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Computational Progress of High Entropy Materials

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High entropy materials (HEMs) are distinct for their varied compositions involving multiple elements in nearly equal amounts, unlike conventional materials that typically rely on one or two main elements with smaller additives. They cover a wide spectrum of materials, including high entropy alloys (HEAs), ceramics (HECs), and oxides (HEOs), offering customizable properties—a thrilling arena in materials science.

Computational methods play a vital role in the study of HEMs because of their vast composition space and intricate atomic interactions. They are instrumental in predicting properties, minimizing the need for trial-and-error experiments, and providing insights into their stability and transformation processes. Recent advancements in computational techniques, such as machine learning and multi-scale modeling, have transformed the field of HEMs research. These approaches enable the prediction of novel structures, simulation of atomic behavior, and integration of experimental data with computational analysis, leading to a deeper understanding of HEMs.

We invite submission of papers focusing on the computational advancements of high entropy materials. All submitted papers will be subjected to a rigorous peer-review process and adhere to the same editorial standards as regular npj Computational Materials articles. The Guest Editors overseeing the submissions declare no competing interests and will maintain impartiality throughout the peer-review process.

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Algorithm programming and artificial intelligence

Editors

Shijun Zhao, PhD, City University of Hong Kong, Hong Kong, China

Dr. Zhao received his Bachelor’s degree in Physics and his Ph.D. degree in Nuclear Engineering, both from Peking University. After graduation, Dr. Zhao conducted his postdoctoral research at the College of Engineering at Peking University. Prior to joining the City University of Hong Kong, he was a postdoctoral research associate at Oak Ridge National Laboratory.
Dr. Zhao’s current research focuses on chemically disordered materials (high-entropy materials) through a combination of computational materials science and machine learning techniques. Specifically, his group aims to understand surface effects, defect thermodynamics, and defect evolution in chemically disordered materials under deformation or irradiation conditions. For this purpose, different simulation techniques at different scales are concurrently or sequentially employed.

 

Penghui Cao, PhD, University of California, Irvine, USA

Dr. Penghui Cao is an Assistant Professor in the Department of Mechanical and Aerospace Engineering at University of California, Irvine, USA. Prior to this, he was a postdoctoral associate at Massachusetts Institute of Technology after obtaining his doctorate from Boston University in 2014. His research involves developing microscopic modeling algorithms to probe the mechanisms controlling microscale deformation and failure of materials. His research interests lie in the fundamental understanding of rate-dependent plastic deformation and flow in the context of computational materials modeling, with applications to advanced materials technology.


Fritz Körmann, PhD, Max-Planck-Institut für Eisenforschung, Germany

Dr. Fritz Körmann is the leader of the group “Complex Concentrated Alloys” at the Department of Computational Materials Design of Max-Planck-Institut für Eisenforschung. His research focuses on the four topics: 1. Many-body theories, Greens functions, Density functional theory, Theory of magnetism; 2. First-principles calculations of ground-state and finite-temperature properties, phase stabilities, local and extended defects (e.g., stacking fault energies); 3. Magnetism, (Quantum) Monte Carlo methods, Heisenberg models, Magnons, Magnon-phonon interactions, magnetic entropies; 4. Steels, high entropy alloys and materials for magnetic applications.


Francesco Ciucci, PhD, University of Bayreuth, Germany

Prof. Francesco Ciucci is a University Professor at the University of Bayreuth, Germany, holding the Chair of Electrode Design for Electrochemical Energy Systems. Before his current role, he was associated with the Hong Kong University of Science and Technology in various capacities. Francesco is an alumnus of Politecnico di Milano and Ecole Centrale de Paris. He completed his Ph.D. at the California Institute of Technology (Caltech) as a Rotary Ambassadorial Scholar and Bechtel Fellow and did his postdoctoral work at the Heidelberg Graduate School of Mathematical and Computational Methods for the Sciences of the University of Heidelberg, Germany. There, he obtained a Marie Curie Fellowship and a Heidelberg Graduate School Fellowship. His research articles have been featured in major journals, including Nature Catalysis, Nature Chemistry, Joule, Energy & Environmental Science, among others. Francesco’s current research centers around solid-state energy materials, including those used in fuel cells and solid-state batteries, with particular emphasis on modeling such systems and developing new functional materials. Lastly, He is a Fellow of the Royal Society of Chemistry.