The use of a novel spectral interconversion scheme, principal component analysis (PCA) based spectral prediction, to probe weak molecular interactions of a polymer film is reported. A PCA model is built based on a joint data matrix by concatenating two related spectral data matrices (such as infrared (IR) and near-infrared (NIR) spectra) along the variable direction, then the obtained loading matrix of the model is split into two parts to predict the desired spectra. For a better PCA-based prediction, it is suggested that the samples whose spectra are to be predicted should be as similar as possible to those used in the model. Based on the PCA model, the thermal-induced changes in the weak interaction of poly(<i>N</i>-isopropylacrylamide) (PNiPA) film is revealed by the interconversion between selected spectral ranges measured between 40 and 220 °C. The thermal-induced weak interaction changes of PNiPA, expressed as either the band shift or intensity changes at a specific region, have been probed properly. Meanwhile, the robustness of the spectral prediction is also compared with that achieved by a partial least squares (PLS2) model in detail, illustrating its advantages in predicting more subtle structural changes such as C–H groups.

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