Ranc Analytics — InsightsTechnical notes on SERS, Raman method development, and leakage-free chemometric validation.https://ranc-analytics.com/enFrom R&D to release testing: chemometric models that survive an audithttps://ranc-analytics.com/insights/chemometric-models-regulated-qc/https://ranc-analytics.com/insights/chemometric-models-regulated-qc/A chemometric model that works in the lab is not yet a QC method. What it takes to move Raman and SERS models into regulated quality control, from validation to data integrity to lifecycle.Fri, 10 Jul 2026 00:00:00 GMTchemometricsquality controlPATvalidationregulatedWhy your spectral classifier is probably overfitting, and how to prove it isn'thttps://ranc-analytics.com/insights/data-leakage-spectral-model-validation/https://ranc-analytics.com/insights/data-leakage-spectral-model-validation/Most reported accuracies for Raman and SERS classification are optimistic. The cause is usually validation design, not the model. Here is how leakage creeps in and how to shut it out.Fri, 10 Jul 2026 00:00:00 GMTchemometricsmachine learningvalidationRamanSERSIn SERS, the substrate and the matrix decide the result, not the spectrometerhttps://ranc-analytics.com/insights/sers-substrate-matrix-vs-instrument/https://ranc-analytics.com/insights/sers-substrate-matrix-vs-instrument/Teams often invest in a better Raman instrument when their SERS problem is really a nanostructure and matrix problem. Where enhancement actually comes from, and what that means for method design.Fri, 10 Jul 2026 00:00:00 GMTSERSnanomaterialsmethod developmentRaman