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Metal powders with hierarchical nanostructures are always designed and fabricated by dealloying with or without combination of other manufacturing processes. However, they are mainly nanoporous metal powder and its derivations, and their…

Applied Physics · Physics 2019-09-17 Li Chenguang , Zhang Mingwei , Ruan Mianmian , Wang Jun , Liang Jiamiao , Zhang Deliang

We search for new superhard B-N-O compounds with an iterative machine learning (ML) procedure, where ML models are trained using sample crystal structures from evolutionary algorithm. We first use cohesive energy to evaluate the…

Materials Science · Physics 2022-06-22 Wei-Chih Chen , Yogesh K. Vohra , Cheng-Chien Chen

Grain size engineering, particularly reducing grain size into the nanocrystalline regime, offers a promising pathway to further improve the strength-to-weight ratio of Al alloys. Unfortunately, the fabrication of nanocrystalline metals…

Materials Science · Physics 2021-10-07 Tianjiao Lei , Jungho Shin , Daniel S. Gianola , Timothy J. Rupert

Nanoporous metals allow for tailoring composition and surface-to-volume ratio, both aspects critical for applications in catalysis. Here, Ag70Au30 (2 at. %) films with a face-centered cubic structure were deposited at 400{\deg}C, either…

Machine learning (ML) has emerged as a powerful tool for accelerating the computational design and production of materials. In materials science, ML has primarily supported large-scale discovery of novel compounds using first-principles…

A comprehensive literature review on recently rediscovered Co- and/or CoNi-based superalloys, strengthened by the {\gamma}' phase, revealed a relationship between the configurational entropy of the system and the {\gamma}' solvus…

The simulation and analysis of the thermal stability of nanoparticles, a stepping stone towards their application in technological devices, require fast and accurate force fields, in conjunction with effective characterisation methods. In…

Nanoalloys offer a unique opportunity to tailor chemical properties through changes in composition, shape, and size. However, this flexibility introduces complexity that challenges both experimental and conventional theoretical methods. In…

Superconductivity has been the focus of enormous research effort since its discovery more than a century ago. Yet, some features of this unique phenomenon remain poorly understood; prime among these is the connection between…

Atomistic simulations provide insights into structure-property relations on an atomic size and length scale, that are complementary to the macroscopic observables that can be obtained from experiments. Quantitative predictions, however, are…

Materials Science · Physics 2021-04-14 Nataliya Lopanitsyna , Chiheb Ben Mahmoud , Michele Ceriotti

The stability of chemically complex nanoparticles is governed by an immense configurational space arising from heterogeneous local atomic environments across surface and interior regions. Efficiently identifying low-energy configurations…

Nanoindentation is a powerful tool capable of providing fundamental insights of material elastic and plastic response at the nanoscale. Alloys at nanoscale are particularly interesting as the local heterogeneity and deformation mechanism…

Colloidal synthesis of nanocrystals usually includes complex chemical reactions and multi-step crystallization processes. Despite the great success in the past 30 years, it remains challenging to clarify the correlations between synthetic…

Materials Science · Physics 2024-12-17 Kai Gu , Yingping Liang , Jiaming Su , Peihan Sun , Jia Peng , Naihua Miao , Zhimei Sun , Ying Fu , Haizheng Zhong , Jun Zhang

Although the tailored metal active sites and porous architectures of MOFs hold great promise for engineering challenges ranging from gas separations to catalysis, a lack of understanding of how to improve their stability limits their use in…

Materials Science · Physics 2021-06-28 Aditya Nandy , Chenru Duan , Heather J. Kulik

CoPt nanoparticle catalysts are integral to commercial fuel cells. Such systems are prohibitive to fully characterize with electronic structure calculations. Machine-learned potentials offer a scalable solution; however, such potentials are…

Materials Science · Physics 2024-09-12 Cheng Zeng , Sushree Jagriti Sahoo , Andrew J. Medford , Andrew A. Peterson

We employ a descriptor based machine-learning approach to assess the effect of chemical alloying on formation-enthalpy of rare-earth intermetallics. Application of machine-learning approaches in rare-earth intermetallic design have been…

Materials Science · Physics 2022-03-07 Prashant Singh , Tyler Del Rose , Guillermo Vazquez , Raymundo Arroyave , Yaroslav Mudryk

The intricate microstructure serves as the cornerstone for the composition/processing-structure-property (CPSP) connection in multiphase alloys. Traditional alloy design methods often overlook microstructural details, which diminishes the…

Materials Science · Physics 2024-09-05 Xudong Ma , Yuqi Zhang , Chenchong Wang , Ming Wang , Mingxin Huang , Wei Xu

Materials properties depend strongly on chemical composition, i.e., the relative amounts of each chemical element. Changes in composition lead to entirely different chemical arrangements, which vary in complexity from perfectly ordered…

Materials Science · Physics 2025-06-24 Killian Sheriff , Daniel Xiao , Yifan Cao , Lewis R. Owen , Rodrigo Freitas

In the nanometric scale, alloy nanomaterials behave as new materials since they are able to display structures and properties which are different from those of the pure metal nanostructures or bulk alloys. In this work, the compositional…

Amorphous solids exhibit structural short-range order despite lacking long-range crystalline order, with this structural descriptor found to be important for determining mechanical properties. Nanobeam electron diffraction offers a…

Materials Science · Physics 2026-05-21 Junjie Wu , Timothy J. Rupert