This workflow demonstrates improved intensity curve modeling in solid-state NMR, enhancing reproducibility and efficiency.
Quantitative analysis of solid-state NMR data, based on magic-angle spinning with cross-polarization experiments (CP-MAS), often requires extensive signal processing, from the transformation of raw time-domain data (FIDs) to the extraction of quantitative data and the modelling of signal intensity kinetics. Many current workflows rely on semi-manual peak fitting and heterogeneous tools across laboratories for intensity curve modelling, limiting reproducibility and throughput. In this work, we propose a fully reproducible and open workflow combining two key methodological approaches: (1) an adaptive bucketing approach, extraction of relevant variables for analysis (ERVA), implemented in NMRProcFlow application, to automatically segment ¹³C spectra into chemically relevant spectral regions; and (2) an online modelling platform that allows users to fit intensity curves over contact time with multiple models, guided by objective indicators including fit quality scores and parameter sensitivity metrics. This integrated approach provides a fast, user-friendly and transparent path from FIDs to kinetic model parameters, opening new perspectives for reproducible quantitative solid-state NMR.
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Jacob et al. (2026) studied this question.
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