Micro-SORS and machine learning for the non-invasive reference-free study of subsurface pigment degradation | Synapse
March 19, 2026
Micro-SORS and machine learning for the non-invasive reference-free study of subsurface pigment degradation
Key Points
The aim is to develop micro-SORS methods for analyzing pigment degradation non-invasively.
Developed micro-SORS techniques for measuring subsurface layers.
Employed machine learning for data analysis of degradation processes.
Targeted analysis focused on cultural heritage artifacts.
Successfully demonstrated non-invasive measurement of pigment degradation.
Identified significant degradation patterns indicative of preservation needs.
Validated the use of micro-SORS in monitoring cultural heritage.
Abstract
The study presents the development of micro-spatially offset Raman spectroscopy (micro-SORS) methods and data analysis routines for the study of pigment degradation processes in the cultural heritage field.