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Pressure, relaxation volume, and elastic interactions in charged simulation cells

Related publications (39)

Encoding quantum-chemical knowledge into machine-learning models of complex molecular properties

Statistical (machine-learning, ML) models are more and more often used in computational chemistry as a substitute to more expensive ab initio and parametrizable methods. While the ML algorithms are capable of learning physical laws implicitly from data, ad ...

EPFL2024

Predicting Ion Diffusion from the Shape of Potential Energy Landscapes

Berend Smit, Senja Dominique Barthel, Amber Kashan Mace

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 ...

Washington2023

Advancing Computational Chemistry with Stochastic and Artificial Intelligence Approaches

Justin Villard

Computational chemistry aims to simulate reactions and molecular properties at the atomic scale, advancing the design of novel compounds and materials with economic, environmental, and societal implications. However, the field relies on approximate quantum ...

EPFL2023

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Non-covalent bonding patterns are commonly harvested as a design principle in the field of catalysis, supramolecular chemistry, and functional materials to name a few. Yet, their computational description generally neglects finite temperature and environme ...

2022

Transferable machine-learning models of complex materials: the case of GaAs

Giulio Imbalzano

Molecular simulations allow to investigate the behaviour of materials at the atomistic level, shedding light on phenomena that cannot be directly observed in experiments. Accurate results can be obtained with ab initio methods, while simulations of large-s ...

EPFL2021

First-principles calculations of charge carrier mobility and conductivity in bulk semiconductors and two-dimensional materials

Samuel Poncé, Feliciano Giustino

One of the fundamental properties of semiconductors is their ability to support highly tunable electric currents in the presence of electric fields or carrier concentration gradients. These properties are described by transport coefficients such as electro ...

IOP PUBLISHING LTD2020

Deterministic and Statistical Approaches to Quantum Chemistry

Alberto Fabrizio

The field of quantum chemistry has recently undergone a series of paradigm shifts, including a boom in machine learning applications that target the electronic structure problem. Along with these technological innovations, the community continues to identi ...

EPFL2020

The redox potential of molecular species is largely modulated by its molecular environment so that a change of the environment will lead to a different redox potential. However, a detailed molecular picture of reorganization of the environment upon reducti ...

AMER CHEMICAL SOC2019

Alignment of energy levels in amorphous oxides and at semiconductor-water interfaces

Zhendong Guo

We conduct a detailed investigation of defects in two representative amorphous oxides: amorphous Al2O3 (am-Al2O3) and TiO2 (am-TiO2), by combining ab initio molecular dynamics (MD) simulations and hybrid functional calculations. Our results indicate that o ...

EPFL2019

i-PI 2.0: A universal force engine for advanced molecular simulations

Michele Ceriotti, David Mark Wilkins, Bingqing Cheng, Venkat Kapil, Riccardo Petraglia, Gareth Aneurin Tribello, Mariana Rossi Carvalho, Benjamin Aaron Helfrecht, Robert Horst Meissner, Alice Cuzzocrea, Sébastien Pierre Bienvenue, Przemyslaw Juda, Wei Fang

Progress in the atomic-scale modeling of matter over the past decade has been tremendous. This progress has been brought about by improvements in methods for evaluating interatomic forces that work by either solving the electronic structure problem explici ...

ELSEVIER SCIENCE BV2019

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