Optimizing methods for Raman spectroscopy of carbonaceous material thermometry: Best practices to develop high-fidelity thermal constraints for tectonic studies

Abstract There is a variety of published sample preparation and data acquisition techniques for Raman spectroscopy of carbonaceous material (RSCM) thermometry, which complicates systematic evaluation, assessment, and comparison of RSCM thermometry datasets. In particular, many modern studies are applying large-n RSCM analyses, acquiring high numbers of RSCM temperature estimates, often systematically distributed along transects, to quantify regional thermal structure or spatial temperature gradients associated with geologic structures. Given the significance of RSCM analyses to address numerous geologic questions in a variety of tectonic settings, it becomes imperative to develop a reproducible, standardized, and optimized workflow for RSCM analyses. Here, we introduce and test protocols for RSCM analyses using samples from the Papoose Flat pluton contact aureole, eastern California, western United States, to determine the reproducibility of automated peak-fitting and RSCM temperature estimation programs. Our RSCM results align with previously estimated temperatures derived from calcite-dolomite isotope exchange thermometry, phase equilibria temperature estimates, and quartz c-axis fabric opening-angle thermometry. Temperature estimates derived from two automated peak-fitting programs (i.e., Iterative Fitting of Raman Spectra software [IFORS] and AutoRaman_K2024) are comparable within analytical error. The RSCM temperature estimates were further validated with simple thermal modeling of pluton heat diffusion. Based on these data, we tested sample preparation and data acquisition parameters to optimize large-n workflows. Coupling large datasets at multiple structural levels with supplementary thermal models of varying complexity allows RSCM thermometry to serve as a robust method for tectonic studies.