Research on a Peak-Deconvolution Method for Raman Spectroscopy for Molecular Structure Characterization of Coal Samples with Different Degrees of Metamorphism

Raman spectroscopy is a rapid and non-destructive tool for carbon materials; its high sensitivity to structural order makes it ideal for coal characterization. To address the complexity of coal structure, optimized peak deconvolution is employed to reveal structural evolution and to support low-carbon utilization and methodological standard development. Methodological inconsistencies in previous studies have led to arbitrary choices in peak numbers and functions, compromising data comparability and reliability. Here, the optimal peak number and function are identified by the coefficient of determination (R²) and literature consensus. Gaussian, Lorentzian, Gaussian-Lorentzian, Voigtian and Pearson Ⅶ functions are systematically compared for the first-order region (1000–1800 cm⁻¹). Gaussian–Lorentzian and Voigtian functions achieve R² > 0.9964 for both symmetric and asymmetric peaks; Gaussian outperforms Lorentzian for symmetric peaks, whereas the reverse holds for asymmetric peaks. Optimal strategies vary with metamorphic grade sample: coal-measure graphite requires three peaks (D1, G, D2), while high-rank coals require four peaks (D4, D1, D3, G), both best fitted by Gaussian–Lorentzian or Voigtian functions (R² > 0.9979); high-ash coals (low-rank coal) need four peaks and are best described by Pearson Ⅶ (R² > 0.9983); pyrolysed coals (≤900℃) require ten peaks and are optimally fitted by Voigtian or Gaussian–Lorentzian (R² > 0.9967). This study demonstrates that function choice depends on peak symmetry, while coal complexity dictates the optimal deconvolution strategy, providing a quantitative protocol for Raman peak fitting of coal. The BRIEF REPORT is available for this paper at http://www.ykcs.ac.cn/en/article/doi/10.15898/j.ykcs.202506290189.