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The unique electron deficiency of boron makes it challenging to determine the stable structures, leading to a wide variety of forms. In this work, we introduce a statistical model based on grand canonical ensemble theory that incorporates…

Materials Science · Physics 2025-02-11 Chang-Chun He , Shao-Gang Xu , Yu-Jun Zhao , Hu Xu , Xiao-Bao Yang

The ability to predict the composition- and temperature-dependent stability of refractory complex concentrated alloys (RCCAs) is vital to the design of high-temperature structural alloys. Here, we present a model based on first-principles…

Materials Science · Physics 2022-10-27 Zhaohan Zhang , Mu Li , John Cavin , Katharine Flores , Rohan Mishra

Integrating deep learning with the search for new electron-phonon superconductors represents a burgeoning field of research, where the primary challenge lies in the computational intensity of calculating the electron-phonon spectral…

Exploring the structural, chemical, and physical properties of matter on the nano- and atomic scales has become possible with the recent advances in aberration-corrected electron energy-loss spectroscopy (EELS) in scanning transmission…

Nanoscale surface analysis of 1 micrometer thick high entropy alloys (HEAs) was carried out using nano-IR for hyperspectral imaging and single point spectroscopy in the 700-1700 1/cm spectral range. Nano-IR is based on the detection of…

Current definition of high-entropy alloys (HEAs) is commonly based on the configurational entropy. But this definition depends only on the chemical composition of a HEA and therefore cannot distinguish the information content that is…

Materials Science · Physics 2021-10-11 Houlong Zhuang

Materials informatics (MI), which uses artificial intelligence and data analysis techniques to improve the efficiency of materials development, is attracting increasing interest from industry. One of its main applications is the rapid…

Machine Learning · Computer Science 2023-02-07 Yoshihiro Osakabe , Akinori Asahara

We use high-throughput first-principles sampling to investigate competitive factors that determine the crystal structure of high-entropy alloys (HEAs) and the energetics dependence of the stable phase on the atomic configuration of fully…

Materials Science · Physics 2022-01-03 Hiroshi Mizuseki , Ryoji Sahara , Kenta Hongo

Materials discovery is a computationally intensive process that requires exploring vast chemical spaces to identify promising candidates with desirable properties. In this work, we propose using quantum-enhanced machine learning algorithms…

We propose a new framework for identifying mechanical properties of heterogeneous materials without a closed-form constitutive equation. Given a full-field measurement of the displacement field, for instance as obtained from digital image…

Although electron energy loss near edge structure analysis provides a tool for experimentally probing unoccupied density of states, a detailed comparison with simulations is necessary in order to understand the origin of individual peaks.…

We introduce a computational scheme for calculating the electronic structure of random alloys that includes electronic correlations within the framework of the combined density functional and dynamical mean-field theory. By making use of…

Strongly Correlated Electrons · Physics 2018-12-26 A. Östlin , L. Vitos , L. Chioncel

A series of new Cr$_{5+x}$Mo$_{35-x}$W$_{12}$Re$_{35}$Ru$_{13}$C$_{20}$ high-entropy alloys (HEAs) have been synthesized and characterized by x-ray diffraction, scanning electron microscopy, electrical resistivity, magnetic susceptibility…

Superconductivity · Physics 2023-02-14 Guorui Xiao , Wuzhang Yang , Qinqing Zhu , Shijie Song , Guang-han Cao , Zhi Ren

A monolithic active pixel sensor based direct detector that is optimized for the primary beam energies in scanning electron microscopes is implemented for electron back-scattered diffraction (EBSD) applications. The high detection…

EXAFS analysis of pure elements, binary and ternary equiatomic refractory alloys within the Nb-Zr-Ti-Hf-Ta system is performed at the Nb and Zr K-edges to analyze the evolution of the chemical local environment and the lattice distortion. A…

We develop a machine-learned interatomic potential for AlCrCuFeNi high-entropy alloys (HEA) using a diverse set of structures from density functional theory calculated including magnetic effects. The potential is based on the…

Materials Science · Physics 2026-02-10 Aslak Fellman , Jesper Byggmästar , Fredric Granberg , Flyura Djurabekova , Kai Nordlund

Bootstrap embedding (BE) is a recently developed electronic structure method that has shown great success at treating electron correlation in molecules. Here, we extend BE to treat surfaces and solids where the wave function is represented…

Strongly Correlated Electrons · Physics 2023-01-18 Oinam Romesh Meitei , Troy Van Voorhis

Nickel-based superalloys and near-equiatomic high-entropy alloys containing Molybdenum are known for higher temperature strength and corrosion resistance. Yet, complex solid-solution alloys offer a huge design space to tune for optimal…

Two new refractory amorphous high-entropy alloys (RAHEAs) within the W--Ta--Cr--V and W--Ta--Cr--V--Hf systems were herein synthesized using magnetron-sputtering and tested under high-temperature annealing and displacing irradiation using…

Materials Science · Physics 2023-03-27 Matheus A. Tunes , Hi T. Vo , Jon K. S. Baldwin , Tarik A. Saleh , Saryu J. Fensin , Osman El-Atwani

The fundamental quantity governing the mechanical and thermodynamic properties of a crystalline solid is its electronic charge density. Yet, its direct use for the rapid prediction of materials properties remains challenging due to its high…

Materials Science · Physics 2026-05-11 Kammampati Sai Kumar , Albert Linda , Shubham Kumar Maurya , Somnath Bhowmick
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