Infrared Microspectroscopy with Bayesian Inference for Revealing Spatiotemporal Evolution of Supercritical CO 2 Sorption in Low-Density Polyethylene
Résumé
We demonstrate the application of Bayesian inference for the analysis of concentration profile data obtained with infrared microspectroscopy (IRM) for the adsorption of supercritical CO 2 in a semicrystalline polymer with simultaneous measurement of the adsorption-induced swelling. Low-density polyethylene (LDPE) is chosen as a model system in which Fick's second law is expected to hold without any anomalous diffusion because the adsorption-induced swelling is negligible as confirmed by the present study.
From fitting all of the spatiotemporal data of the adsorption process, the solubility and the Fickian diffusion coefficient of CO 2 in LDPE are obtained. The Bayesian method provides the statistical uncertainty of the best-fit parameters in addition to rigorously quantifying how closely the proposed model with optimal parameters can explain the experimental data. The sorptive-diffusive process is confirmed to proceed with Fickian kinetics as has been frequently assumed though not formally demonstrated.
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