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The conversion of $\mathrm{CO_2}$ to value-added compounds is an important part of the effort to store and reuse atmospheric $\mathrm{CO_2}$ emissions. Here we focus on $\mathrm{CO_2}$ hydrogenation over so-called inverse catalysts:…

High-throughput approximations of quantum mechanics calculations and combinatorial experiments have been traditionally used to reduce the search space of possible molecules, drugs and materials. However, the interplay of structural and…

Quantum Physics · Physics 2019-10-29 Alain Tchagang , Julio Valdés

We present a novel phase-field approach for investigating solute segregation in a moving grain boundary. In our model, the correct choice of various parameters can control the solute-grain boundary interaction potential, resulting in…

Materials Science · Physics 2023-08-17 Sandip Guin , Miral Verma , Soumya Bandyopadhyay , Yu-Chieh Lo , Rajdip Mukherjee

Grain boundary engineering via dopant segregation can dramatically change the properties of a material. For metallic systems, most current studies concerning interfacial segregation and subsequent transitions of grain boundary structure are…

Materials Science · Physics 2018-12-26 Yang Hu , Timothy J. Rupert

Alloys composed of several elements in roughly equimolar composition, often referred to as high-entropy alloys, have long been of interest for their thermodynamics and peculiar mechanical properties, and more recently for their potential…

The crystallization of complex, concentrated alloys can result in atomic-level short-range order, composition gradients, and phase separation. These features govern the properties of the resulting alloy. While nucleation and growth in…

Materials Science · Physics 2024-10-23 Saswat Mishra , Alejandro Strachan

The grain boundary (GB) microchemistry and precipitation behaviour in high-strength Al-Zn-Mg-Cu alloys has an important influence on their mechanical and electrochemical properties. Simulation of the GB segregation, precipitation, and…

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

Machine learning (ML) offers considerable promise for the design of new molecules and materials. In real-world applications, the design problem is often domain-specific, and suffers from insufficient data, particularly labeled data, for ML…

Chemical Physics · Physics 2025-02-04 Ming Han , Ge Sun , Juan J. de Pablo

Mn enrichment at dislocations in Fe-Mn alloys due to segregation and spinodal decomposition along the dislocation line is studied via modeling and experimental characterization. To model these phenomena, both finite-deformation microscopic…

Multi-component alloys offer broad tunability for addressing challenges in materials science, but their vast configurational space makes their surface chemistry highly sensitive to operating conditions, for example through adsorption and…

Materials Science · Physics 2026-03-03 Pernilla Ekborg-Tanner , Paul Erhart

An exciting development over the past few decades has been the use of high-throughput computational screening as a means of identifying promising candidate materials for a variety of structural or functional properties. Experimentally, it…

Materials Science · Physics 2020-02-12 Christina A. C. Garcia , Joshua D. Bocarsly , Ram Seshadri

Computational screening has become a powerful complement to experimental efforts in the discovery of high-performance photovoltaic (PV) materials. Most workflows rely on density functional theory (DFT) to estimate electronic and optical…

Materials Science · Physics 2025-07-18 Matthew Walker , Keith T. Butler

Machine learning interatomic potentials (MLIPs) are routinely used to model diverse atomistic phenomena, yet parameterizing them to accurately capture solid-state phase transformations remains difficult. We present error metrics and…

Materials Science · Physics 2026-01-21 Lorenzo Piersante , Anirudh Raju Natarajan

Surface energies of metal-based systems are important for determining the Wulff-constructed shapes of metal nanoparticles and understanding the stability. We have developed a coordination number-based model to predict the total energy of…

Materials Science · Physics 2025-06-19 Shyama Charan Mandal , Frank Abild-Pedersen

High-entropy alloys, which exist in the high-dimensional composition space, provide enormous unique opportunities for realizing unprecedented structural and functional properties. A fundamental challenge, however, lies in how to predict the…

Materials Science · Physics 2021-05-20 Jie Qi , Andrew M. Cheung , S. Joseph Poon

Disordered elemental semiconductors, most notably a-C and a-Si, are ubiquitous in a myriad of different applications. These exploit their unique mechanical and electronic properties. In the past couple of decades, density functional theory…

Materials Science · Physics 2023-03-14 Miguel A. Caro

Grain boundary (GB) segregation in magnesium (Mg) substantially influences its mechanical properties and performance. Atomic-scale modelling, typically using ab-initio or semi-empirical approaches, has mainly focused on GB segregation at…

A multidisciplinary approach is presented to analyse the precipitation process in a model Al-Cu alloy. Although this topic has been extensively studied in the past, most of the investigations are focussed either on transmission electron…

Materials Science · Physics 2018-05-22 A. Rodríguez-Veiga , B. Bellón , I. Papadimitriou , G. Esteban-Manzanares , I. Sabirov , J. Llorca

In the drive towards higher strength alloys, a diverse range of alloying elements is employed to enhance their strength and ductility. Limited solid solubility of these elements in steel leads to segregation during casting which affects the…

Materials Science · Physics 2016-04-25 Bernard Ennis