EasyCID: Make component identification easy in Raman spectroscopy

Abstract

Raman spectroscopy can provide valuable fingerprints for molecule identification. The high chemical specificity, minimal or no sample preparation, and the ability to use advanced optical technologies in the visible or near-infrared spectral range have increased its applications. However, identifying components of mixtures is still challenging in Raman spectrometry. The performance of traditional identification methods largely depends on the quality of spectral preprocessing and library searching methods, which limits the ease of Raman application. Thus, based on our previous work, we developed a user-friendly software named EasyCID to directly identify the components of mixtures from raw spectra. EasyCID provides an easy-to-use platform for building deep learning models, identifying components in mixtures, and displaying results intuitively. It is implemented in Python and is available at https://github.com/Ryan21wy/EasyCID.