Application of Singular Value Decomposition for Identification of Liquid Precursor Chemicals Using Energy-Dispersive X-Ray Scattering

A new method based on singular value decomposition (SVD) was developed to identify liquid precursor chemicals in this paper. Feature scattering spectra of several kinds of pure liquid precursor chemicals were described through energy-dispersive x-ray scattering (EDXRS). These spectra, each of which was unique to particular liquid, were organized as matrices for SVD after truncation and smoothing. It was demonstrated that the two largest singular values and their corresponding left and right singular vectors of each matrix could reconstruct the matrix in the permissible error and contained enough information of the matrix. We extracted the two largest singular values of each matrix as the characteristic of the relative spectrum, and successfully identified several pure liquid precursor chemical samples. It can be hopefully expected that this method is effective for inspection of high concentration and multitudinous liquid precursor chemicals.