal is configured to cause the second valve to continuously adjust the flow of gas flowing out of the first chamber of the SPS over a second time period. The system according to claim 8, configured as follows.

21. A method for moving a substrate from a first section of a substrate processing system (SPS) to a second section of the SPS, To open the first gate between the first section and the third section of the SPS, Moving the substrate from the first section to the third section, Closing the first gate to isolate the third compartment from the first compartment, Controlling the second gate to isolate the third compartment from the second compartment, Initiating a gas flow, wherein the gas flow is one of (i) a gas flow flowing into the third compartment, or (ii) a gas flow flowing out of the third compartment, The flow rate of the gas is such that, at each of a plurality of time periods, each of the plurality of RFRs has a target reference flow rate (RFR), where each of the plurality of RFRs is determined based on modeling that minimizes the generation of contaminating particles in the third compartment caused by the flow of the gas. A method comprising opening the second gate and moving the substrate from the third compartment to the second compartment in response to a change in the pressure in the third compartment from an initial pressure to a final pressure.

22. The flow of the gas flows into the third compartment, and the modeling uses a first model that characterizes the resistance force acting on contaminant particles adsorbed on the surface of the third compartment, and the input to the first model is, The viscosity of the aforementioned gas and The method according to claim 21, comprising the velocity of the gas near the surface of the third compartment, wherein the velocity of the gas is determined based on the ratio of the flow of the gas into the third compartment.

23. The modeling uses a second model that characterizes the affinity of the contaminating particles to the surface of the third section, and the modeling is Using the outputs of the first and second models, the instantaneous probability of resuspending the contaminating particles from the surface of the third section is determined. The method according to claim 22, further comprising determining the percentage of contaminating particles remaining adsorbed on the surface of the third compartment after a target duration for which the pressure in the third compartment changes from the initial pressure to the final pressure.

24. The method according to claim 22, wherein the plurality of RFRs are further determined based on (i) a target duration for changing the pressure in the third compartment from the initial pressure to the final pressure, and (ii) a target percentage of contaminating particles remaining adsorbed on the surface of the third compartment.

25. The flow of the gas exits from the third compartment, the pollutant is water particles, and the modeling is, The method according to claim 21, comprising determining the threshold pressure of each of the plurality of threshold pressures related to the condensation of water particles at each of the plurality of time periods.

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