Physics-Informed Machine Learning Overcomes Particle-Size Nonlinearities That Confound the Raman Spectrometry of Granular Carbonaceous Materials
Raman spectroscopy supports multivariate regression models that can offer a rapid and nondestructive approach to quantifying the composition of granular materials. Soils constitute a class of such materials for which chemical analysis provides vital information for agriculture and environmental stewardship.