Artificial intelligence assisted development of dielectric materials

The rapid development of electrical systems in transportation, energy storage, and defense demands dielectric polymers with excellent electrical strength, thermal stability, appropriate dielectric constant, and low loss. However, the mutual constraints among these properties pose a major challenge, and the conventional trial-and-verification paradigm is inefficient for exploring the vast polymer chemical space. Combining artificial intelligence with dielectric material design offers a promising route to accelerate multi-property optimization. This paper introduces an AI-assisted design methodology that integrates domain expertise, curated solid dielectric datasets, target characterization, and advanced machine learning. A polymer database with multi-dimensional structural and performance…