Mixture analysis using reverse searching and non-negative least squares

• RSearch-NNLS has been proposed for analyzing Raman spectra of mixtures.
• Detect major peaks automatically and accurately with CWT for reverse matching
• The RSearch procedure is superior for identifying compounds in the mixture.
• NNLS following the RSearch procedure can refine searching results and estimate ratios.
• Implement in C++ and embed into handheld Raman spectrometers for in situ analysis

The portable even handheld Raman spectrometer can provide adequate spectral resolution for material identification in situ. Raman spectra are information rich but not easy to interpret, especially for the spectra of mixtures. The ability to identify components in the mixture is, therefore, of considerable interest and challenge. In this study, a promising solution for rapid mixture identification was developed with the assistance of a handheld Raman spectrometer, a spectral database and chemometrics. The Raman spectra of raw materials commonly used in the pharmaceutical industry have been acquired under suitable situations and inserted into the spectral database. Classic reverse searching procedure has been modified according to the features of a Raman spectrum based on automatic and accurate peak detection in the wavelet spaces. The match quality can be calculated by counting the negative ratio in the subtractive spectrum between the mixture and database (scaled by the minimal ratio of the reversely matched peaks). On the basis of the modified reverse searching and non-negative least square (RSearch-NNLS), a practical method for mixture analysis has been proposed in this study. The results show that the proposed RSearch procedure is superior for identifying compounds in the mixture than the method based on correlation coefficient. The employment of non-negative least square can further refine searching results and estimate ratios of the compounds in the mixture. The proposed RSearch-NNLS method may be a promising procedure for solving the mixture analysis problem of Raman spectra for some applications.