Machine learning models for predicting thermal conductivity of nano‑enhanced phase-change materials

Leveraging machine learning to predict the thermal properties of advanced materials drastically accelerates the discovery process for energy storage solutions. This computational approach reduces reliance on costly physical prototyping, paving the way for more efficient thermal management in next-generation electronics.