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

Patent metadata

Field	Value
Publication number	US-2016259872-A1
Application number	US-201615061705-A
Country	US
Kind code	A1
Filing date	Mar 4, 2016
Priority date	May 9, 2013
Publication date	Sep 8, 2016
Grant date	—

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.

First claim

1 . A method for tuning an impedance matching network in a step-wise fashion, comprising:
receiving a first measured input parameter value sensed between an output of a radio frequency (RF) generator and an input of an impedance matching network when the RF generator operates at a first parametric value and the impedance matching network has a first variable measurable factor; initializing one or more models to have the first variable measurable factor and the first parametric value, wherein the one or more models include a match network model of the impedance matching network; calculating a first output parameter value using the one or more models from the first measured input parameter value when the one or more models have the first variable measurable factor and the first parametric value; computing, using the first output parameter value and the one or more models, an optimum parametric value and an optimum variable measurable factor for which a reflection coefficient at an input of the one or more models is zero; calculating, using the first output parameter value and the one or more models, a first favorable parametric value for which the reflection coefficient at the input of the one or more models is at a minimum; operating the RF generator at the first favorable parametric value; and setting the impedance matching network to have a first step variable measurable factor, wherein the first step variable measurable factor is closer to the optimum variable measurable factor compared to the first variable measurable factor so that the impedance matching network is tuned in a step-wise fashion.

2 . The method of claim 1 , further comprising:
receiving a second measured input parameter value sensed between the output of the RF generator and the input of the impedance matching network when the RF generator is operated at the first favorable parametric value and the impedance matching network is set to have the first step variable measurable factor; setting the one or more models to have the first step variable measurable factor and the first favorable parametric value; computing a second output parameter value using the one or more models from the second measured input parameter value when the one or more models have the first step variable measurable factor and the first favorable parametric value; computing, using the second output parameter value and the one or more models, a second favorable parametric value for which the reflection coefficient at the input of the one or more models is at a minimum; operating the RF generator at the second favorable parametric value; and setting the impedance matching network to have a second step variable measurable factor.

3 . The method of claim 2 , wherein the second favorable parametric value is the optimum parametric value.

4 . The method of claim 2 , further comprising:
receiving a third measured input parameter value sensed between the output of the RF generator and the input of the impedance matching network when the RF generator is operated at the second favorable parametric value and the impedance matching network is set to have the second step variable measurable factor; setting the one or more models to have the second step variable measurable factor and the second favorable parametric value; computing a third output parameter value using the one or more models from the third measured input parameter value; computing, using the third output parameter value and the one or more models, a third favorable parametric value for which the reflection coefficient at the input of the one or more models is at a minimum; and operating the RF generator at the third favorable parametric value.

5 . The method of claim 4 , wherein the third favorable parametric value is the optimum parametric value.

6 . The method of claim 4 , wherein the third favorable parametric value is different from the optimum parametric value.

7 . The method of claim 1 , wherein the first measured parameter value is sensed by a sensor that is coupled to the output of the RF generator, wherein the first measured parameter value is an impedance or a reflection coefficient.

8 . The method of claim 1 , wherein the first output parameter value is calculated by forward propagating the first measured input parameter value via circuit elements of the one or more models.

9 . The method of claim 1 , wherein the optimum parametric value and the optimum variable measurable factor are computed by back propagating the first output parameter value via circuit elements of the one or more models to achieve the zero reflection coefficient.

10 . A system for tuning an impedance matching network in a step-wise fashion, comprising:
a processor configured to receive a first measured input parameter value sensed between an output of a radio frequency (RF) generator and an input of an impedance matching network when the RF generator operates at a first parametric value and the impedance matching network has a first variable measurable factor, wherein the processor is configured to initialize one or more models to have the first variable measurable factor and the first parametric value, wherein the one or more models include a model of the impedance matching network; and a memory device connected to the processor, wherein the memory device is configured to store the one or more models, wherein the processor is configured to calculate a first output parameter value using the one or more models from the first measured input parameter value when the one or more models have the first variable measurable factor and the first parametric value, wherein the processor is configured to compute, using the first output parameter value and the one or more models, an optimum parametric value and an optimum variable measurable factor for which a reflection coefficient at an input of the one or more models is zero; wherein the processor is configured to calculate, using the first output parameter value and the one or more models, a first favorable parametric value for which the reflection coefficient at the input of the one or more models is at a minimum, wherein the processor is configured to operate the RF generator at the first favorable parametric value, wherein the processor is configured to set the impedance matching network to have a first step variable measurable factor, wherein the first step variable measurable factor is closer to the optimum variable measurable factor compared to the first variable measurable factor so that the impedance matching network is tuned in a step-wise fashion.

11 . The system of claim 10 ,
wherein the processor is configured to receive a second measured input parameter value sensed between the output of the RF generator and the input of the impedance matching network when the RF generator is operated at the first favorable parametric value and the impedance matching network is set to have the first step variable measurable factor, wherein the processor is configured to set the one or more models to have the first step variable measurable factor and the first favorable parametric value, wherein the processor is configured to compute a second output parameter value using the one or more models from the second measured input parameter value when the one or more models have the first step variable measurable factor and the first favorable parametric value, wherein the processor is configured to compute, using the second output parameter value and the one or more models, a second favorable parametric value for which the reflection coefficient at the input of the one or more models is at a minimum, wherein the processor is configured to operate the RF genera

Assignees

• Lam Res Corp

Inventors

• Howald Arthur M
• Valcore Jr John C
• Fong Andrew
• Hopkins David

Classifications

• G06F30/367

  Design verification, e.g. using simulation, simulation program with integrated circuit emphasis [SPICE], direct methods or relaxation methods · CPC title

• G06F17/11 Primary

  for solving equations {, e.g. nonlinear equations, general mathematical optimization problems (optimization specially adapted for a specific administrative, business or logistic context G06Q10/04)} · CPC title

• G06F30/36 Primary

  Circuit design at the analogue level · CPC title

• G06F17/5009 Primary

  Physics · mapped topic

• G06F2217/16

  Physics · mapped topic