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Soft computing tools emerged as most reliable alternatives of traditional regression and statistical methods. In recent times, these tools can predict the optimum material compositions, mechanical and tribological properties of composite…

Computational Engineering, Finance, and Science · Computer Science 2025-12-09 Maitreyi Chatterjee , Biplab Chatterjee

We present an efficient method for anealing 3d metallic grains using Gradient Weighted Moving Finite Elements (GWMFE). The initial grain microstructure is generated from Monte-Carlo evolution of a an effective discrete model on the initial…

Computational Physics · Physics 2009-09-25 Andrew Kuprat , J. Tinka Gammel

The changes in the electronic properties of the substitutionally disordered MgC(Ni_{1-x}T_{x})_{3} (T=Fe, Co or Cu) alloys are studied using the atomic sphere formulation of the Korringa-Kohn-Rostoker coherent-potential approximation method…

Materials Science · Physics 2007-05-23 P. Jiji Thomas Joseph , Prabhakar P. Singh

Numerical simulations of a complete laser powder bed fusion (LPBF) additive manufacturing (AM) process are extremely challenging or even impossible to achieve without a radical model reduction of the complex physical phenomena occurring…

Numerical Analysis · Mathematics 2021-12-20 Massimo Carraturo , Alex Viguerie , Alessandro Reali , Ferdinando Auricchio

In conventional FORC (First Order Reversal Curve) analysis of a magnetic system, reversible and low-coercivity irreversible materials are treated as being qualitatively different: the FORC distribution shows low-coercivity materials but…

Materials Science · Physics 2018-11-07 P. B. Visscher

ThMn12-type (Sm,Zr)1(Fe,Co,Ti)12 compounds show great potential for permanent magnets. Magnetically hard anisotropic powders prepared via reduction-diffusion exhibit a significant increase in coercivity from 0.45 T to 1.26 T as the…

Achieving altermagnetism (AM) in two-dimensional materials is crucial for advancing the development of novel spintronic devices. This study introduces an innovative strategy to realize AM in monolayer materials by adsorbing non-magnetic…

Materials Science · Physics 2025-08-28 Han-Bing Li , Zhi-Gang Shao

There is growing interest in engineering unconventional computing devices that leverage the intrinsic dynamics of physical substrates to perform fast and energy-efficient computations. Granular metamaterials are one such substrate that has…

Machine Learning · Computer Science 2024-04-09 Atoosa Parsa , Corey S. O'Hern , Rebecca Kramer-Bottiglio , Josh Bongard

Intercalation of two dimensional materials, particularly transition metal dichalcogenides, is a noninvasive way to modify electronic, optical and structural properties of these materials. However, research of these atomic-scale phenomena…

The use of additive manufacturing (AM) processes for industrial fabrication has grown rapidly over the last ten years. The most well-known AM technologies are fused deposition modelling and stereolithography techniques. One particular…

Significant developments in the field of additive manufacturing (AM) allowed the fabrication of complex microarchitectured components with varying porosity across different scales. However, due to the high complexity of this process, the…

Computational Engineering, Finance, and Science · Computer Science 2020-12-16 N. Korshunova , J. Jomo , G. Lékó , D. Reznik , P. Balázs , S. Kollmannsberger

Novel quantum technologies and devices place unprecedented demands on the performance of experimental components, while their widespread deployment beyond the laboratory necessitates increased robustness and fast, affordable production. We…

Atomic Physics · Physics 2021-08-18 S H Madkhaly , L A Coles , C Morley , C D Colquhoun , T M Fromhold , N Cooper , L Hackermüller

The bottleneck of alloy design for powder-based additive manufacturing (AM) resides in customized powder production - an expensive and time-consuming process hindering the rapid closed-loop design iterations. This study analyzed an…

Applied Physics · Physics 2026-05-14 Zhaoxuan Ge , Sebastian Calderon , S. Mohadeseh Taheri-Mousavi

We have built an integrated computational platform for material properties at extreme conditions, ProME (Professional Materials at Extremes) v1.0, which enables integrated calculations for multicomponent alloys, covering high temperatures…

The nature of low-impurity ferromagnetism remains a challenging problem in the solid-state community. Despite initial experiments dating back to the mid-20th century, a comprehensive theoretical explanation and reliable ab initio…

Magnesium (Mg) has the lowest density of all structural metals and has excellent potential for wide use in structural applications. While pure Mg has inferior mechanical properties; the addition of further elements at various concentrations…

Atomic layer deposition (ALD), a layer-by-layer controlled method to synthesize ultrathin materials, provides various merits over other techniques such as precise thickness control, large area scalability and excellent conformality. Here we…

The potentiality of composition graded AlMgSi wires for optimized combination of electrical conductivity and torsion strength has been investigated. Composition graded wires were obtained by co-drawing commercially pure Al with an AlMgSi…

Materials Science · Physics 2020-08-24 Cui Yang , Nicolas Masquellier , Camille Gandiolle , Xavier Sauvage

We developed new modified embedded-atom method (MEAM) interatomic potentials for the Mg-Al alloy system using a first-principles method based on density functional theory (DFT). The materials parameters, such as the cohesive energy,…

Materials Science · Physics 2013-05-29 B. Jelinek , J. Houze , Sungho Kim , M. F. Horstemeyer , M. I. Baskes , Seong-Gon Kim

Magnetism is a prototypical phenomenon of quantum collective state, and has found ubiquitous applications in semiconductor technologies such as dynamic random access memory (DRAM). In conventional materials, it typically arises from the…

Mesoscale and Nanoscale Physics · Physics 2019-11-12 Yongjin Lee , Shi Che , Jairo Velasco , David Tran , Jacopo Baima , Francesco Mauri , Matteo Calandra , Marc Bockrath , Chun Ning Lau