Search Results (2)

The glass transition temperature (T_g) was a pivotal parameter governing the thermal and mechanical properties of bismaleimide-based polyimide (BMI) resins. However, limited experimental data for BMI systems posed significant challenges for predictive modeling. To address this gap, this study introduced a hybrid modeling framework leveraging transfer learning. Specifically, a multilayer perceptron (MLP) deep neural network was pre-trained on a large-scale polymer database and subsequently fine-tuned on a small-sample BMI dataset. Complementing this approach, six interpretable machine learning algorithms—random forest, ridge regression, k-nearest neighbors, Bayesian regression, support vector regression, and extreme gradient boosting—were employed to construct transparent predictive models. SHapley Additive exPlanations (SHAP) analysis was further utilized to quantify the relative contributions of molecular descriptors to T_g. Results demonstrated that the transfer learning strategy achieved superior predictive accuracy in data-scarce scenarios compared to direct training on the BMI dataset. SHAP analysis identified charge distribution inhomogeneity, molecular topology, and molecular surface area properties as the major influences on T_g. This integrated framework not only improved the prediction performance but also provided feasible insights into molecular structure design, laying a solid foundation for the rational engineering of high-performance BMI resins. Full article

Phase-separated polymer blend composite films exhibiting high thermal diffusivity were prepared by blending a soluble polyimide (BPADA-MPD) and a bismaleimide (BMI) with needle-shaped zinc oxide (n-ZnO) particles followed by high-temperature curing at 250 °C. Images recorded with a field-emission scanning electron microscope (FE-SEM) equipped with wavelength-dispersive spectroscopy (WDS) demonstrated that the spontaneously separated phases in the composite films were aligned along the out-of-plane direction, and the n-ZnO particles were selectively incorporated into the BMI phase. The out-of-plane thermal diffusivity of the composite films was significantly higher than those of the previously reported composite films at lower filler contents. Based on wide-angle X-ray diffraction (WAXD) patterns and image analysis, the enhanced thermal diffusivity was attributed to the confinement of the anisotropically shaped particles and their nearly isotropic orientation in one phase of the composite films. Full article