Guest Editors
Dr. Bin Chen
Email: steelboy@sjtu.edu.cn
Affiliation: School of Materials Science and Engineering, Shanghai Jiao Tong University, Shanghai, China
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Research Interests: First-principles computational materials science, density functional theory (DFT) applications, metallic alloy property prediction (structural, electronic, thermodynamic, mechanical), phase stability & transformation, defect behavior & engineering, high-performance alloy design (e.g., structural steel, lightweight alloys), AI/ML-augmented materials discovery, multi-scale modeling (atomic to macroscopic), advanced alloys for aerospace, energy & sustainable technologies, rational materials design & optimization
Summary
First-principles calculations, particularly based on density functional theory (DFT), have become indispensable tools in modern materials science for understanding and predicting the fundamental properties of metallic alloys from quantum mechanical principles. These computational approaches enable accurate exploration of atomic-scale phenomena—such as phase stability, defect energetics, electronic structure, and thermodynamic behavior—without relying on empirical parameters. As alloy systems grow increasingly complex (e.g., high-entropy alloys, multi-principal element alloys, and advanced structural steels), first-principles methods provide critical insights that guide rational alloy design, accelerate materials discovery, and reduce reliance on costly trial-and-error experimentation.
The integration of first-principles calculations with complementary techniques—including machine learning, CALPHAD-based thermodynamic modeling, and multiscale simulations—further enhances predictive capabilities across time and length scales. This synergy is vital for developing next-generation alloys tailored for demanding applications in aerospace, energy conversion and storage, nuclear systems, and sustainable infrastructure. Therefore, this Special Issue focuses on the application, advancement, and interdisciplinary integration of first-principles computational methods in the study and design of metallic alloys. The following subtopics are of particular interest, including but not limited to:
• First-principles prediction of phase stability and formation enthalpies in binary and multicomponent alloys
• Electronic structure and its relationship to mechanical, magnetic, and transport properties
• Point defects, dislocations, grain boundaries, and interfacial phenomena in alloys
• High-throughput DFT screening for alloy discovery and optimization
• Machine learning potentials trained on first-principles data for large-scale alloy simulations
• Finite-temperature and entropic effects in alloy thermodynamics via ab initio molecular dynamics or statistical methods
• First-principles studies of high-performance structural alloys (e.g., high-strength steels, Ni-based superalloys, lightweight Al/Mg/Ti alloys)
• Methodological developments for treating chemical disorder, magnetism, and strong correlation in alloys
• Applications of first-principles insights to alloy design for extreme environments (high temperature, radiation, corrosion)
Keywords
First-principles calculations, density functional theory (DFT), metallic alloys, high-entropy alloys, phase stability, defect engineering, alloy design, machine learning for materials
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