Modular and Automated Workflow for Streamlined Raman Signal Analysis

2025/07/23 by Mykyta Kizilov, Vsevolod Cheburkanov, Kizilov, Mykyta +5
Biochemistry, Genetics and Molecular Biology · #Chemical Physics (physics.chem-ph) #FOS: Electrical engineering #FOS: Physical sciences #Optics (physics.optics) #Signal Processing (eess.SP) #Spectroscopy Techniques in Biomedical and Chemical Research #electronic engineering #information engineering

paper · pdf · doi:10.48550/arxiv.2507.17917

openalex publication_date 2025/07/23 · openalex created_date 2025/10/16 · openalex updated_date 2026/07/28

Abstract

Raman spectroscopy is a powerful tool for material characterization. However, careful preprocessing is required for the identification and handling of noise, baseline drift, and random spikes. This paper presents a comprehensive approach to generating and preprocessing Raman spectra. Additionally, we describe methods for fitting Voigt peaks to the spectrum to determine peak parameters. The effectiveness of these methods is demonstrated using both synthetic and real Raman spectra, with code provided in an open-source GitHub repository.

Citations

• Deep ultraviolet resonant Raman (DUVRR) spectroscopy for spectroscopic evaluation and disinfection of food and agricultural samples
• Tuning Parameter Selection for Penalized Estimation via R²
• A shifted‐excitation Raman difference spectroscopy (SERDS) evaluation strategy for the efficient isolation of Raman spectra from extreme fluorescence interference
• Automated Method for Subtraction of Fluorescence from Biological Raman Spectra

Related

• RAMANMETRIX: a delightful way to analyze Raman spectra
• RamanSPy: An Open-Source Python Package for Integrative Raman Spectroscopy Data Analysis
• One-dimensional Active Contour Models for Raman Spectrum Baseline Correction
• RamanNet: A generalized neural network architecture for Raman Spectrum Analysis
• Bayesian modelling and quantification of Raman spectroscopy