Related papers: Composition-Based Machine Learning for Screening S…
In this work, global search for crystal structures of ternary Mg-Sc-H hydrides (Mg$_x$Sc$_y$H$_z$) under high pressure ($100 \le P \le 200$ GPa) were performed using the evolutionary algorithm and first-principles calculations. Based on…
Research on high-temperature superconductors has primarily focused on hydrogen-rich compounds, however, the need for extreme pressures limits their practical applications. The X2MH6-type structure Mg2IrH6 stands out because it exhibits…
Pressurized hydrogen-rich compounds, which could be viewed as precompressed metallic hydrogen, exhibit high superconductivity, thereby providing a viable route toward the discovery of high-temperature superconductors. Of particular interest…
Multi-principal element alloys open large composition spaces for alloy development. The large compositional space necessitates rapid synthesis and characterization to identify promising materials, as well as predictive strategies for alloy…
Solid state lithium- and sodium-ion batteries utilize solid ionicly conducting compounds as electrolytes. However, the ionic conductivity of such materials tends to be lower than their liquid counterparts, necessitating research efforts…
Hydrogen-based superconductors provide a route to the long-sought goal of room-temperature superconductivity, but the high pressures required to metallize these materials limit their immediate application. For example, carbonaceous sulfur…
Motivated by recent discovery of yttrium-based high-temperature ternary superconducting hydrides (e.g., CaYH$_{12}$, LaYH$_{12}$, and ScYH$_{6}$), we have employed evolutionary algorithm and first-principles calculations to comprehensively…
We exhaustively search quaternary metal hydrides based on the (13-2-1) and (13-3-1) structures that are the two of the putative densest ternary sphere packings in cubic systems [R. Koshoji \textit{et al.}, Phys. Rev. E \textbf{104}, 024101…
Barium hydrides are of interest for their potential in both ionic conductivity and superconductivity. Recently, a superconducting hydride BaH$_{12}$ containing H$_2$ and H${_3}^{-1}$ molecular units was experimentally reported with a…
The discovery of novel superconducting materials is a longstanding challenge in materials science, with a wealth of potential for applications in energy, transportation, and computing. Recent advances in artificial intelligence (AI) have…
Metal hydrides can be tuned to have a diverse range of properties and find applications in hydrogen storage and superconductivity. Finding methods to control the synthesis of hydrides can open up new pathways to unlock novel hydride…
Data driven generative machine learning models have recently emerged as one of the most promising approaches for new materials discovery. While the generator models can generate millions of candidates, it is critical to train fast and…
The search for conventional superconductors with high transition temperatures ($T_c$) has largely focused on intrinsically metallic compounds. In this work, we explore the potential of intrinsically non-metallic compounds to exhibit…
Hydrides have long been considered promising candidates for achieving room-temperature superconductivity; however, the extremely high pressures typically required for high critical temperatures remain a major challenge in experiment. Here,…
Recently, Grockowiak $\textit{et al.}$ reported "hot superconductivity" in ternary or multinary compounds based on lanthanum hydride [A. D. Grockowiak $\textit{et al.}$, Front. Electron. Mater. $\textbf{2}$, 837651 (2022)]. In this paper,…
Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven…
In this study, we evaluate several classifiers and focus on selecting a minimal set of appropriate material features. Our objective is to propose and discuss general strategies for reducing the number of descriptors required for material…
The growing need for structural materials with strength, mechanical stability, and durability in extreme environments is driving the development of high entropy alloys. These are materials with near equiatomic mixing of five or more…
The rapid development of computational materials science powered by machine learning (ML) is gradually leading to solutions to several previously intractable scientific problems. One of the most prominent is machine learning interatomic…
Discovery of high-temperature superconductivity in hydrogen-rich compounds has fuelled the enthusiasm for finding materials with more promising superconducting properties among hydrides. However, the ultrahigh pressure needed to synthesize…