Quantum Material Discovery: the New Era of Room-Temperature Superconductivity - I: Navigating Combinatorial Explosion through Annealing, ... Physics, and Hybrid Machine Learning: 1

Quantum Material Discovery Volume I: Physics, Search Spaces, and Computational FoundationsThe next scientific revolution will not be driven by faster computers alone-it will be driven by the discovery of materials that have never existed before.From room-temperature superconductors and quantum materials to high-entropy alloys and AI-guided materials design, modern science faces an extraordinary challenge: how do we navigate a virtually infinite landscape of possible compounds to identify the few capable of transforming energy, computing, transportation, and advanced manufacturing?Quantum Material Discovery - Volume I provides the scientific foundation for answering that question.Beginning with the combinatorial explosion that defines modern materials research, this volume systematically develops the physics, mathematics, and computational principles underlying contemporary quantum materials discovery. Readers are guided from superconductivity and strongly correlated electron systems to quantum annealing, lattice optimization, electron-phonon interactions, high-pressure physics, and high-entropy alloys through a carefully structured progression that emphasizes intuition, rigorous derivation, and practical implementation.Rather than treating condensed matter physics, computational materials science, machine learning, and optimization as isolated disciplines, this book demonstrates how they combine into the computational architecture that is reshaping scientific discovery.Inside this volume, readers will explore: - The combinatorial complexity of modern materials discovery- BCS theory and the evolution of superconductivity- Strong electron correlation and the Hubbard model- Quantum annealing and QUBO formulation- Electron-phonon coupling and lattice interactions- High-pressure physics and metastable phases- High-entropy alloys and configurational complexity- The physical foundations that underpin AI-guided materials discoveryDesigned for graduate students, researchers, computational scientists, physicists, materials engineers, and AI practitioners, this volume establishes the theoretical and computational framework required for the intelligent discovery of next-generation quantum materials.Volume II continues this journey by integrating Bayesian optimization, computational validation, synthesizability analysis, and AI-driven discovery workflows into a complete end-to-end materials discovery pipeline.

Pagina's: 336, Paperback, Independently published