Publications associées à Implementation of drift velocities and currents in SOLEDGE2D-EIRENE

Verification of the Fourier-enhanced 3D finite element Poisson solver of the gyrokinetic full-f code PICLS

Laurent Villard, Stephan Brunner, Moahan Murugappan, Alberto Bottino

We introduce and derive the Fourier -enhanced 3D electrostatic field solver of the gyrokinetic full -f PIC code PICLS. The solver makes use of a Fourier representation in one periodic direction of the domain to make the solving of the system easily paralle ...

Elsevier2024

Second harmonic scattering of nanoparticles: A journey into the electrical double layer

Bingxin Chu

In aqueous solutions, a charged surface causes the redistribution of nearby ions. The ion layers formed are known as the electrical double layer (EDL), and are widespread in many systems involving electrochemistry, colloidal science, biomedicine, and energ ...

EPFL2024

Adaptive Symplectic Model Order Reduction Of Parametric Particle-Based Vlasov-Poisson Equation

Jan Sickmann Hesthaven, Nicolò Ripamonti, Cecilia Pagliantini

. High-resolution simulations of particle-based kinetic plasma models typically require a high number of particles and thus often become computationally intractable. This is exacerbated in multi-query simulations, where the problem depends on a set of para ...

AMER MATHEMATICAL SOC2023

Device, system, and method for ion fragmentation by use of an ion mobility device and messenger tagging

Thomas Rizzo, Ahmed Ben Faleh, Stephan Warnke

A device for fragmenting ions by collision induced dissociation, the device intended to be used together with a planar ion mobility apparatus, the device including a first conductive grid having a plurality of first openings, the first conductive grid conf ...

2023

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 ...

Amer Chemical Soc2023

A reduced-order, rotation-based model for thin hard-magnetic plates

Pedro Miguel Nunes Pereira de Almeida Reis, Dong Yan, Bastien Freddy Gustave Aymon

We develop a reduced-order model for thin plates made of hard magnetorheological elastomers (hard-MREs), which are composed of hard-magnetic particles embedded in a polymeric matrix. First, we propose a new magnetic potential, as an alternative to an exist ...

PERGAMON-ELSEVIER SCIENCE LTD2023

High entropy molybdate-derived FeOOH catalyzes oxygen evolution reaction in alkaline media

Lichen Bai, Seunghwa Lee

High-entropy materials are a new class of materials that have lately been developed and applied to a variety of potential fields. Here we present that electrochemical activation facilitates the application of high-entropy molybdates (HEMo) as oxygen evolut ...

PERGAMON-ELSEVIER SCIENCE LTD2023

Evolution of the electrical double layer with electrolyte concentration probed by second harmonic scattering

Sylvie Roke, Arianna Marchioro, Bingxin Chu, Marie Bischoff

Investigating the electrical double layer (EDL) structure has been a long-standing challenge and has seen the emergence of several sophisticated techniques able to probe selectively the few molecular layers of a solid/water interface. While a qualitative e ...

ROYAL SOC CHEMISTRY2023

Grassmannian diffusion maps based surrogate modeling via geometric harmonics

Ketson Roberto Maximiano Dos Santos

A novel surrogate model based on the Grassmannian diffusion maps (GDMaps) and utilizing geometric harmonics (GH) is developed for predicting the response of complex physical phenomena. The method utilizes GDMaps to obtain a low-dimensional representation o ...

Wiley2022

PDE-Aware Deep Learning for Inverse Problems in Cardiac Electrophysiology

Alfio Quarteroni, Simone Deparis, Riccardo Tenderini, Stefano Pagani

In this work, we present a PDE-aware deep learning model for the numerical solution to the inverse problem of electrocardiography. The model both leverages data availability and exploits the knowledge of a physically based mathematical model, expressed by ...

2022