Machine-learning-based computation in materials innovation, performance optimization, and sustainability offers exciting opportunities at the mesoscale research frontier. presents research findings and insights about material behavior at the molecular level and its impact on macroscopic properties. The book’s fifteen essays represent author Sidney Yip’s work in atomistic modeling and materials simulation over more than five decades. The phenomena are grouped into five basic types: fluctuations in simple fluids, crystal melting, plasticity and fracture, glassy relaxations, and amorphous rheology, all focused on molecular mechanisms in base materials. The organizing principle of is multiscale modeling and simulation, where conceptual models and simulation techniques are linked across the micro-to-macro length and time scales to control the outcome of specific materials processes. Each essay addresses a specific standalone topic of materials phenomena while also recognizing the larger context of materials science and technology. Individual case studies serve both as standalone essays and companion pieces to each other. Indeed, the global transformation of science and technology is well underway: in his epilogue, Yip discusses the potential of artificial intelligence and machine learning to enhance future materials for societal benefits in the face of global challenges such as climate change, energy sustainability, infrastructure renewal, and nuclear arms control.