Method of endpoint detection of plasma etching process using multivariate analysis

摘要

Disclosed is a method for determining an endpoint of an etch process using optical emission spectroscopy (OES) data as an input. Optical emission spectroscopy (OES) data are acquired by a spectrometer attached to a plasma etch processing tool. The acquired time-evolving spectral data are first filtered and demeaned, and thereafter transformed into transformed spectral data, or trends, using multivariate analysis such as principal components analysis, in which previously calculated principal component weights are used to accomplish the transform. A functional form incorporating multiple trends may be used to more precisely determine the endpoint of an etch process. A method for calculating principal component weights prior to actual etching, based on OES data collected from previous etch processing, is disclosed, which method facilitates rapid calculation of trends and functional forms involving multiple trends, for efficient and accurate in-line determination of etch process endpoint.

主权项

1. A method for determining etch process endpoint data, comprising:
in a plasma etch processing tool, performing k plasma etch process runs, where k is an integer greater than zero, each of the k plasma etch process runs comprising steps of:
loading a substrate to be processed into the plasma etch processing tool, the plasma etch processing tool comprising a spectrometer having a detector comprising m pixels, each pixel corresponding to a different light wavelength;igniting a plasma in the plasma etch processing tool;collecting n optical emission spectroscopy (OES) data sets sampled at equal time intervals during each of k plasma etch process runs, each of the n optical emission spectroscopy (OES) data sets comprising m pixel intensities corresponding to m pixels of the spectrometer;forming an n×m optical emission spectroscopy (OES) data matrix [X] for each of k plasma etch process runs, each time sample occupying a row of the optical emission spectroscopy (OES) data matrix [X], the columns of the optical emission spectroscopy (OES) data matrix [X] corresponding to pixels of the spectrometer; computing an n×m average optical emission spectroscopy (OES) data matrix [X]avg, wherein each element of the average optical emission spectroscopy (OES) data matrix [X]avg is computed as an average of corresponding elements of optical emission spectroscopy (OES) data matrices [X] for the k etch process runs; filtering noise from the average optical emission spectroscopy (OES) data matrix [X]avg; truncating each optical emission spectroscopy (OES) data matrix [X] to eliminate optical emission spectroscopy (OES) data acquired during plasma startup and for times beyond an etch process endpoint; truncating the average optical emission spectroscopy (OES) data matrix [X]avg to eliminate averaged optical emission spectroscopy (OES) data acquired during plasma startup and for times beyond the etch process endpoint; calculating an n×m mean optical emission spectroscopy (OES) data matrix [Savg], wherein each element of the mean optical emission spectroscopy (OES) data matrix [Savg] is computed as an average value of n elements of the corresponding column of the average optical emission spectroscopy (OES) data matrix [X]avg; subtracting the mean optical emission spectroscopy (OES) data matrix [Savg] from optical emission spectroscopy (OES) data matrices [X], to de-mean the optical emission spectroscopy (OES) data, and performing a principal component analysis [T]=([X][i]−[Savg])[P] on the de-meaned and non-normalized subtraction results, to obtain a transformed optical emission spectroscopy (OES) data vector [T] and principal component weights vector [P]; storing the mean optical emission spectroscopy (OES) data matrix [Savg] for later use in in-situ determination of an etch process endpoint; storing the principal component weights vector [P] for later use in in-situ determination of the etch process endpoint.