raman-fitting

Raman peak fitting applies Lorentzian, Gaussian, or Voigt models with constrained parameters to graphene G, D, and 2D bands. This Skill handles baseline correction, peak identification, and parameter bounds to improve fit accuracy and ensure physically plausible results.

Data parsing validation ensures wavenumbers and intensities are correctly formatted and structured. This Skill checks input format, performs baseline correction, and estimates initial peak positions before selecting an appropriate peak model.

Yes. This Skill supports Lorentzian, Gaussian, and Voigt peak models with physically informed constraints. You can select and compare models to find the best fit for your specific carbon material spectra.

Fit quality validation uses R² values and residual analysis to check goodness of fit. This Skill performs physical plausibility checks on fitted parameters to confirm results are physically reasonable before accepting the fit.

Systematic debugging includes verifying data parsing, checking baseline correction, reviewing peak identification, and examining fitted parameter bounds. This Skill guides troubleshooting of curve-fitting problems through residual inspection and constraint adjustment.

This Skill is optimized for graphene-related materials covering G, D, and 2D band fitting. The approach applies baseline correction and constrained peak models to Raman spectra of carbon materials broadly.