Solvation of Palladium Clusters in an Ionic Liquid: A QM/MM Molecular Dynamics Study

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Atomic-level structure determination of amorphous molecular solids by NMR

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Structure determination of amorphous materials remains challenging, owing to the disorder inherent to these materials. Nuclear magnetic resonance (NMR) powder crystallography is a powerful method to determine the structure of molecular solids, but disorder ...

Nature Portfolio2023

Universal machine learning for the response of atomistic systems to external fields

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Machine learned interatomic interaction potentials have enabled efficient and accurate molecular simulations of closed systems. However, external fields, which can greatly change the chemical structure and/or reactivity, have been seldom included in curren ...

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Factorized structure of the long-range two-electron integrals tensor and its application in quantum chemistry

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We introduce two new approximation methods for the numerical evaluation of the long-range component of the range-separated Coulomb potential and the approximation of the resulting high dimensional Two-Electron Integrals tensor (TEI) with long-range interac ...

Academic Press Inc Elsevier Science2023

Predicting Ion Diffusion from the Shape of Potential Energy Landscapes

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We present an efficient method to compute diffusion coefficients of multiparticle systems with strong interactions directly from the geometry and topology of the potential energy field of the migrating particles. The approach is tested on Li-ion diffusion ...

Amer Chemical Soc2023

Advancing first principle-based molecular dynamics of biological systems with machine learning

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Molecular dynamics (MD) simulations have emerged as a transformative approach to analyse molecular systems at the atomic level, offering valuable insights into complex biological processes. Many biological phenomena can only accurately be described by inco ...

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Towards high-throughput many-body perturbation theory: efficient algorithms and automated workflows

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The automation of ab initio simulations is essential in view of performing high-throughput (HT) computational screenings oriented to the discovery of novel materials with desired physical properties. In this work, we propose algorithms and implementations ...

NATURE PORTFOLIO2023

Magnetic orderings and electronic structure of complex oxides from advanced Hubbard functionals

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Transition metal oxides represent a class of materials displaying very unusual electronic, structural and magnetic properties. They are extremely interesting, both from a technological and fundamental point of view. The most important characteristic of the ...

EPFL2023

Coupled Rotary and Oscillatory Motion in a Second-Generation Molecular Motor Pd Complex

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Molecular machines offer many opportunities for the development of responsive materials and introduce autono-mous motion in molecular systems. While basic molecular switches and motors carry out one type of motion upon being exposed to an external stimulus ...

AMER CHEMICAL SOC2023

Comparing transferability in neural network approaches and linear models for machine-learning interaction potentials

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Atomic simulations using machine learning interatomic potential (MLIP) have gained a lot of popularity owing to their accuracy in comparison to conventional empirical potentials. However, the transferability of MLIP to systems outside the training set pose ...

AMER PHYSICAL SOC2023

Lattice Green's function method for Atomistic/Continuum coupling

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Metal plasticity is an inherently multiscale phenomenon due to the complex long-range field of atomistic dislocations that are the primary mechanism for plastic deformation in metals. Atomistic/Continuum (A/C) coupling methods are computationally efficient ...

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koopmans: An Open-Source Package for Accurately and Efficiently Predicting Spectral Properties with Koopmans Functionals

Nicola Marzari, Nicola Colonna, Edward Baxter Linscott, Ngoc Linh Nguyen, Giovanni Borghi, Riccardo De Gennaro

Over the past decade we have developed Koopmans functionals, a computationally efficient approach for predicting spectral properties with an orbital-density-dependent functional framework. These functionals impose a generalized piecewise linearity conditio ...

Amer Chemical Soc2023