Experiment-in-Loop Interactive Optimization of Polymer Composites for "5G-and-Beyond"

Abstract

“Fifth generation and beyond” communication technologies have sparked considerable demand for polymer composite materials with low thermal expansion coefficients (CTE) and low dielectric loss under high operation frequency. However, the complexity of process parameters and the lack of knowledge in fabrication procedures hinder this goal. In this study, state-of-the-art experiment-in-loop Bayesian optimization (EiL-BO) is developed to optimize a composite of perfluoroalkoxyalkane matrix with silica fillers. The Gaussian process equipped with an automatic relevance determination kernel that automatically adjusts the scaling parameters of individual dimensions effectively enhances the EiL-BO’s ability to search for candidates in a complex and anisotropic multidimensional space. This address the most critical issue regarding the eight-dimensional parameters, including filler morphology, surface chemistry, and compounding process parameters. The obtained optimal composite shows a low CTE of 24.7 ppm/K and an extinction coefficient of 9.5×10-4, outperforming existing polymeric composite, revealing exceptionally effective and versatile of EiL-BO in accelerates the advanced materials development.