Artificial Intelligence in Applied Chemistry: From Molecular Design to Interface Engineering with Lithium Battery Examples

Abstract

The monograph introduces state-of-the-art AI methodologies, including scientific machine learning, physics-constrained models, graph-based and generative approaches, and decision-oriented frameworks, and demonstrates their application to molecular and interface design, data integration, and reaction network analysis. Case studies of lithium battery electrodes, electrolytes, and interphases show practical implementation while highlighting principles applicable to a broad range of applied chemistry problems.