Publications associées à DeePMD-kit v2: A software package for deep potential models

Publications associées (17)

Wear across scales

When two objects are rubbed together, they create friction, heat, and their surfaces might be worn away. However, the fundamental mechanisms behind these processes remain poorly understood. While empirical engineering models exist, they are tailored to spe ...

EPFL2025

Momentum tunnelling between nanoscale liquid flows

Nikita Kavokine

The world of nanoscales in fluidics is the frontier where the continuum of fluid mechanics meets the atomic, and even quantum, nature of matter. While water dynamics remains largely classical under extreme confinement, several experiments have recently rep ...

2025

Automated Parameterization for Aerodynamic Shape Optimization via Deep Geometric Learning

Pascal Fua, Zhen Wei

Traditional aerodynamic shape optimization (ASO) is costly and time-intensive, requiring extensive manual tuning for parameterization to define the design space and manipulate geometries. Conventional parameterization methods limit flexibility and demand s ...

American Institute of Aeronautics and Astronautics (AIAA)2025

Expanding density-correlation machine learning representations for anisotropic coarse-grained particles

Jigyasa Nigam, Kevin Kazuki Huguenin-Dumittan

Physics-based, atom-centered machine learning (ML) representations have been instrumental to the effective integration of ML within the atomistic simulation community. Many of these representations build off the idea of atoms as having spherical, or isotro ...

2024

Predicting protein interactions using geometric deep learning on protein surfaces

Freyr Sverrisson

In the domain of computational structural biology, predicting protein interactions based on molecular structure remains a pivotal challenge. This thesis delves into this challenge through a series of interconnected studies. The first chapter introduces th ...

EPFL2024

Bayesian optimization of massive material injection for disruption mitigation in tokamaks

Carl Mathias Paul Hoppe

A Bayesian optimization framework is used to investigate scenarios for disruptions mitigated with combined deuterium and neon injection in ITER. The optimization cost function takes into account limits on the maximum runaway current, the transported fracti ...

Cambridge University Press2023

Modeling Structured Data in Attention-based Models

Alireza Mohammadshahi

Natural language processing has experienced significant improvements with the development of Transformer-based models, which employ self-attention mechanism and pre-training strategies. However, these models still present several obstacles. A notable issue ...

EPFL2023

Transport and Interfacial Injection of d-Band Hot Holes Control Plasmonic Chemistry

Omer Can Karaman, Giulia Tagliabue, Fateme Kiani Shahvandi, Alan Richard Bowman, Milad Sabzehparvar

Harnessing nonequilibrium hot carriers from plasmonic metal nanostructures constitutes a vibrant research field with the potential to control photochemical reactions, particularly for solar fuel generation. However, a comprehensive understanding of the int ...

AMER CHEMICAL SOC2023

Super-harmonically resonant swirling waves in longitudinally forced circular cylinders

François Gallaire, Alessandro Bongarzone, Alice Evelyne Julienne Marcotte

Resonant sloshing in circular cylinders was studied by Faltinsen et al. (J. Fluid Mech., vol. 804, 2016, pp. 608-645), whose theory was used to describe steady-state resonant waves due to a time-harmonic container's elliptic orbits. In the limit of longitu ...

Cambridge University Press2023

Interactions of Cavitation Bubbles with Deformable Interfaces

Armand Baptiste Sieber

Cavitation is a topic that has long been of interest due to the large and growing range of applications associated with it. This is mainly because the collapse of cavitation bubbles releases a considerable amount of energy into the surrounding environment. ...

EPFL2023

Recent Advances in First-Principles Based Molecular Dynamics

Ursula Röthlisberger, Justin Villard, François Louis Mouvet, Viacheslav Bolnykh

First-principles molecular dynamics (FPMD) and its quantum mechanical-molecular mechanical (QM/MM) extensions are powerful tools to follow the real-time dynamics of a broad variety of systems in their ground as well as electronically excited states. The co ...

American Chemical Society2022

Conformal Field Theory at the Lattice Level: Discrete Complex Analysis and Virasoro Structure

Clément Hongler

Critical statistical mechanics and Conformal Field Theory (CFT) are conjecturally connected since the seminal work of Beliavin et al. (Nucl Phys B 241(2):333-380, 1984). Both exhibit exactly solvable structures in two dimensions. A long-standing question ( ...

SPRINGER2022

Error measurements for a quantum annealer using the one-dimensional Ising model with twisted boundaries

Gabriel Aeppli

A finite length ferromagnetic chain with opposite spin polarization imposed at its two ends is one of the simplest frustrated spin models. In the clean classical limit the domain wall inserted on account of the boundary conditions resides with equal probab ...

NATURE PORTFOLIO2022

Dark Energy Survey Year 3 results: Cosmology from cosmic shear and robustness to data calibration

Jonathan Andrew Blazek

This work, together with its companion paper, Secco, Samuroff et al. [Phys. Rev. D 105, 023515 (2022)], present the Dark Energy Survey Year 3 cosmic-shear measurements and cosmological constraints based on an analysis of over 100 million source galaxies. W ...

American Physical Society2022

Realistic Modelling of Dynamics at Nanostructured Interfaces Relevant to Heterogeneous Catalysis

Kevin Rossi

The focus of this short review is directed towards investigations of the dynamics of nanostructured metallic heterogeneous catalysts and the evolution of interfaces during reaction-namely, the metal-gas, metal-liquid, and metal-support interfaces. Indeed, ...

MDPI2022

Fe-57-Enrichment effect on the composition and performance of Fe-based O-2-reduction electrocatalysts

Jeremy Luterbacher, Benjamin Pierre Le Monnier

Pt-group metal (PGM)-free catalysts of the Me-N-C type based on abundant and inexpensive elements have gained importance in the field of oxygen reduction reaction (ORR) electrocatalysis due to their promising ORR-activities. Their insufficient stability, h ...

2021

Electronic-structure methods for materials design

Nicola Marzari

Simulations can be used to accelerate the characterization and discovery of materials. Here we Review how electronic-structure methods such as density functional theory work, what properties they can be used to predict and how they can be used to design ma ...

NATURE RESEARCH2021