TWI804067B - Systems and methods for tuning an impedance matching network in a step-wise fashion - Google Patents

Abstract

Systems and methods for tuning an impedance matching network in a step-wise fashion are described. By tuning the impedance matching network in a step-wise fashion instead of directly to achieve optimum values of a radio frequency (RF) and a combined variable capacitance, processing of a wafer using the tuned optimal values becomes feasible.

Description

System and method for adjusting impedance matching network in steps

The present invention relates to systems and methods for adjusting an impedance matching network in a stepwise manner.

The plasma system is used to control the plasma process. The plasma system includes multiple radio frequency (RF) sources, an impedance matching element, and a plasma reactor. A workpiece is placed within the plasma chamber, and plasma is generated within the plasma chamber to process the workpiece. It is important to treat the work pieces in a similar or uniform manner. In order to treat the workpiece in a similar or uniform manner, it is important to adjust the RF source and impedance matching.

This is the background against which the embodiments described in this disclosure arise.

Embodiments of the present disclosure provide an apparatus, method, and computer program for adjusting an impedance matching network in a stepwise manner. It should be understood that the embodiments of the present invention can be implemented in various ways (eg, processes, devices, systems, hardware, or methods on computer-readable media). Several embodiments are described below.

A plasma tool has a radio frequency (RF) matching network tuning algorithm. The plasma tool has one or two RF generators, and each RF generator is connected to a 50 ohm coaxial RF cable. The RF cables are connected to an impedance matching network connected to the plasma chamber via RF transmission lines. The RF generators are designed to operate with a load impedance of 50+0j ohms or close to 50+0j ohms. One purpose of the impedance matching network is to transform the load impedance of the plasma chamber and the RF transmission line, which is usually not close to 50+0j ohms, to 50+0j ohms or close to 50+0j ohms. The target impedance at or near 50+0j ohms has two parts: the real part, which should be at or near 50 ohms; and the imaginary part, which should be at or near 0 ohms. Therefore, the branch circuit connected to the impedance matching network of one of the two RF generators has two variable elements. The two variable elements include a motor driven variable capacitor and a variable RF frequency output from the one of the RF generators.

The variable capacitance is preset in the recipe and is not changed within the recipe step. Variable capacitors are changed by editing recipes. The variable RF frequency is controlled by a process running inside the RF generator. The process operates according to the voltage reflection coefficient. If the reflection coefficient is high relative to a threshold, the process increases or decreases the RF frequency, and in this way, changes the RF frequency in one direction or the other based on the reflection coefficient. The sensor in the RF generator detects the reflected voltage using a narrowband filter, and detects a portion of the reflected voltage at the fundamental frequency, while at the intermodulation frequency there may be large reflected wave amplitudes that go undetected. The matching network model for the impedance matching network is used when the following inputs (for example: values of RF power, variable capacitance and variable RF frequency, and measured values of RF load impedance at the output of the RF generator, etc. ) are provided as input to the matching network model, predicting the RF voltage, current and phase between the RF voltage and the current at the output of the impedance matching network or the load impedance. The matching network model was extended to predict the RF voltage and current between the output of the impedance matching network and the chuck. In various embodiments, the matching network model comprises a series of modules having the same form, as described in US Patent Application Serial No. 14/245,803.

In some embodiments, the load impedance at the output of the RF generator is propagated forward through the matching network model to calculate the load impedance at the output of the matching network model from the variable capacitance and variable RF frequency, and at the output of the matching network model The load impedance at the output is then propagated back to determine the optimum values for the variable capacitance and variable RF frequency. Once the optimum values are determined, the RF generator and impedance matching network are adjusted to achieve the optimum values of variable capacitance and RF variable frequency. The variable RF frequency can be changed more quickly to achieve the optimum value of the variable RF frequency than to change the variable capacitance to achieve the optimum value of the variable capacitance. For example, variable RF frequency is changed on the order of microseconds compared to changing variable capacitance on the order of seconds. Therefore, it is difficult to directly set the RF generator to operate at the optimum value of the variable RF frequency and the impedance matching network to operate at the optimum value of the variable capacitance. In order to adjust the impedance matching network, instead of adjusting the impedance matching network to achieve the optimum value of the variable capacitance and the RF generator to achieve the optimum value of the variable RF frequency, the impedance matching network is adjusted in steps to achieve Instead of the optimum value of the variable capacitance, a step variable capacitance value is generated, and a local optimum value of the variable RF frequency for the stepped variable capacitance is calculated. For example, the impedance matching network is adjusted to have a variable capacitance value in the direction of the optimum value of the variable capacitance, and a local optimum value of the variable RF frequency determined for the variable capacitance value. In this way, optimum values for variable capacitance and variable RF frequency are achieved, rather than directly achieving optimum values for variable capacitance and variable RF frequency.

Some advantages of the systems and methods described herein include the use of stepwise adjustments of the variable capacitance of the impedance matching network. In this stepwise manner, the local optimum of the variable RF frequency at which the reflection coefficient is the minimum at the input of the matching network model is calculated for the step value of the variable capacitance. The step value is then incremented and another value of the variable RF frequency at which the reflection coefficient at the input of the matching network model is the minimum is calculated for the incremental step value of the variable capacitance. The step value is incremented until the optimum value of the varactor is reached. It is difficult to achieve the optimum value of the variable capacitance and at the same time the optimum value of the variable RF frequency directly from the value being operated by the impedance matching network. This is because it is difficult to control more than one variable capacitor of an impedance matching network at the same speed as the RF generator. By using this stepping method, optimum values of variable capacitance and RF frequency are achieved.

Other implementation aspects will become apparent from the following detailed description when taken in conjunction with the accompanying drawings.

The following embodiments describe systems and methods for adjusting an impedance matching network in a stepwise manner. It is understood that embodiments of the invention may be practiced without some or all of these specific details. In other instances, well known process operations have not been described in detail in order not to unnecessarily obscure embodiments of the invention.

FIG. 1 is a diagram of an embodiment of a plasma system 100 to illustrate the use of a matching network model 102 to generate a load impedance ZL1 . The plasma system 100 includes a radio frequency (RF) generator 104 , an impedance matching network 106 , and a plasma chamber 108 . The plasma system 100 includes a host computer system 110 , a drive assembly 112 , and one or more connection mechanisms 114 .

The plasma chamber 108 includes a top electrode 116 , a chuck 118 , and a wafer W. The upper electrode 116 faces the chuck 118 and is, for example, grounded, coupled to a reference voltage, coupled to zero voltage, coupled to a negative voltage, or the like. Examples of the chuck 118 include an electrostatic chuck (ESC) and a magnetic chuck. The lower electrode of the chuck 118 is made of metal, such as anodized aluminum, aluminum alloys, and the like. In various embodiments, the lower electrode of chuck 118 is covered with a thin layer of ceramic metal. In addition, the upper electrode 116 is made of metal, such as aluminum, aluminum alloy, and the like. In some embodiments, the top electrode 116 is made of silicon. The upper electrode 116 is located on the opposite side of the electrode below the chuck 118 and faces the lower electrode of the chuck 118 . The wafer W is placed on the top surface 120 of the chuck 118 for processing, such as depositing materials on the wafer W, or cleaning the wafer W, or etching layers deposited on the wafer W, or doping the wafer. W, or implanting ions on the wafer W, or generating photolithography patterns on the wafer W, or etching the wafer W, or sputtering the wafer W, or a combination thereof.

In some embodiments, the plasma chamber 108 is formed using additional components such as: an upper electrode extension surrounding the upper electrode 116, a lower electrode extension surrounding the lower electrode of the chuck 118, an upper electrode extension between the upper electrode 116 and the upper electrode. A dielectric ring between the electrode extensions, a dielectric ring between the lower electrode and the lower electrode extension, at the edge of the upper electrode 116 and the chuck 118 to surround a region within the plasma chamber 108 where the plasma is formed confining rings, etc.

The impedance matching network 106 includes more than one circuit element, such as more than one inductor, or more than one capacitor, or more than one resistor, or a combination of the two or more, and these circuit elements are coupled to each other. For example, impedance matching network 106 includes a series circuit including an inductor coupled in series with a capacitor. The impedance matching network 106 further includes a shunt circuit connected to the series circuit. The shunt circuit includes a capacitor connected in series with an inductor. Impedance matching network 106 includes one or more capacitors, and the corresponding capacitances of the one or more capacitors (eg, all variable capacitors, etc.) are variable (eg, changed using drive components, etc.). Impedance matching network 106 includes one or more capacitors with fixed capacitance, such as capacitors that cannot be changed using drive component 112 , or the like. The combined variable capacitance of one or more variable capacitors of the impedance matching network 106 is C1. For example, the respective oppositely placed plates of more than one variable capacitor are adjusted to be in fixed positions to set the variable capacitance C1. To illustrate, the combined capacitance of two or more capacitors connected in parallel with each other is the sum of the capacitances of those capacitors. As another illustration, the combined capacitance of two or more capacitors connected in series with each other is the reciprocal of the sum of the reciprocals of the capacitances of those capacitors. An example of impedance matching network 106 is provided in US Patent Application Serial No. 14/245,803.

The matching network model 102 is derived from a branch of the impedance matching network 106 , for example, represents a branch of the impedance matching network 106 . For example, when an x MHz RF generator is connected to a sub-circuit of the impedance matching network 106, the matching network model 102 represents a computer-generated model of a circuit such as a sub-circuit of the impedance matching network 106, and the like. As another example, the number of circuit elements of the matching network model 102 is not equal to the number of circuit elements of the impedance matching network 106 . In some embodiments, the matching network model 102 has a smaller number of circuit elements compared to the number of circuit elements of the impedance matching network 106 . For illustration, matching network model 102 is a simplified form of the sub-circuits of impedance matching network 106 . For further illustration, the variable capacitances of the plurality of variable capacitors of the sub-circuits of the impedance matching network 106 are combined into a combined variable capacitance represented by one or more variable capacitance elements of the matching network model 102; the impedance matching network The fixed capacitances of the plurality of fixed capacitors of the branch circuits of 106 are combined into a combined fixed capacitance represented by one or more fixed capacitance elements of the matching network model 102; and/or the plurality of fixed inductances of the branch circuits of the impedance matching network 106 The inductance of the impedance matching network 106 is combined into a combined inductance represented by more than one inductive element of the matching network model 102; A fixed resistance represented by one or more resistive elements. To illustrate more, the capacitances of capacitors in series are combined by taking the inverse of each capacitance value to produce a plurality of reciprocal capacitance values, summing the reciprocal capacitance values to produce a reciprocal combined capacitance value, and then by A combined capacitance value is generated by taking the reciprocal of the reciprocal combined capacitance value. As another illustration, the inductances of inductors connected in series are summed to produce a combined inductance, and the resistances of resistors connected in series are combined to produce a combined resistance. All the fixed capacitances of all the fixed capacitors of the portion of the impedance matching network 106 are combined into a combined fixed capacitance of one or more fixed capacitance elements of the matching network model 102 . Other examples of matching network models 102 are provided in US Patent Application Serial No. 14/245,803. Additionally, the manner in which a matching network model is generated from an impedance matching network is described in US Patent Application Serial No. 14/245,803.

In some embodiments, the matching network model 102 is generated from a schematic diagram for an impedance matching network 106 with three branches, one for the RF generator at x MHz, y MHz, and z MHz respectively. The three branches are connected to each other at the output 140 of the impedance matching network 106 . The schematic initially contains several inductors and capacitors in various combinations. For one of the three branches considered independently, the matching network model 102 represents one of the three branches. Circuit elements are added to the matching network model 102 by input means, examples of which are provided below. Examples of added circuit elements include: resistors not previously included in the schematic to account for power losses in the branches of the impedance matching network 106; inductors not previously included in the schematic to represent RF for various connections. the inductance of the band; and the capacitor previously not included in the schematic to represent parasitic capacitance. In addition, some circuit elements are further added to the schematic diagram by input means to represent the transmission line nature of the branches of the impedance matching network 106 due to the physical size of the impedance matching network 106 . For example, the unconvoluted length of the more than one inductor in a branch of the impedance matching network 106 is non-negligible compared to the wavelength of the RF signal passing through the more than one inductor. To explain this result, one inductor in the schematic is divided into two or more inductors. Afterwards, some circuit elements are removed from the schematic by input means to generate a matching network model 102 .

In various embodiments, the branch circuits of the matching network model 102 and the impedance matching network 106 have the same topology, such as connections between circuit elements, number of circuit elements, and the like. For example, if the subcircuit of the impedance matching network 106 includes a capacitor coupled in series with an inductor, the matching network model 102 includes a capacitor coupled in series with an inductor. In this example, the inductors of the branch circuits of the impedance matching network 106 have the same value as the inductors of the matching network model 102, and the capacitors of the branch circuits of the impedance matching network 106 and the capacitors of the matching network model 102 have the same value. same value. As another example, if the subcircuit of the impedance matching network 106 includes a capacitor coupled in parallel with an inductor, the matching network model 102 includes a capacitor coupled in parallel with an inductor. In this example, the inductors of the branch circuits of the impedance matching network 106 have the same value as the inductors of the matching network model 102, and the capacitors of the branch circuits of the impedance matching network 106 and the capacitors of the matching network model 102 have the same value. same value. As another example, matching network model 102 has the same number and same type of circuit elements as circuit elements of impedance matching network 106, and matching network model 102 is between circuit elements as impedance matching network 106 connections compared to connections with the same type. Examples of types of circuit elements include resistors, inductors, and capacitors. Examples of types of connections include series, parallel, and the like.

In addition, the RF generator 104 includes an RF power supply 122 for generating RF signals. The RF generator 104 includes a sensor 124 connected to an output 126 of the RF generator 104, such as a complex impedance sensor, a complex current and voltage sensor, a complex reflection coefficient ( complex reflection coefficient) sensors, complex voltage sensors, complex current sensors, etc. The output 126 is connected to the input 128 of the branch circuit of the impedance matching network 106 via the RF cable 130 . The impedance matching network 106 is connected to the plasma chamber 108 via an RF transmission line 132 comprising an RF rod and an RF outer conductor surrounding the RF rod.

The driving component 112 includes a driver (such as more than one transistor) and a motor, and the motor is connected to a variable capacitor of the impedance matching network 106 through the connection mechanism 114 . Examples of the connection mechanism 114 include more than one rod, or a plurality of rods connected to each other by gears, and the like. The connection mechanism 114 is a variable capacitor connected to the impedance matching network 106 . For example, connection mechanism 114 is a variable capacitor connected to a portion of a branch circuit that is connected to RF generator 104 via input 128 .

It should be noted that where the impedance matching network 106 includes more than one variable capacitor in a branch circuit connected to the RF generator 104, the drive assembly 112 includes a separate motor for controlling the more than one variable capacitor, and Each motor is connected to a corresponding variable capacitor via a corresponding connection mechanism. In this example, the plurality of connection mechanisms are referred to as connection mechanisms 114 .

The RF generator 104 is an x megahertz (MHz) RF generator or a y MHz RF generator or a z MHz RF generator. In some embodiments, an instance of an x MHz RF generator includes a 2 MHz RF generator, an instance of a y MHz RF generator includes a 27 MHz RF generator, and an instance of a z MHz RF generator Includes 60 MHz RF generator. In various embodiments, an instance of an x MHz RF generator includes a 400 kHz RF generator, an instance of a y MHz RF generator includes a 27 MHz RF generator, and an instance of a z MHz RF generator Includes 60 MHz RF generator.

It should be noted that where two RF generators (e.g., x and y MHz RF generators, etc.) are used within the plasma system 100, one of the two RF generators is connected to the input 128 and the The other of the RF generators is connected to another input of the impedance matching network 106 . Similarly, where three RF generators (e.g., x, y, and z MHz RF generators, etc.) are used within the plasma system 100, the first of the RF generators is connected to the input 128 , the second of the RF generators is connected to the second input of the impedance matching network 106 , and the third of the RF generators is connected to the third input of the impedance matching network 106 . Output 140 is connected to input 128 via a branch circuit of impedance matching network 106 . In embodiments where multiple RF generators are used, the output 140 is connected to the second input via a second branch of the impedance matching network 106, and the output 140 is connected via a third branch of the impedance matching network 106 A circuit is connected to the third input.

The host computer system 110 includes a processor 134 and a memory device 137 . Examples of the host computer system 110 include a laptop computer, or a desktop computer, or a tablet, or a smart phone, and the like. As used herein, central processing unit (CPU), controller, application specific integrated circuit (ASIC), or programmable logic device (PLD) are used in place of processor, and these terms are used interchangeably herein use. Examples of memory devices include read-only memory (ROM), random-access memory (RAM), hard disks, volatile memory, non-volatile memory, redundant array of storage disks, flash memory, etc. . Sensor 124 is connected to host computer system 110 via network cable 136 . Examples of network cables used herein are cables used to transfer data serially, or in parallel, or using the USB protocol, etc.

The RF generator 104 operates at a radio frequency RF1. For example, the processor 134 provides the recipe including the radio frequency RF1 and the power value to the RF generator 104 . RF generator 104 receives the recipe via network cable 138 connected to RF generator 104 and host computer system 110 , and a digital signal processor (DSP) of RF generator 104 provides the recipe to RF power supply 122 . RF power supply 122 generates an RF signal having radio frequency RF1 and power specified in the recipe.

Impedance matching network 106 is initialized to have combined variable capacitance C1. For example, the processor 134 sends a signal to a driver of the driving element 112 to generate one or more current signals. The one or more current signals are generated by the driver and sent to the corresponding one or more stators of the corresponding one or more motors of the drive assembly 112 . The respective one or more rotors of the drive assembly 112 are rotated to move the connection mechanism 114 to change the combined variable capacitance of the branch circuits of the impedance matching network 106 to C1. The branch circuit of impedance matching network 106 with combined variable capacitor C1 receives an RF signal with radio frequency RF1 from output 126 via input 128 and RF cable 130, and compares the impedance of the load connected to impedance matching network 106 with the impedance connected to impedance The impedance of the source of the matching network 106 is matched to generate a modified signal, which is an RF signal. Examples of loads include plasma chamber 108 and RF transmission line 132 . Examples of sources include RF cable 130 and RF generator 104 . The modified signal is provided to the chuck 118 from the output 140 of the branch circuit of the impedance matching network 106 via the RF transmission line 132 . When the modified signal is provided to chuck 118 in combination with more than one process gas (e.g., oxygen-containing gas, fluorine-containing gas, etc.), a plasma is generated or maintained in the gap between chuck 118 and upper electrode 116 .

When an RF signal with a radio frequency RF1 is generated and the impedance matching network 106 has a combined variable capacitance C1, the sensor 124 senses the voltage reflection coefficient Γmi1 at the output 126 and transfers the voltage reflection coefficient Γmi1 via the network cable 136 Provided to processor 134. Examples of voltage reflection coefficients include a ratio of the power reflected from the plasma chamber 108 toward the RF generator 104 to the power supplied within the RF signal generated by the RF generator 104 . The processor 134 calculates the impedance Zmi1 from the voltage reflection coefficient Γmi1. For example, the processor 134 calculates the impedance Zmi1 by applying the equation (1) Γmi1=(Zmi1−Zo)/(Zmi1+Zo), and solving to obtain Zmi1, where Zo is the characteristic impedance of the RF transmission line 132 . Impedance Zo is provided to the processor 134 by an input device (eg, mouse, keyboard, stylus, keypad, button, touch screen, etc.) via an input/output interface (eg, serial interface, parallel interface, universal serial bus (USB) interface, etc.) to the processor 134 . In some embodiments, the sensor 124 measures the impedance Zmi1 and provides the impedance Zmi1 to the processor 134 via the network cable 136 .

Impedance Zmi1 is applied to input 142 of matching network model 102 by processor 134 and is propagated forward through matching network model 102 to calculate load impedance ZL1 at output 144 of matching network model 102 . For example, impedance Zmi1 is propagated forward by processor 134 through one or more circuit elements of matching network model 102 to generate load impedance ZL1 . For illustration, the matching network model 102 is initialized to have a radio frequency RF1. When the matching network model 102 includes a series combination of a resistive element, an inductive element, a fixed capacitive element, and a variable capacitive element, the processor 134 calculates the impedance Zmi1, received at the input 142 of the matching network model 102, The directional sum of the complex impedance across the resistive element, the complex impedance across the inductive element, the complex impedance across the variable capacitive element with variable capacitance C1, and the complex impedance across the fixed capacitive element sum) to generate the load impedance ZL1.

In some embodiments, the RF generator 104 operates in a continuous wave mode rather than a pulsed wave mode. For example, the RF generator 104 does not have the pulsed states S1 and S2, wherein all power values of the RF signal in the state S2 are not included in the power values of the RF signal in the state S2. The power value of state S2 is lower than the power value of state S1. As another example, in continuous wave mode, at least one power value in state S1 overlaps at least one power value in state S2 to eliminate the difference between states S1 and S2 to generate a state.

In various embodiments, instead of measuring the voltage reflection coefficient at output 126 , the voltage reflection coefficient is measured at any point on RF cable 130 from output 126 (including output 126 ) to input 128 . For example, sensor 124 is connected to a point between RF power source 122 and impedance matching network 106 to measure the voltage reflection coefficient.

FIG. 2 is a diagram of one embodiment of a matching network model 102 initialized to a radio frequency RF1 and a variable capacitor C1 to generate a voltage reflection coefficient Γi at an input 142 . The processor 134 calculates the radio frequency value RF _optimum and the combined variable capacitance value C _optimum 1 with the voltage reflection coefficient Γi being zero from the load impedance ZL1 and the matching network model 102 . For example, processor 134 backpropagates load impedance ZL1 through matching network model 102 to generate input impedance Zi corresponding to a voltage reflection coefficient Γi at input 142 having a value of zero. Backward propagation is the same as forward propagation, except that the direction of backward propagation is opposite to the direction of forward propagation. In some embodiments, the non-linear least squares optimization procedure is executed by the processor 134 to calculate from the load impedance ZL1 and the matching network model 102 the RF value RF _optimum for which the voltage reflection coefficient Γi is zero and the combination variable Capacitance C _optimum 1. In various embodiments, predetermined equations are applied by the processor 134 to calculate the RF value RF _optimal and the combined variable capacitance value C _optimal 1 with the voltage reflection coefficient Γi equal to zero from the load impedance ZL1 and the matching network model 102 .

In addition, the processor 134 changes the RF value applied to the matching network model 102 from RF _optimum 1@C1 to RF _optimum @C1 and propagates the load impedance ZL1 backward to determine the radio frequency RF _optimum 1@ with the minimum voltage reflection coefficient Γi C1, where n is an integer greater than 1. For example, when the matching network model 102 has a radio frequency RF _optimum 1@C1, the processor 134 propagates the load impedance ZL1 backward through the matching network model 102 having a variable capacitance C1 to determine that the voltage reflection coefficient Γi has a first value . In addition, in this example, when the matching network model 102 has the radio frequency RF _optimum 2@C1, the processor 134 propagates the load impedance ZL1 backward through the matching network model 102 with the variable capacitance C1 to determine the voltage reflection coefficient Γi with second value. The processor 134 determines that the first value is the minimum value of the first and second values, so as to further determine that RF _optimum 1@C1 is a radio frequency value whose voltage reflection coefficient Γi is the minimum value. In some embodiments, a non-linear quadratic optimization procedure is used to find the RF value RF _optimum 1@C1 for which the voltage reflection coefficient Γi has a minimum value.

In various embodiments, the value of the radio frequency at which the voltage reflection coefficient is at a minimum is referred to herein as the favorable RF value.

In some embodiments, RF values are sometimes referred to herein as "parameter values." Additionally, capacitance is sometimes referred to herein as a "measurable factor."

FIG. 3 is a diagram of an embodiment of the plasma system 100 to illustrate the use of the capacitance value C _optimal 1 to generate the step combined variable capacitance value C _step 1 and the use of the value RF _optimum 1@C1 in the matching network model 102. A load impedance ZL2 is developed at the output 144 of . The processor 134 modifies the recipe to include the radio frequency value RF _optimum 1@C1 and provides the radio frequency value RF _optimum 1@C1 to the RF generator 104 . In addition, _the processor 134 determines a step variable capacitance value C _step 1 , which is a step in the direction from the value C1 to the value C _optimum 1 . It should be noted that even if one or more capacitances of the corresponding one or more variable capacitors of the impedance matching network 106 are modified to change from C1 towards C _optimal 1, the one or more variable capacitors relative to the RF signal generated by the RF generator 104 Changes in RF frequency move slowly enough.

Instead of setting the combined variable capacitance of the impedance matching network 106 at a value of C _optimum 1 and instead of setting the RF generator 104 to generate an RF signal with a radio frequency RF _optimum , the processor 134 controls the driver component 112 such that the combination of the impedance matching network 106 The variable capacitor is set at a value C _step 1, and the RF generator 104 is controlled to operate at a radio frequency RF _optimum 1@C1. The time required for the impedance matching network 106 to reach the variable capacitance C _optimum 1 (eg, on the order of seconds) is longer than the time required for the RF generator 104 to generate the RF signal with the RF _optimum . For example, the RF generator 104 reaches the radio frequency RF _optimum from the radio frequency RF1 in microseconds. Therefore, it is difficult to directly reach the value _Coptimum 1 from the value C1 and at the same time reach the value _RFoptimum from the value RF1 such that the voltage reflection coefficient at the output 126 of the RF generator 104 is zero. Therefore, the variable capacitance of the impedance matching network 106 is adjusted in a stepwise manner (such as C _step 1, etc.) in the direction of the previous variable capacitance C _optimum 1 .

For the radio frequency RF _optimum 1@C1 and the variable capacitor C _step 1, the RF generator 104 generates an RF signal with the radio frequency RF _optimum 1@C1, and the RF signal is passed through the impedance matching network 106 to generate and provide to the chuck 118 The modified signal of the electrode. When RF generator 104 generates an RF signal with radio frequency RF _optimum 1@C1 and combined variable capacitance system C _step 1, sensor 124 measures voltage reflection coefficient Γmi2 at output 126, and processor 134, as above The impedance Zmi1 is generated from the voltage reflection coefficient Γmi1 in the same way that the impedance Zmi2 is generated from the voltage reflection coefficient Γmi2. Furthermore, the impedance Zmi2 is propagated forward through the matching network model 102, and in the same way that the load impedance ZL1 is generated at the output 144 from the impedance Zmi1 at the input 142 of the matching network model 102, in the matching network model A load impedance ZL2 is developed at output 144 of 102 .

FIG. 4 is a diagram of one embodiment of a matching network model 102 set to a radio frequency RF _optimum 1@C1 and a combined variable capacitor C _step 1 to generate a voltage reflection coefficient Γi at an input 142 min. For example, the processor 134 applies the radio frequency RF _optimum 1@C1 and the combined varactor C _step 1 to the matching network model 102 . As another example, the processor 134 sets the parameter values of the matching network model 102 to have a radio frequency value RF _optimum 1@C1 and a combined variable capacitance value C _step 1 .

The processor 134 calculates the combined variable capacitance C _optimal 2 with zero voltage reflection coefficient Γi from the load impedance ZL2 and the matching network model 102 in the same manner as the combined variable capacitance C _optimal 1 as described above. The processor 134 changes the radio frequency value applied to the matching network model 102 from RF _optimum 1@C _step 1 to RF _optimum @C _step 1 and propagates the load impedance ZL2 backward to determine the radio frequency RF _optimum with the minimum voltage reflection coefficient Γi 1@C _step 1, where n is an integer greater than 1. For example, when the matching network model 102 has a radio frequency RF _optimum 1@C _step 1, the processor 134 propagates the impedance ZL2 backward through the matching network model 102 with a variable capacitance C _step 1 to determine the voltage reflection coefficient Γi with first value. In addition, in this example, when the matching network model 102 has a radio frequency RF _optimum 2@C _step 1, the processor 134 propagates the impedance ZL2 backward through the matching network model 102 with a variable capacitance C _step 1 to determine the voltage reflection The coefficient Γi has a second value. The processor 134 determines that the first value is the minimum value of the first value and the second value, so as to further determine that RF _optimum 1@C _step 1 is the RF value at which the voltage reflection coefficient Γi is the minimum value.

FIG. 5 is a diagram of one embodiment of the plasma system 100 to illustrate the use of capacitance value C _optimal 2 to generate another step combined variable capacitance value C _step 2 and the use of values RF _optimum 1@C _step 1 to generate load impedance ZL3. The processor 134 modifies the recipe to include the radio frequency value RF _optimum 1@C _step 1 and provides the radio frequency value RF _optimum 1@C _step 1 to the RF generator 104 . In addition, the processor 134 determines a step variable capacitance value C _step 2 , which is an additional step in the direction from the value C _{step 1} to the value C _optimum 2 . For example, among the variable capacitance values C _step 1, C _step 2, and C _optimal 2, the variable capacitance value C _step 2 is greater than the value of C _step 1 and smaller than the value of C _optimal 2, and the values of C _step 2 and C _step 1 is greater than the value C1. As another example, among the variable capacitance values C _step 1, C _step 2, and C _optimal 2, the variable capacitance value C _step 2 is smaller than the value C _step 1 and larger than the value C _optimal 2, and the values C _step 1 and C _step 2 is less than value C1.

Instead of setting the combined variable capacitors of the impedance matching network 106 at a value C _optimum 2 and instead of setting the RF generator 104 to generate an RF signal with a radio frequency RF _optimum , the processor 134 controls the drive element 112 such that the combination of the impedance matching network 106 The variable capacitor is set at the value C _step 2, and the RF generator 104 is controlled to operate at the radio frequency RF _optimum 1@C _step 1 . For the radio frequency RF _optimum 1@C _step 1 and the variable capacitance C _step 2, the RF generator 104 generates an RF signal with the radio frequency RF _optimum 1@C _step 1, and the RF signal is passed through the impedance matching network 106 to generate and provide to the clip The modified signal of the electrode below the disk 118. For the radio frequency RF _optimum 1@C _step 1 and the variable capacitance C _step 2, the sensor 124 measures the voltage reflection coefficient Γmi3 at the output 126, and the processor 134, with the same impedance Zmi1 generated from the voltage reflection coefficient Γmi1 way, the impedance Zmi3 is generated from the voltage reflection coefficient. Furthermore, the impedance Zmi3 is propagated forward through the matching network model 102 in the same way that the load impedance ZL1 is generated at the output 144 from the impedance Zmi1 at the input 142 of the matching network model 102 at the matching network model A load impedance ZL3 develops at output 144 of 102 .

In some embodiments, the radio frequency RF _optimal 1@C _step 1 is equal to the optimal radio frequency value RF _optimal , and the combined variable capacitance of C _step 2 is equal to the value C _optimal 2 . In these embodiments, the operations described below with reference to FIGS. 6 to 9 are not performed.

FIG. 6 is a diagram of one embodiment of a matching network model 102 set to a radio frequency RF _optimum 1@C _step 1 and a combined variable capacitance C _step 2 to generate a voltage reflection coefficient at input 142 The minimum value of Γi. The processor 134 calculates the combined variable capacitance C _optimal 3 with zero voltage reflection coefficient Γi from the load impedance ZL3 and the matching network model 102 in the same way as the combined variable capacitance C _optimal 1 as described above.

In addition, the processor 134 changes the radio frequency value applied to the matching network model 102 from RF _optimum 1@C _step 2 to RF _optimum @C _step 2 and propagates the load impedance ZL3 backwards to determine the radio frequency with the minimum value of the voltage reflection coefficient Γi RF _optimum 1@C _step 2, where n is an integer greater than 1. For example, when the matching network model 102 has a radio frequency RF _optimum 1@C _step 2, the processor 134 propagates the impedance ZL3 backward through the matching network model 102 with the combined variable capacitor C _step 2 to determine the voltage reflection coefficient Γi has the first value. In addition, in this example, when the matching network model 102 has a radio frequency RF _optimum 2@C _step 2, the processor 134 propagates the impedance ZL3 backward through the matching network model 102 with the combined variable capacitance C _step 2 to determine the voltage The reflection coefficient Γi has a second value. The processor 134 determines that the first value is the minimum value of the first value and the second value, so as to further determine that RF _optimum 1@C _step 2 is the RF value at which the voltage reflection coefficient Γi is the minimum value.

In some embodiments, any one of the capacitance values C _optimum 2 and C _optimum 3 is equal to the capacitance value C _optimum 1 with the voltage reflection coefficient Γi being zero.

FIG. 7 is a diagram of one embodiment of the plasma system 100 to illustrate the use of a capacitance value of C _optimum 3, and the use of values of RF _optimum 1@C _step 2 to generate a load impedance ZL4. The processor 134 modifies the recipe to include the radio frequency value RF _optimum 1@C _step 2 and provides the radio frequency value RF _optimum 1@C _step 2 to the RF generator 104 . In addition, the processor 134 determines a step variable capacitance value C _step 3 , which is an additional step in the direction from the value C _{step 2} to the value C _optimum 3 . For example, the value C _step 3 is the value C _optimum 3. For further illustration, among the variable capacitance values C _step 1, C _step 2, and C _optimal 3, the variable capacitance value C _optimal 3 is greater than the value C _step 2, and the value C _step 2 is greater than the value C _step 1, the The value C _step 1 is greater than the capacitor value C1. As another illustration, among the variable capacitance values C _step 1, C _step 2, and C _optimal 3, the variable capacitance value C _optimal 3 is smaller than the value C _step 2, the value C _step 2 is smaller than the value C _step 1, And the value C _step 1 is smaller than the value C1.

The processor 134 controls the driving component 112 such that the combined variable capacitance of the impedance matching network 106 is set at a value C _optimum 3 . Furthermore, instead of setting the RF generator 104 to generate an RF signal with an RF _optimum , the processor 134 controls the RF generator 104 to operate under the RF _optimum 1@C _step 2 .

For the radio frequency RF _optimum 1@C _step 2 and the variable capacitance C _optimum 3, the RF generator 104 generates an RF signal with the radio frequency RF _optimum 1@C _step 2, and the RF signal is passed through the impedance matching network 106 to generate The modified signal of the electrode below the disk 118. For the radio frequency RF _optimum 1@C _step 2 and the variable capacitance C _optimum 3, the sensor 124 measures the voltage reflection coefficient Γmi4 at the output 126, and the processor 134, with the same impedance Zmi1 generated from the voltage reflection coefficient Γmi1 In a way, the impedance Zmi4 is generated from the voltage reflection coefficient Γmi4. Furthermore, the impedance Zmi4 is propagated forward through the matching network model 102 in the same way that the load impedance ZL1 is generated at the output 144 from the impedance Zmi1 at the input 142 of the matching network model 102 at the matching network model A load impedance ZL4 develops at output 144 of 102 .

In some embodiments, the value RF _optimum 1@C _step 2 is equal to the radio frequency value RF _optimum . In these embodiments, the operations described below with reference to FIGS. 8 and 9 are not performed.

In various embodiments, each of the optimal values C _optimal 1 , C _optimal 2 , and C _optimal 3 are constrained when the processor 134 is programmed to calculate an optimal capacitance value within predetermined capacitance value boundaries be obtained afterwards. For example, the processor 134 is programmed to determine the optimum capacitance C _optimum 1 in the manner described above with reference to FIG. 2 , except that the capacitance C _optimum 1 is between the upper predetermined limit and the lower predetermined limit. The predetermined boundaries are the same as the operating boundaries of the one or more variable capacitors of the impedance matching network 106 (FIG. 1). For example, more than one variable capacitor is physically inoperable outside these operating boundaries. As another example, the processor 134 is programmed to determine the optimum capacitance C _optimum 2 in the manner described above with reference to FIG. 4 , except that the capacitance C _optimum 2 is between the upper predetermined limit and the lower predetermined limit. As yet another example, the processor 134 is programmed to determine the optimum capacitance value C _optimum 3 in the manner described above with reference to FIG. 6 , except that the capacitance value C _optimum 3 is between an upper predetermined limit and a lower predetermined limit.

In some embodiments, each of the values RF _optimum 1@C1, RF _optimum 1@C _step 1, RF _optimum 1@C _step 2, and RF _optimum 1@C _optimum are constrained when processor 134 is programmed obtained after calculating an optimum RF value within predetermined limits. For example, the processor 134 is programmed to determine the RF value RF _optimum 1@C1 in the manner described above with reference to FIG. 2 , except that the RF value RF _optimum 1@C1 is between the upper predetermined boundary and the lower predetermined boundary. The predetermined boundaries are the same as the operating boundaries of the RF generator 104 (FIG. 1). For example, RF generator 104 is physically inoperable outside of operational boundaries. As another example, processor 134 is programmed to determine the RF value RF _optimum 1@C _step 1 in the manner described _above with reference to FIG _. between borders. As yet another example, the processor 134 is programmed to determine the optimum RF value RF _optimum 1@C _step 2 in the manner described above with reference to FIG. 6 , except that the RF value RF _optimum 1@C _step 2 is at the upper predetermined boundary and the lower predetermined boundary. As another example, _processor 134 is _programmed to determine the optimum RF value RF _optimum 1@C _optimum in the manner described above with reference to FIG. between borders.

FIG. 8 is a diagram of one embodiment of a matching network model 102 set to a radio frequency RF _optimum 1@C _step 2 and a combined variable capacitance C _optimum 3 to generate a voltage reflection coefficient at input 142 The minimum value of Γi. The processor 134 changes the radio frequency value applied to the matching network model 102 from RF _optimum 1@C _optimum to RF _optimum @C _optimum and propagates the load impedance ZL4 backward to determine the radio frequency RF _optimum 1@ of the minimum voltage reflection coefficient Γi C _optimal , where n is an integer greater than 1. For example, when the matching network model has a radio frequency RF _optimum 1@C _step 2, the processor 134 propagates the load impedance ZL4 backward through the matching network model 102 with a variable capacitance C _optimum 3 to determine the voltage reflection coefficient Γi with first value. Furthermore, in this example, when the matching network model has a radio frequency RF _optimum 2@C _step 2, the processor 134 propagates back the load impedance ZL4 via the matching network model 102 with a variable capacitance C _optimum 3 to determine the voltage reflection The coefficient Γi has a second value. The processor 134 determines that the first value is the minimum value of the first and second values, so as to further determine that RF _optimum 1@C _optimum is the radio frequency value at which the voltage reflection coefficient Γi is the minimum value.

In some embodiments, the value RF _optimal 1@C _optimal is equal to the value RF _optimal .

FIG. 9 is a diagram of one embodiment of a plasma system 100 to illustrate processing a wafer W using a capacitance value of C _optimum 3 and using a value of RF _optimum 1@C _optimum . The processor 134 modifies the recipe to include the radio frequency value RF _optimum 1@C _optimum and provides the radio frequency value RF _optimum 1@C _optimum to the RF generator 104 . In addition, the processor 134 continues to control the driving component 112 such that the combined variable capacitance of the impedance matching network 106 is set at the value C _optimum 3 . Furthermore, instead of setting the RF generator 104 to generate an RF signal with a radio frequency RF _optimum , the processor 134 controls the RF generator 104 to operate at a radio frequency RF _optimum 1@C _optimum .

For the radio frequency RF _optimum 1@C _optimum and the variable capacitance C _optimum 3, the RF generator 104 generates an RF signal with the radio frequency RF _optimum 1@C _optimum , which is passed through the impedance matching network 106 to generate a modified signal, The modified signal is provided to the lower electrode of the chuck 118 for processing the wafer W. In this way, instead of applying the radio frequency RF _optimum directly from the radio frequency RF1 and instead of applying the combined variable capacitance value C _optimal 1 directly from the combined variable capacitance value C1, the step-by-step method proceeds as follows: First, the combined variable capacitance value C _step 1 is Apply with radio frequency RF _optimum 1@C1, then apply combined variable capacitance value C _step 1 and radio frequency RF _optimum 1@C1, then apply combined variable capacitance value C _step 2 and radio frequency RF _optimum 1@C _step 1, then apply Combine the variable capacitance value C _optimum 3 and the radio frequency RF _optimum 1@C _step 2, and finally apply the combined variable capacitance value C _optimum 3 and the radio frequency RF _optimum 1@C _optimum . For example, the application of the combined variable capacitance value C _optimum 3 and the radio frequency RF _optimum 1@C _step 2 precedes the application of the combined variable capacitance value C _optimum 3 and the radio frequency RF _optimum 1@C _optimum . In addition, the combined variable capacitance value C _step 2 and the radio frequency RF _optimum 1@C _step 1 are applied prior to the application of the combined variable capacitance value C _optimum 3 and the radio frequency RF _optimum 1@C _step 2 . In addition, the application of the combined variable capacitance value C _step 1 and the radio frequency RF _optimum 1@C1 is prior to the application of the combined variable capacitance value C _step 2 and the radio frequency RF _optimum 1@C _step 1 .

In some embodiments, instead of applying the radio frequency RF _optimum directly from radio frequency RF1 and instead of applying the combined variable capacitance value C _optimal 1 directly from the combined variable capacitance value C1, a step-by-step approach is performed as follows: First, the combined variable capacitance value C _step 1 is applied with radio frequency RF _optimum 1@C1 (see Figure 3), followed by combined variable capacitance value C _step 2 and radio frequency RF _optimum 1@C _step 1 (see Figure 5), followed by combined variable capacitance value C _Optimum 3 and radio frequency RF _optimum 1@C _step 2 (see Figure 7), and finally apply the combined variable capacitance value C _optimum 3 and radio frequency RF _optimum 1@C _optimal (see Figure 9).

In some embodiments, instead of generating impedances (e.g., impedance Zmi1, etc.) from voltage reflection coefficients (e.g., Γmi1, Γmi2, Γmi3, Γmi4, etc.) Corresponding load voltage reflection coefficient impedances (eg, ΓL1 , ΓL2 , ΓL3 , ΓL4 , etc.) are generated at the output 144 of 102 . There is no need to convert the voltage reflection coefficient to impedance and vice versa.

In various embodiments, instead of the matching network model 102, a combination of the matching network model 102 and the RF transmission model is used to vary the capacitance of the impedance matching network 106 in a stepwise manner as described herein. For example, load impedances ZL1 , ZL2 , ZL3 , and ZL4 are calculated at the output of the RF transmission model rather than at the output 144 of the matching network model 102 . As another example, instead of using the matching network model 102 in Figures 2, 4, 6 and 8, both the matching network model 102 and the RF transmission model are used. The RF transmission model is connected in series with the output 144 of the matching network model 102 and originates from the RF transmission line 132 in a manner similar to the manner in which the matching network model 102 originates from the impedance matching network 106 . For example, the RF transmission model has inductance, capacitance, and/or resistance derived from the inductance, capacitance, and/or resistance of the RF transmission line 132 . As another example, the capacitance of the RF transmission model matches the capacitance of the RF transmission line 132 , the inductance of the RF transmission model matches the inductance of the RF transmission line 132 , and the resistance of the RF transmission model matches the resistance of the RF transmission line 132 .

In some embodiments, instead of the matching network model 102, a combination of the RF cable model, the matching network model 102, and the RF transmission model are used to vary the capacitance of the impedance matching network 106 in a stepwise manner as described herein. For example, load impedances ZL1 , ZL2 , ZL3 , and ZL4 are calculated at the output of the RF transmission model rather than at the output 144 of the matching network model 102 . As another example, instead of the matching network model 102 used in Figures 2, 4, 6 and 8, an RF cable model, matching network model 102, and RF transmission model are used. The RF cable model is connected in series with the input 142 of the matching network model 102 and originates from the RF cable 130 in a manner similar to the manner in which the matching network model 102 originates from the impedance matching network 106 . For example, the RF cable model has inductance, capacitance, and/or resistance derived from the inductance, capacitance, and/or resistance of the RF cable 130 . As another example, the capacitance of the RF cable model matches the capacitance of the RF cable 130 , the inductance of the RF cable model matches the inductance of the RF cable 130 , and the resistance of the RF cable model matches the resistance of the RF cable 130 .

FIG. 10 illustrates one embodiment of a diagram 1000 for stepwise adjustment of impedance matching network 106 and RF generator 104 . Graph 1000 plots the frequency of the RF signal generated by RF generator 104 versus the combined variable capacitance of impedance matching network 106 . Graph 1000 plots representative contours of the voltage reflection coefficient Γ as a function of the combined variable capacitance of impedance matching network 106 and the frequency of the RF signal generated by RF generator 104 . Starting from point B where the magnitude of the voltage reflection coefficient is approximately equal to 0.5, the matching network model 102 indicates an optimal adjustment point system A where the magnitude of Γ is approximately equal to zero and the resistance value at output 126 is 50 ohms (Figure 1). If the combined variable capacitance of impedance matching network 106 and the frequency of the RF signal generated by RF generator 104 are changed at the maximum achievable rate, then the slower variable capacitance of impedance matching network 106 has a chance to move. , the frequency drops very rapidly to point C where the magnitude of the voltage reflection coefficient Γ is worse. In step-wise adjustment, the combined variable capacitance of the impedance matching network 106 is changed from point B to point A, but via points D, E, and F, and the frequency of the RF signal is targeted at points D, E, and Each of the variable capacitances of and F are adjusted. At each of points D, E, and F, the local optimum frequency of the RF signal for the minimum magnitude of the voltage reflection coefficient Γ is determined.

It should be understood that in some of the embodiments described above, the RF signal is supplied to the lower electrode of the chuck 118 and the upper electrode 116 is grounded. In various embodiments, the RF signal is applied to the upper electrode 116 and the lower electrode of the chuck 118 is grounded.

Embodiments described herein can be implemented using various computer system configurations including handheld hardware units, microprocessor systems, microprocessor-based or programmable consumer electronics, mini-computers, mainframe computers wait. The embodiments described herein may also be practiced in distributed computing environments where tasks are performed by remote processing hardware units that are linked through a computer network.

In some embodiments, the controller is part of the system, which may be part of the examples above. The system includes semiconductor processing equipment that includes one or more processing tools, one or more chambers, one or more platforms for processing, and/or specific processing elements (wafer susceptors, gas flow systems, etc.). The system is integrated with electronics used to control the operation of the system before, during, and after processing of semiconductor wafers or substrates. The electronic devices are referred to as "controllers" which control the various elements or subsections of the system. Depending on the processing needs and/or type of the system, the controller is programmed to control any of the processes disclosed herein, including: delivery of process gases, temperature settings (e.g., heating and/or cooling), pressure settings, vacuum settings, power settings , RF generator settings, RF matching circuit settings, frequency settings, flow rate settings, fluid delivery settings, position and operation settings, access to a tool and other transfer tools and/or crystals of the load lock connected or interfaced with the system Circle transfer.

Broadly speaking, in various embodiments, a controller is defined as an electronic device having various integrated circuits, logic, memory, and/or software that receives instructions, issues instructions, controls operations, enables cleaning operations, enables terminal point measurement etc. An integrated circuit includes a chip in the form of firmware storing program instructions, a digital signal processor (DSP), a chip defined as an ASIC, a PLD, one or more microprocessors or microcontrollers that execute program instructions (eg, software). The program instructions are instructions communicated to the controller in the form of various individual settings (or program files) that define the operating parameters for executing the process on the semiconductor wafer. In some embodiments, the operating parameters are part of a recipe defined by a process engineer to generate an output in one or more layers, materials, metals, oxides, silicon, silicon dioxide, surfaces, circuits, and/or wafers more than one processing step during die fabrication.

In some embodiments, the controller is part of or coupled to a computer that is integrated with the system, coupled to the system, otherwise networked to the system, or a combination thereof. For example, the controller is part or all of the "cloud" or fab's host computer system, allowing remote access for wafer processing. The controller allows remote access to the system to monitor the current progress of the manufacturing operation, examine the history of past manufacturing operations, examine trends or performance metrics from a plurality of manufacturing operations, to change the parameters of the current process, to set the current operation processing steps, or start a new process.

In some embodiments, a remote computer (such as a server) provides the process recipe to the system via a computer network, which includes a local area network or the Internet. The remote computer includes a user interface that allows the input or programming of parameters and/or settings that are then communicated from the remote computer to the system. In some examples, the controller receives instructions in the form of settings for processing the wafers. It should be understood that these settings are specific to the type of process to be performed on the wafer and the type of tool to be interfaced or controlled by the controller. Thus, as noted above, the controller is distributed, such as by including more than one distributed controller, networked together and working toward a common purpose, such as the realized process described herein. An example of a decentralized controller for these purposes consists of one or more integrated circuits on the housing, communicating with one or more integrated circuits located remotely (such as at the platform level or as part of a remote computer), which combines the Control the process in the chamber.

Without limitation, in various embodiments, the system includes a plasma etch chamber, a deposition chamber, a spin-rinse chamber, a metal plating chamber, a cleaning chamber, a bevel etch chamber, a physical vapor deposition ( PVD) chambers, chemical vapor deposition (CVD) chamber groups, atomic layer deposition (ALD) chambers, atomic layer etching (ALE) chambers, ion implantation chambers, orbital chambers, and associated or used in semiconductor Any other semiconductor processing chamber in the fabrication and/or production of wafers.

It should also be noted that although the above operations are described with reference to parallel plate plasma chambers (e.g., capacitively coupled plasma chambers, etc.), in some embodiments, the above operations can be applied to other types of plasma chambers, such as : Plasma chambers including inductively coupled plasma (ICP) reactors, transformer coupled plasma (TCP) reactors, conductor tools, and dielectric tools; plasma chambers including electron cyclotron resonance (ECR) reactors, etc. For example: an RF generator of x MHz, an RF generator of y MHz, and an RF generator of z MHz are coupled to an inductor within the ICP plasma chamber.

As noted above, depending on the process operations to be performed by the tool, the controller communicates with: one or more other tool circuits or modules, other tool components, group tools, other tool interfaces, adjacent tools, adjacent tools, located throughout the factory A tool, a host computer, another controller, or a tool for material transfer that carries containers of wafers into and out of a tool location and/or load end within a semiconductor manufacturing facility.

After considering the above embodiments, it should be understood that some embodiments employ various computer-implemented operations including data stored in computer systems. These computer-implementable operations are those that manipulate physical quantities.

Some embodiments also relate to hardware units or devices for performing these operations. This device is purpose built for a special purpose computer. When defined as a special purpose computer, the computer performs other processing, program execution, or commonly used programs that are not part of the special purpose, but is still capable of operating for the special purpose.

In some embodiments, the operations described herein are performed by a computer that is selectively activated or configured by one or more computer programs stored in computer memory or available through a computer network. When data is obtained through a computer network, the data can be processed by other computers on the computer network (such as cloud computing resources).

One or more embodiments described herein can also be fabricated as computer readable code on a non-transitory computer readable medium. The non-transitory computer readable medium is any data storage hardware unit (such as a memory device, etc.) that stores data, which is then read by a computer system. Examples of non-transitory computer readable media include hard disk, network attached storage (NAS), ROM, RAM, compact disc ROM (CD-ROM), compact disc recordable (CD-R), compact disc (CD-RW), magnetic tape, and other optical and non-optical data storage hardware units. In some embodiments, the non-transitory computer-readable medium includes physical computer-readable media distributed over network-coupled computer systems so that the computer-readable code is stored and executed in a distributed fashion.

Although some of the method operations described above are presented in a particular order, it should be understood that in various embodiments, other housekeeping operations are performed between the method operations, or that the method operations are adjusted such that the operations occur At slightly different points in time, or dispersed in a system that allows the method operations to occur over various time intervals, or performed in an order different from that described above.

It should further be noted that in an embodiment, one or more features from any embodiment described above may be combined with one or more features of any other embodiment without departing from the scope of the various embodiments described in this disclosure.

Although the foregoing embodiments have been described in some detail for purposes of clarity of understanding, it will be apparent that certain changes and modifications may be practiced within the purview of the appended claims. Accordingly, embodiments of the invention are to be regarded as illustrative and not restrictive, and such embodiments are not limited to the details provided herein, but may be modified within the scope and equivalents of the appended claims. Revise.

100: Plasma system 102: Matching network model 104: Radio frequency (RF) generator 106: Impedance matching network 108: Plasma chamber 110: host computer system 112: Drive components 114: Connection mechanism 116: Upper electrode 118: Chuck 120: top surface 122: RF power supply 124: sensor 126: output 128: input 130: RF cable 132: RF transmission line 134: Processor 136: Network cable 137: Memory device 138: Network cable 140: output 142: input 144: output 1000: graph

Embodiments are understood by referring to the following description in conjunction with the accompanying drawings.

FIG. 1 is a diagram of an embodiment of a plasma system to illustrate the use of a matching network model to generate a load impedance ZL1.

2 is a diagram of one embodiment of a matching network model initialized to a radio frequency RF1 and a variable capacitor C1 to generate reflection coefficients Γi at the input of the matching network model.

FIG. 3 is a diagram of an embodiment of a plasma system to illustrate the use of capacitance C _optimal 1 to generate a step combined variable capacitance value C _step 1 , and the use of value RF _optimum 1@C1 to generate a load impedance ZL2 .

Fig. 4 is a diagram of an embodiment of a matching network model, which is set to a radio frequency RF _optimum 1@C1 and a combined variable capacitor C _step 1 to generate a reflection coefficient Γi at the input of the matching network model minimum value.

5 is a diagram of one embodiment of a plasma system to illustrate the use of capacitance value C _optimal 2 to generate another step combined variable capacitance value C _step 2, and the use of value RF _optimum 1@C _step 1 to generate load impedance ZL3 .

Figure 6 is a diagram of one embodiment of a matching network model set to a radio frequency RF _optimum 1@C _step 1 and a combined variable capacitor C _step 2 to generate reflections at the input of the matching network model The minimum value of the coefficient Γi.

FIG. 7 is a diagram of one embodiment of a plasma system to illustrate the use of a capacitance value of C _optimum 3, and the use of values of RF _optimum 1@C _step 2 to generate a load impedance ZL4.

Figure 8 is a diagram of one embodiment of a matching network model set to a radio frequency RF _optimum 1@C _step 2 and a combined variable capacitor C _optimum 3 to generate reflections at the input of the matching network model The minimum value of the coefficient Γi.

9 is a diagram of one embodiment of a plasma system to illustrate processing a wafer W using a capacitance value of C _optimum 3 and using a value of RF _optimum 1@C _optimum .

FIG. 10 is an embodiment of a diagram illustrating the step-wise adjustment of the impedance matching network and RF generator of the plasma system.

100: Plasma system

102: Matching network model

104: Radio frequency (RF) generator

106: Impedance matching network

108: Plasma chamber

110: host computer system

112: Drive components

114: Connection mechanism

116: Upper electrode

118: Chuck

120: top surface

122: RF power supply

124: sensor

126: output

128: input

130: RF cable

132: RF transmission line

134: Processor

136: Network cable

137: Memory device

138: Network cable

140: output

142: input

144: output

Claims (24)

A controller for regulating a radio frequency (RF) generator, comprising: a processor configured to: obtain a first input parameter value determined based on a measurement received from an output of the RF generator, wherein the measurements are received while the RF generator is operating at a first parameter value, wherein the first input parameter value includes an impedance value; and one or more computer-generated models are initialized to have the first parameter value, wherein the more than one The computer-generated model includes a matching network model of an impedance matching network; when the more than one computer-generated models have the first parameter value, propagating the first input parameter value through the one or more computer-generated models to output a first an output parameter value; using the first output parameter value and the one or more computer-generated models, determining such that a reflection coefficient at an input of the one or more computer-generated models has a minimum value between values of the reflection coefficient an output parameter value; and controlling the RF generator to operate at the output parameter value; and a memory device coupled to the processor. The controller for regulating a radio frequency (RF) generator as claimed in claim 1, wherein the first output parameter value comprises another impedance value. The controller for regulating a radio frequency (RF) generator as claimed in claim 1, wherein for propagating the first input parameter value through the more than one computer-generated model to output the first output parameter value, the processor is configured to: calculate the A directional sum of a first input parameter value and one or more parameter values associated with one or more circuit elements of the one or more computer-generated models to obtain the first output parameter value. The controller for adjusting a radio frequency (RF) generator as claimed in claim 1, wherein the reflection coefficient at the input of the more than one computer generated model is determined for use of the first output parameter value and the more than one computer generated model For the output parameter value having a minimum value among the reflection coefficient values, the processor is configured to: backpropagate the first output parameter value through the one or more computer-generated models having a first output value to calculating a first value of the reflection coefficient at the input of the one or more computer-generated models; backpropagating the first output parameter value through the one or more computer-generated models having a second output value to calculate a value at the one or more computer-generated models a second value of the reflection coefficient at the input to the above computer-generated model; determining that the first value of the reflection coefficient is lower than the second value of the reflection coefficient; and determining the first value of the reflection coefficient is lower than the second value of the reflection coefficient, the first output value is selected as the output parameter value. The controller for adjusting a radio frequency (RF) generator as claimed in claim 1, wherein the output parameter value is a radio frequency value. The controller for adjusting a radio frequency (RF) generator as in claim 1, wherein the first input parameter value is derived from a voltage reflection coefficient measured by a sensor coupled to the output of the RF generator calculate. The controller for adjusting a radio frequency (RF) generator as in claim 1, wherein the processor is further configured to: obtain a second input parameter value determined based on a measurement received from the output of the RF generator, Wherein the measured value on which the value of the second input parameter is based is determined when the RF generates is received when the device is operating at the output parameter value, wherein the second input parameter value comprises an impedance value; the one or more computer-generated models are initialized to have the output parameter value; when the one or more computer-generated models have the output parameter value When, propagating the second input parameter value through the one or more computer-generated models to output a second output parameter value; using the second output parameter value and the one or more computer-generated models, it is determined such that The reflection coefficient at the input has another output parameter value having a minimum value between values of the reflection coefficient; and controlling the RF generator to operate at the other output parameter value. The controller for regulating a radio frequency (RF) generator as claimed in claim 1, wherein the output of the RF generator is coupled to an input of the impedance matching network via an RF cable. A system for regulating a radio frequency (RF) generator, comprising: the RF generator having an output and configured to generate an RF signal; an impedance matching network coupled to the output of the RF generator, wherein the an impedance matching network configured to modify the RF signal to generate a modified RF signal; a plasma chamber coupled to the impedance matching network, wherein the plasma chamber is configured to receive the modified RF signal; and a processor coupled to the RF generator, wherein the processor is configured to: obtain a first input parameter value determined based on a measurement received from the output of the RF generator, wherein the measurements are received while the RF generator is operating at a first parameter value, wherein the first input parameter value includes an impedance value; initializing one or more computer-generated models to have the first parameter value, wherein the one or more computer-generated models include a matching network model of the impedance matching network; when the one or more computer-generated models have the first parameter value, propagating The first input parameter value is passed through the one or more computer-generated models to output a first output parameter value; using the first output parameter value and the one or more computer-generated models, it is determined such that at one input of the one or more computer-generated models a reflection coefficient having an output parameter value that is a minimum among values of the reflection coefficient; and controlling the RF generator to operate at the output parameter value. The system for adjusting a radio frequency (RF) generator as claimed in claim 9, wherein the first output parameter value comprises another impedance value. The system for adjusting a radio frequency (RF) generator of claim 9, wherein for propagating the first input parameter value through the more than one computer-generated model to output the first output parameter value, the processor is configured to: calculate the first output parameter value A directional sum of an input parameter value and one or more parameter values associated with one or more circuit elements of the one or more computer-generated models to obtain the first output parameter value. The system for adjusting a radio frequency (RF) generator as claimed in claim 9, wherein for using the first output parameter value and the more than one computer generated model to determine the reflection coefficient at the input of the more than one computer generated model has For the output parameter value that is the smallest value among the reflection coefficient values, the processor is configured to: backpropagate the first output parameter value through the one or more computer-generated models having a first output value to calculate a first value of the reflection coefficient at the input of the one or more computer-generated models; backpropagating the first output parameter value through the one or more computer-generated models having a second output value to calculate a second value for the reflection coefficient at the input of the one or more computer-generated models; determining the reflection coefficient the first value of the reflection coefficient is lower than the second value of the reflection coefficient; and upon determining that the first value of the reflection coefficient is lower than the second value of the reflection coefficient, selecting the first output value as the output parameter value. The system for adjusting a radio frequency (RF) generator as claimed in claim 9, wherein the output parameter value is a radio frequency value. The system for adjusting a radio frequency (RF) generator as claimed in claim 9, wherein the first input parameter value is calculated from a voltage reflection coefficient measured by a sensor coupled to the output of the RF generator . The system for adjusting a radio frequency (RF) generator of claim 9, wherein the processor is further configured to: obtain a value received based on the output from the RF generator when the RF generator is operating at the output parameter value a second input parameter value determined by a measurement, wherein the second input parameter value includes an impedance value; initializing the one or more computer-generated models to have the output parameter value; when the one or more computer-generated models have the output parameter value, propagating the second input parameter value through the one or more computer-generated models to output a second output parameter value; using the second output parameter value and the one or more computer-generated models, determining such that in the one or more computer-generated models another output parameter value at which the reflection coefficient at the input has a minimum value among values of the reflection coefficient; and The RF generator is controlled to operate at the other output parameter value. The system for regulating a radio frequency (RF) generator as claimed in claim 9, wherein the output of the RF generator is coupled to an input of the impedance matching network via an RF cable. A method of tuning a radio frequency (RF) generator, comprising: obtaining a value of a first input parameter determined based on a measurement received from an output of the RF generator, wherein the measurement is when the RF generator is at receiving while operating at a first parameter value, wherein the first input parameter value comprises an impedance value; initializing one or more computer-generated models to have the first parameter value, wherein the one or more computer-generated models comprise an impedance matching network a matching network model of the one or more computer-generated models; when the one or more computer-generated models have the first parameter value, propagating the first input parameter value through the one or more computer-generated models to output a first output parameter value; using the first output parameter values and the one or more computer-generated models, determining an output parameter value such that a reflection coefficient at an input of the one or more computer-generated models has a minimum value among values of the reflection coefficient; and controlling the RF generator to operate on the output parameter value. The method of adjusting a radio frequency (RF) generator as claimed in claim 17, wherein the first output parameter value includes another impedance value. The method of adjusting a radio frequency (RF) generator as claimed in claim 17, wherein said propagating the first input parameter value through the more than one computer-generated model to output the first output parameter value comprises calculating the first input parameter value and A directional sum of one or more parameter values of one or more circuit elements associated with the one or more computer-generated models to obtain the first output parameter value. The method of adjusting a radio frequency (RF) generator as claimed in claim 17, wherein said determination is such that the reflection coefficient at the input of the more than one computer-generated model has the minimum value between values of the reflection coefficient The output parameter value comprises: back propagating the first output parameter value through the one or more computer generated models having a first output value to calculate a first value of the reflection coefficient at the input of the one or more computer generated models value; backpropagating the first output parameter value through the more than one computer-generated model with a second output value to calculate a second value of the reflection coefficient at the input of the more than one computer-generated model; determining the the first value of reflection coefficient is lower than the second value of reflection coefficient; and upon determining that the first value of reflection coefficient is lower than the second value of reflection coefficient, selecting the first output value as The output parameter value. The method for adjusting a radio frequency (RF) generator as claimed in claim 17, wherein the output parameter value is a radio frequency value. The method of adjusting a radio frequency (RF) generator as claimed in claim 17, wherein the first input parameter value is calculated from a voltage reflection coefficient measured by a sensor coupled to the output of the RF generator . The method for adjusting a radio frequency (RF) generator as claimed in claim 17, further comprising: obtaining a second input parameter value determined based on a measurement value received from the output of the RF generator, wherein the second input is determined the measured value on which the parameter value is based is received when the RF generator is operating at the output parameter value, wherein the second input parameter value comprises an impedance value; initializing the one or more computer-generated models to have the output parameter value; propagating the second input parameter value through the one or more computer-generated models to output a second output parameter value when the one or more computer-generated models have the output parameter value ; using the second output parameter value and the one or more computer-generated models, determining another output such that the reflection coefficient at the input of the one or more computer-generated models has a minimum value between values of the reflection coefficient a parameter value; and controlling the RF generator to operate at the other output parameter value. The method of adjusting a radio frequency (RF) generator as claimed in claim 17, wherein the output of the RF generator is coupled to an input of the impedance matching network via an RF cable.

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