Advanced spectral reconstruction (ASR) for setup-independent universal Raman spectroscopy models

Raman spectroscopy is a versatile tool for the non-invasive determination of system or material properties. The desired information about a property or state must always be extracted from the acquired spectra. To that end, a variety of techniques ranging from data-driven machine learning methods to physics-based modeling of spectra are applied. However, most of these techniques suffer from setup dependency, i.e. even minor changes in the experimental setup can lead to major prediction errors when applying previously generated models. Consequently, laborious retraining, recalibration, or even complete rebuilding of a method are required.