Atomic investigations of dislocation phenomena in HCP magnesium and BCC high entropy alloys

À propos
Confidentialité
Mentions légales

Graph Chatbot

Publications associées (5)

Page 1 sur 1

Hyphenated elemental analysis methods for characterizing trace gas compounds and nano-objects for energy and environmental applications

Ayush Agarwal

This thesis addresses two urgent challenges in the pursuit of cleaner energy and environmental sustainability. First, it advances the quantification of problematic trace compounds in biogas derived from waste streams. Second, it refines rapid characterizat ...

EPFL2025

Computational Inverse Design of Shape Morphing Structures

Yingying Ren

Shape-morphing structures can transform between multiple geometric configurations, enabling a wide range of applications in architecture, robotics, personalizable medical devices, emergency shelters, and space technology. This thesis presents computational ...

EPFL2024

A recipe for cracking the quantum scaling limit with machine learned electron densities

Mario Geiger

A long-standing goal of science is to accurately simulate large molecular systems using quantum mechanics. The poor scaling of current quantum chemistry algorithms on classical computers, however, imposes an effective limit of about a few dozen atoms on tr ...

IOP Publishing Ltd2023

Charge fluctuations in the intermediate-valence ground state of SmCoIn5

Nicola Colonna

The microscopic mechanism of heavy band formation, relevant for unconventional superconductivity in CeCoIn5 and other Ce-based heavy fermion materials, depends strongly on the efficiency with which f electrons are delocalized from the rare earth sites and ...

NATURE PORTFOLIO2023

What do we talk about, when we talk about single-crystal termination-dependent selectivity of Cu electrocatalysts for CO2 reduction? A data-driven retrospective

Kevin Rossi

We mine from the literature experimental data on the CO2 electrochemical reduction selectivity of Cu single crystal surfaces. We then probe the accuracy of a machine learning model trained to predict faradaic efficiencies for 11 CO2 reduction reaction prod ...

ROYAL SOC CHEMISTRY2023