Publications related to Unsupervised landmark analysis for jump detection in molecular dynamics simulations

Related publications (33)

Solvation Free Energies from Machine Learning Molecular Dynamics

Nicola Marzari, Nicéphore Arthur François Bonnet

The present work proposes an extension to the approach of [Xi, C; et al. J. Chem. Theory Comput. 2022, 18, 6878] to calculate ion solvation free energies from first-principles (FP) molecular dynamics (MD) simulations of a hybrid solvation model. The approa ...

Amer Chemical Soc2024

Efficient and insightful descriptors for representing molecular and material space

Alexander Jan Goscinski

Data-driven approaches have been applied to reduce the cost of accurate computational studies on materials, by using only a small number of expensive reference electronic structure calculations for a representative subset of the materials space, and using ...

EPFL2024

Hydrodynamical simulations of merging galaxy clusters: giant dark matter particle colliders, powered by gravity

David Richard Harvey

Terrestrial particle accelerators collide charged particles, then watch the trajectory of outgoing debris - but they cannot manipulate dark matter. Fortunately, dark matter is the main component of galaxy clusters, which are continuously pulled together by ...

Oxford Univ Press2024

Hidden Gems on a Ring: Infant Massive Clusters and Their Formation Timeline Unveiled by ALMA, HST, and JWST in NGC 3351

Robin Gopala Tress

We use 0.1 '' observations from the Atacama Large Millimeter Array (ALMA), Hubble Space Telescope (HST), and JWST to study young massive clusters (YMCs) in their embedded "infant" phase across the central starburst ring in NGC 3351. Our new ALMA data revea ...

Iop Publishing Ltd2024

Thermal conductivity of Li 3 PS 4 solid electrolytes with ab initio accuracy

Michele Ceriotti, Federico Grasselli, Davide Tisi, Lorenzo Gigli

The vast amount of computational studies on electrical conduction in solid-state electrolytes is not mirrored by comparable efforts addressing thermal conduction, which has been scarcely investigated despite its relevance to thermal management and (over)he ...

Amer Physical Soc2024

The effect of pressure-anisotropy-driven kinetic instabilities on magnetic field amplification in galaxy clusters

Salim Bennouna, Yoan Rappaz

Context. The intracluster medium (ICM) is the low-density diffuse gas that fills the space between galaxies within galaxy clusters. It is primarily composed of magnetized plasma, which reaches virial temperatures of up to 10(8) K, probably due to mergers o ...

Edp Sciences S A2024

Thermal transport of glasses via machine learning driven simulations

Federico Grasselli, Paolo Pegolo

Accessing the thermal transport properties of glasses is a major issue for the design of production strategies of glass industry, as well as for the plethora of applications and devices where glasses are employed. From the computational standpoint, the che ...

Frontiers Media Sa2024

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

Ksenia Briling

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

A pre-fatigue training strategy to stabilize LiCoO2 at high voltage

Lei Zhang, Kangning Zhao

Layered cathodes are among the most promising cathodes for high-energy-density Li-ion batteries, yet hindered by the structural degradation from both bulk strain and surface oxygen loss at high voltage (above 4.5 V). Herein, we report a pre-fatigue trainin ...

Royal Soc Chemistry2024

Seebeck Coefficient of Ionic Conductors from Bayesian Regression Analysis

Paolo Pegolo

We propose a novel approach to evaluating the ionic Seebeck coefficient in electrolytes from relatively short equilibrium molecular dynamics simulations, based on the Green-Kubo theory of linear response and Bayesian regression analysis. By exploiting the ...

Amer Chemical Soc2024

Characterising directed and undirected metrics of high-order interdependence

Michael Christoph Gastpar

Systems of interest for theoretical or experimental work often exhibit high-order interactions, corresponding to statistical interdependencies in groups of variables that cannot be reduced to dependencies in subsets of them. While still under active develo ...

Institute of Electrical and Electronics Engineers Inc.2024

A diversity-driven discovery of potential nanoporous materials for energy-related applications

Sauradeep Majumdar

The design and discovery of potential novel materials is critical for the advancement of climate change mitigation technologies. In this respect, metal-organic frameworks (MOFs) have received considerable attention over the last two decades. The combinatio ...

EPFL2024

Exciton migration in two-dimensional materials

Giovanni Consalvo Cistaro

Excitons play an essential role in the optical response of two-dimensional materials. These are bound states showing up in the band gaps of many-body systems and are conceived as quasiparticles formed by an electron and a hole. By performing real-time simu ...

Nature Portfolio2024

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

François Louis Mouvet

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 ...

EPFL2023

Elastocapillary menisci mediate interaction of neighboring structures at the surface of a compliant solid

John Martin Kolinski, Lebohang Molefe

Surface stress drives long-range elastocapillary interactions at the surface of compliant solids, where it has been observed to mediate interparticle interactions and to alter the transport of liquid drops. We show that such an elastocapillary interaction ...

2023

The PHANGS-JWST Treasury Survey: Star Formation, Feedback, and Dust Physics at High Angular Resolution in Nearby GalaxieS

Robin Gopala Tress

The PHANGS collaboration has been building a reference data set for the multiscale, multiphase study of star formation and the interstellar medium (ISM) in nearby galaxies. With the successful launch and commissioning of JWST, we can now obtain high-resolu ...

IOP Publishing Ltd2023

Inferring free-energy barriers and kinetic rates from molecular dynamics via underdamped Langevin models

David Daniel Girardier, Fabio Pietrucci, Sara Bonella

Rare events include many of the most interesting transformation processes in condensed matter, from phase transitions to biomolecular conformational changes to chemical reactions. Access to the corresponding mechanisms, free-energy landscapes and kinetic r ...

Aip Publishing2023

The role of Zn in C-S-H atomic structure, nucleation and growth

Anna Morales Melgares

The most promising solution towards cementitious materials with a lower carbon footprint is the partial substitution of the clinker by supplementary cementitious materials (SCMs) such as fly ash, blast furnace slag, limestone and calcined clays. The produc ...

EPFL2023

Atomic scale volume and grain boundary diffusion elucidated by in situ STEM

Johann Michler, Xavier Maeder, Laszlo Pethö

Diffusion is one of the most important phenomena studied in science ranging from physics to biology and, in abstract form, even in social sciences. In the field of materials science, diffusion in crystalline solids is of particular interest as it plays a p ...

Nature Portfolio2023

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