Systems for automatically characterizing a plasma

Abstract

A system includes a probe arranged in a plasma processing chamber of the plasma processing system. A capacitor has one end connected to the probe. An RF source is configured to selectively supply an RF signal including RF bursts to another end of the capacitor. A plasma characterizing computing device is configured to collect a set of process data from the probe by measuring current supplied to the capacitor and voltage at the capacitor; identify a relevancy range for the set of process data, wherein the relevancy range includes process data collected after the capacitor begins discharging and before the capacitor is fully discharged; determine a set of seed values based on the process data in the relevancy range; and employ the relevancy range and the set of seed values as initial values for curve fitting corresponding to the one of the RF bursts to reduce a number of curve-fitting iterations.

What is claimed is: 
     
         1 . A system for automatically characterizing plasma during substrate processing in a plasma processing system, comprising:
 a probe arranged in a plasma processing chamber of the plasma processing system;   a capacitor having one end connected to the probe;   an RF source configured to selectively supply an RF signal including RF bursts to another end of the capacitor;   a plasma characterizing computing device configured to:
 collect a set of process data from the probe during substrate processing by measuring current supplied to the another end of the capacitor and voltage at the one end of the capacitor; 
 identify a relevancy range for the set of process data, 
 wherein the relevancy range includes a subset of the set of process data collected after the capacitor begins discharging after one of the RF bursts and before the capacitor is fully discharged after the one of the RF bursts; 
 determine a set of seed values based on the process data in the relevancy range; and 
 employ the relevancy range and the set of seed values as initial values for curve fitting corresponding to the one of the RF bursts to reduce a number of curve-fitting iterations. 
   
     
     
         2 . The system of  claim 1 , wherein the plasma characterizing computing device is configured to identify the relevancy range by:
 calculating a peak of a first derivative of the set of process data; and   determining a percentage decay point.   
     
     
         3 . The system of  claim 2 , wherein:
 the percentage decay point represents a level below an original data value corresponding to an end of one of the RF bursts, and   wherein the relevancy range is between the original data value and the percentage decay point.   
     
     
         4 . The system of  claim 3 , wherein the plasma characterizing computing device is configured to identify the relevancy range by identifying an inflection point, wherein:
 the relevancy range is represented by a range between the original data value and the inflection point,   the inflection point corresponds to a first derivative of the current values between the percentage decay point and a second decay point,   the second decay point is between the original data value and the percentage decay point.   
     
     
         5 . The system of  claim 4 , wherein the set of seed values includes a slope, an electron temperature, an ion saturation value, and a floating voltage potential. 
     
     
         6 . The system of  claim 5 , wherein the plasma characterizing computing device is configured to determine the set of seed values based on an ion saturation interval, wherein the ion saturation interval corresponds to an interval from the original data value to the second decay point. 
     
     
         7 . The system of  claim 6 , wherein the slope is determined by performing a linear regression of the ion saturation interval. 
     
     
         8 . The system of  claim 7 , wherein the ion saturation value is determined by averaging data values within the ion saturation interval. 
     
     
         9 . The system of  claim 8 , wherein the electron temperature is determined by taking a first derivative of data collected at the inflection point. 
     
     
         10 . The system of  claim 9 , wherein the plasma characterizing computing device determines the floating voltage potential by averaging voltage data collected from an initial floating voltage potential point to a data point before a second RF charge. 
     
     
         11 . A non-transitory, tangible computer-readable medium comprising executable instructions for:
 selectively supplying an RF signal including RF bursts to a first terminal of a capacitor connected to a probe in a plasma processing chamber of a plasma processing system;   collecting a set of process data from the probe during substrate processing by measuring current supplied to the first terminal of the capacitor and voltage at a second terminal of the capacitor;   identifying a relevancy range for the set of process data,   wherein the relevancy range includes a subset of the set of process data collected after the capacitor begins discharging after one of the RF bursts and before the capacitor is fully discharged after the one of the RF bursts;   determining a set of seed values based on the process data in the relevancy range; and   employing the relevancy range and the set of seed values as initial values for curve fitting corresponding to the one of the RF bursts to reduce a number of curve-fitting iterations.   
     
     
         12 . The non-transitory, tangible computer-readable medium of  claim 11 , further comprising executable instructions for identifying the relevancy range by:
 calculating a peak of a first derivative of the set of process data; and   determining a percentage decay point.   
     
     
         13 . The non-transitory, tangible computer-readable medium of  claim 12 , wherein:
 the percentage decay point represents a level below an original data value corresponding to an end of one of the RF bursts, and   wherein the relevancy range is between the original data value and the percentage decay point.   
     
     
         14 . The non-transitory, tangible computer-readable medium of  claim 13 , further comprising executable instructions for identifying the relevancy range by identifying an inflection point, wherein:
 the relevancy range is represented by a range between the original data value and the inflection point,   the inflection point corresponds to a first derivative of the current values between the percentage decay point and a second decay point,   the second decay point is between the original data value and the percentage decay point.   
     
     
         15 . The non-transitory, tangible computer-readable medium of  claim 14 , wherein the set of seed values includes a slope, an electron temperature, an ion saturation value, and a floating voltage potential. 
     
     
         16 . The non-transitory, tangible computer-readable medium of  claim 15 , further comprising executable instructions for determining the set of seed values based on an ion saturation interval, wherein the ion saturation interval corresponds to an interval from the original data value to the second decay point. 
     
     
         17 . The non-transitory, tangible computer-readable medium of  claim 16 , further comprising executable instructions for determining the slope by performing a linear regression of the ion saturation interval. 
     
     
         18 . The non-transitory, tangible computer-readable medium of  claim 17 , further comprising executable instructions for determining the ion saturation value by averaging data values within the ion saturation interval. 
     
     
         19 . The non-transitory, tangible computer-readable medium of  claim 18 , further comprising executable instructions for determining the electron temperature by taking a first derivative of data collected at the inflection point. 
     
     
         20 . The non-transitory, tangible computer-readable medium of  claim 19 , further comprising executable instructions for determining the floating voltage potential by averaging voltage data collected from an initial floating voltage potential point to a data point before a second RF charge.