Quantifying Soil Total Inorganic Carbon Using Shifted-Excitation Raman Difference Spectroscopy (SERDS) and Machine Learning

Accurate quantification of soil inorganic carbon, which is stored predominantly in carbonate minerals, is essential for understanding the soil chemistry, agricultural productivity, and carbon sequestration processes.

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Physics-Informed Machine Learning Overcomes Particle-Size Nonlinearities That Confound the Raman Spectrometry of Granular Carbonaceous Materials

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Announcing DIGITAL Future of Mining and Energy Project Funding