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Despite rapid progress in the development of quantum algorithms in quantum computing as well as numerical simulation methods in classical computing for atomic and molecular applications, no systematic and comprehensive electronic structure…

To facilitate rational molecular and materials design, this research proposes an integrated computational framework that combines stochastic simulation, ab initio quantum chemistry, and molecular docking. The suggested workflow allows…

Materials Science · Physics 2026-01-08 Md Rakibul Karim Akanda , Michael P. Richard

Synthesis remains a challenge for advancing materials science. A key focus of this challenge is how to enable selective synthesis, particularly as it pertains to metastable materials. This perspective addresses the question: how can…

Materials Science · Physics 2023-06-14 James R Neilson , Matthew J McDermott , Kristin A Persson

Finding Minimum Energy Configurations (MECs) is essential in fields such as physics, chemistry, and materials science, as they represent the most stable states of the systems. In particular, identifying such MECs in multi-component alloys…

Materials Science · Physics 2025-01-27 Md Rajib Khan Musa , Yichen Qian , Jie Peng , David Cereceda

Multivariable parametric models are critical for designing, controlling, and optimizing the performance of engineered systems. The main aim of this paper is to develop a parametric identification strategy that delivers accurate and…

Signal Processing · Electrical Eng. & Systems 2025-07-01 Maarten van der Hulst , Rodrigo González , Koen Classens , Nic Dirkx , Jeroen van de Wijdeven , Tom Oomen

Applications of neural networks to condensed matter physics are becoming popular and beginning to be well accepted. Obtaining and representing the ground and excited state wave functions are examples of such applications. Another…

Disordered Systems and Neural Networks · Physics 2019-12-30 Tomi Ohtsuki , Tomohiro Mano

The reason behind the remarkable properties of High-Entropy Alloys (HEAs) is rooted in the diverse phases and the crystal structures they contain. In the realm of material informatics, employing machine learning (ML) techniques to classify…

Machine Learning · Computer Science 2024-01-02 Debsundar Dey , Suchandan Das , Anik Pal , Santanu Dey , Chandan Kumar Raul , Arghya Chatterjee

The question on the dominant driving mechanism (displacive or order-disorder) at each structural phase transition of KNbO3 is investigated by means of molecular dynamics simulations. To this purpose, we first develop a shell model by…

Materials Science · Physics 2007-05-23 M. Sepliarsky , M. G. Stachiotti , R. L. Migoni , C. O. Rodriguez

The application of state-of-the-art machine learning techniques to statistical physic problems has seen a surge of interest for their ability to discriminate phases of matter by extracting essential features in the many-body wavefunction or…

Strongly Correlated Electrons · Physics 2017-07-04 Peter Broecker , Fakher F. Assaad , Simon Trebst

We consider a mixed hybrid finite element formulation for coupled poromechanics. A stabilization strategy based on a macro-element approach is advanced to eliminate the spurious pressure modes appearing in undrained/incompressible…

Numerical Analysis · Mathematics 2020-07-28 Matteo Frigo , Nicola Castelletto , Massimiliano Ferronato , Joshua A. White

Large-scale electrification is vital to addressing the climate crisis, but several scientific and technological challenges remain to fully electrify both the chemical industry and transportation. In both of these areas, new electrochemical…

We present here a Finite Element Method devoted to the simulation of 3D periodic structures of arbitrary geometry. The numerical method based on ARPACK and PARDISO libraries, is discussed with the aim of extracting the eigenmodes of…

Computational Physics · Physics 2014-02-21 Romain Garnier , André Barka , Olivier Pascal

Stability is one of the key issues in mixed-halide perovskite alloys which are promising in emergent optoelectronics. Previous density-functional-theory (DFT) and machine learning studies indicate that the formation-energy convex hulls of…

Materials Science · Physics 2024-03-01 Fang Pan , Junni Zhai , Jinyu Chen , Lin Yang , Hua Dong , Fang Yuan , Zhuangde Jiang , Wei Ren , Zuo-Guang Ye , Guo-Xu Zhang , Jingrui Li

Parasitic extraction is a powerful tool in the design process of electromechanical devices, specifically as part of workflows that check electromagnetic compatibility. A novel scheme to extract impedances from CAD device models, suitable…

Computational Engineering, Finance, and Science · Computer Science 2021-07-07 Jonathan Stysch , Andreas Klaedtke , Herbert De Gersem

In this paper we consider a three-field formulation of the Biot model which has the displacement, the total pressure, and the pore pressure as unknowns. For parameter-robust stability analysis, we first show a priori estimates of the…

Numerical Analysis · Mathematics 2018-07-02 Jeonghun J. Lee

Obtaining a thermodynamically accurate phase diagram through numerical calculations is a computationally expensive problem that is crucially important to understanding the complex phenomena of solid state physics, such as superconductivity.…

Computational Physics · Physics 2015-05-20 Michał Januszewski , Andrzej Ptok , Dawid Crivelli , Bartłomiej Gardas

Due to the subtle balance of intermolecular interactions that govern structure-property relations, predicting the stability of crystal structures formed from molecular building blocks is a highly non-trivial scientific problem. A…

Chemical Physics · Physics 2022-12-26 Rose K. Cersonsky , Maria Pakhnova , Edgar A. Engel , Michele Ceriotti

The true power of computational research typically can lay in either what it accomplishes or what it enables others to accomplish. In this work, both avenues are simultaneously embraced across several distinct efforts existing at three…

Materials Science · Physics 2024-11-06 Adam M. Krajewski

Many applications of computational fluid dynamics require multiple simulations of a flow under different input conditions. In this paper, a numerical algorithm is developed to efficiently determine a set of such simulations in which the…

Numerical Analysis · Mathematics 2017-05-29 Max Gunzburger , Nan Jiang , Zhu Wang

At present, many laboratories are performing experiments to simulate theoretical models of strongly correlated systems using cold atoms in optical lattices, a program referred to as "Quantum Simulation". It is hoped that these experiments…

Superconductivity · Physics 2016-11-07 Tin-Lun Ho , Qi Zhou