Systems and Methods for Analyzing Unknown Sample Compositions Using a Prediction Model Based On Optical Emission Spectra

摘要

Aspects of the disclosure relate to techniques for analyzing unknown sample compositions using a prediction model based on optical emission spectra. One method comprises: receiving first emission spectra corresponding to a training sample comprising a plurality of pure elements of known concentrations; determining, based on the first emission spectra, a plurality of spectral regions corresponding to the plurality of pure elements of known concentrations; determining, for each spectral region corresponding to each pure element of a known concentration, features associated with a signature peak of the spectral region; training a prediction model to predict unknown concentrations of a plurality of constituents of an unknown sample based on an emission spectra of the unknown sample; receiving second emission spectra corresponding to the unknown sample comprising a plurality of constituents of unknown concentrations; and generating, based on the application of the trained prediction model, a concentration for each of the constituents of the unknown sample.