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Statistical learning algorithms are finding more and more applications in science and technology. Atomic-scale modeling is no exception, with machine learning becoming commonplace as a tool to predict energy, forces and properties of…

Chemical Physics · Physics 2020-12-09 Félix Musil , Michele Ceriotti

This review presents some of the challenges in constructing models of atomic nuclei starting from theoretical descriptions of the strong interaction between nucleons. The focus is on statistical computing and methods for analyzing the link…

Nuclear Theory · Physics 2019-12-06 Andreas Ekström

Multiscale modelling is a new paradigm that has emerged in recent times to study the well-known problem of the process-structure-property relationship in the area of materials science and engineering. For obtaining the desired performance…

Materials Science · Physics 2023-10-10 Rupesh Chafle , Vishal Panwar , Kaushik Das , Somnath Bhowmick , Rajdip Mukherjee

Simulations at the atomic scale provide a direct and effective way to understand the mechanical properties of materials. In the regime of classical mechanics, simulations for the thermodynamic properties of metals and alloys can be done by…

Computational Physics · Physics 2019-11-05 Ka-Ming Tam , Nicholas Walker , Samuel Kellar , Mark Jarrell

The first step in the construction of a regression model or a data-driven analysis, aiming to predict or elucidate the relationship between the atomic scale structure of matter and its properties, involves transforming the Cartesian…

Atomistic modelling of magnetic materials provides unprecedented detail about the underlying physical processes that govern their macroscopic properties, and allows the simulation of complex effects such as surface anisotropy, ultrafast…

Atomistic simulations have become a powerful tool in materials research due to the extremely fine spatial and temporal resolution provided by such techniques. In order to understand the fundamental principles which govern material behavior…

Materials Science · Physics 2014-08-26 Jason F. Panzarino , Timothy J. Rupert

Atomistic simulations based on the first-principles of quantum mechanics are reaching unprecedented length scales. This progress is due to the growth in computational power allied with the development of new methodologies that allow the…

Materials Science · Physics 2021-05-19 Mariana Rossi

While machine learning (ML) models have been able to achieve unprecedented accuracies across various prediction tasks in quantum chemistry, it is now apparent that accuracy on a test set alone is not a guarantee for robust chemical modeling…

Atomistic-continuum multiscale modelling is becoming an increasingly popular tool for simulating the behaviour of materials due to its computational efficiency and reliable accuracy. In the case of ferromagnetic materials, the atomistic…

Computational Physics · Physics 2019-02-01 Doghonay Arjmand , Mikhail Poluektov , Gunilla Kreiss

Studies in nuclear and atomic physics have played an important role in developing our understanding of the Standard Model of electroweak interactions. We review the basic ingredients of the Standard Model, and discuss some key nuclear and…

Nuclear Theory · Physics 2017-08-23 M. J. Ramsey-Musolf , J. Secrest

Classical atomistic simulations based on interatomic potentials resolve lattice instabilities, defect nucleation, and microstructure evolution with high fidelity, but their accessible system sizes remain far below those required for…

Numerical Analysis · Mathematics 2026-05-26 Aagashram Neelakandan , Karsten Albe , Bernhard Eidel

After many years of development of the basic tools, quantum simulation with ultracold atoms has now reached the level of maturity where it can be used to investigate complex quantum processes. Planning of new experiments and upgrading…

Quantum Gases · Physics 2020-07-13 Florian Schäfer , Takeshi Fukuhara , Seiji Sugawa , Yosuke Takasu , Yoshiro Takahashi

Automated analyses of the outcome of a simulation have been an important part of atomistic modeling since the early days, addressing the need of linking the behavior of individual atoms and the collective properties that are usually the…

Chemical Physics · Physics 2019-05-22 Michele Ceriotti

Predicting the structural response of advanced multiphase alloys and understanding the underlying microscopic mechanisms that are responsible for it are two critically important roles modeling plays in alloy development. An alloys…

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

Atomic scale nanowires attract enormous interest in a wide range of fields. On the one hand, due to their quasi-one-dimensional nature, they can act as a experimental testbed for exotic physics: Peierls instability, charge density waves,…

Materials Science · Physics 2014-03-13 Danny E. P. Vanpoucke

All-atom simulations can provide molecular-level insights into the dynamics of gas-phase, condensed-phase and surface processes. One important requirement is a sufficiently realistic and detailed description of the underlying intermolecular…

Chemical Physics · Physics 2022-06-15 K. Töpfer , M. Upadhyay , M. Meuwly

Accuracy of molecular dynamics simulations depends crucially on the interatomic potential used to generate forces. The gold standard would be first-principles quantum mechanics (QM) calculations, but these become prohibitively expensive at…

The performance of basis sets made of numerical atomic orbitals is explored in density-functional calculations of solids and molecules. With the aim of optimizing basis quality while maintaining strict localization of the orbitals, as…

Materials Science · Physics 2009-11-07 Javier Junquera , Oscar Paz , Daniel Sanchez-Portal , Emilio Artacho
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