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.