Publications related to Average-atom interatomic potential for random alloys

Thermal transport of glasses via machine learning driven simulations

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

Modelling of metal alloys in realistic conditions with machine learning

Nataliya Lopanitsyna

Computer simulations based on statistical methods have emerged as a powerful tool for studying structure-property relationships at the atomistic level. However, to provide reliable insights into materials in realistic conditions, it is essential to accurat ...

EPFL2023

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

Johann Michler, Xavier Maeder, Amit Sharma, 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

Gas/Surface reactions probed by reflection absorption infrared spectroscopy

Harmina Vejayan

In my thesis, I present an investigation of the dissociation reactions of gas phase molecules on single crystal metal surfaces studied by a molecular beam in combination with Reflection Absorption Infrared Spectroscopy (RAIRS). Two gas/surface systems were ...

EPFL2023

Many-body physics with strongly interacting fermions coupled to light

Victor Youri Helson

This thesis reports on the realization of the first experiments conducted with superfluid, strongly interacting Fermi gases of 6Li coupled to the light field of an optical cavity. In the scope of existing ultracold atomic platforms, this is the first time ...

EPFL2023

Machine-learned interatomic potentials: Recent developments and prospective applications

William Curtin

High-throughput generation of large and consistent ab initio data combined with advanced machine-learning techniques are enabling the creation of interatomic potentials of near ab initio quality. This capability has the potential of dramatically impacting ...

Springer Heidelberg2023

Cavity Quantum Electrodynamics with strongly correlated fermions

Kevin Etienne Robert Roux

This thesis presents the first cavity quantum electrodynamics experiments performed with a degenerate gas of

^6

Li with strong atom-atom interactions. The first part of this manuscript describes the design and the building of the apparatus that has been e ...

EPFL2022

Long Spin Lifetime in Rare-Earth Single-Atom Magnets at Surfaces

Boris Sorokin

Further miniaturisation of magnetic storage devices requires an advent of new types of magnets, since classical ferromagnetic materials show lack of remanence at nano- and subnanoscale. A single atom can represent the smallest possible bit of information. ...

EPFL2022

Unified theory of atom-centered representations and message-passing machine-learning schemes

Michele Ceriotti, Guillaume André Jean Fraux, Sergey Pozdnyakov, Jigyasa Nigam

Data-driven schemes that associate molecular and crystal structures with their microscopic properties share the need for a concise, effective description of the arrangement of their atomic constituents. Many types of models rely on descriptions of atom-cen ...

AIP Publishing2022

Nanoscale Growth Initiation as a Pathway to Improve the Earth-Abundant Absorber Zinc Phosphide

Anna Fontcuberta i Morral, Elias Zsolt Stutz, Jean-Baptiste Leran, Mahdi Zamani, Simon Robert Escobar Steinvall, Rajrupa Paul, Mirjana Dimitrievska

Growth approaches that limit the interface area between layers to nanoscale regions are emerging as a promising pathway to limit the interface defect formation due to mismatching lattice parameters or thermal expansion coefficient. Interfacial defect mitig ...

AMER CHEMICAL SOC2022