S. Cottenier

Crystallographic Control of Hydrogen Ingress in BCC-Iron: Insights from Ab-Initio Simulations

L. Meier, A.I. Bhatti, L. Kestens, S. Cottenier

ISBN/ISSN:

Poster

Conference / event / venue

ASTM Conference on Hydrogen in Materials

La Rochelle (Fr)

Tuesday, 3 June, 2025 to Friday, 6 June, 2025

Inverse design of energy materials using atomistic deep learning

R. Jennen

Master of Science in Sustainable Materials Engineering

2023

Supervisors

Prof. Dr. Stefaan Cottenier; Prof. Dr. ir. Toon Verstraelen

Inverse design of energy materials using atomistic deep learning

R. Jennen

Master of Science in Materials Engineering

2022

Testing the hell out of DFT codes with virtual oxides

S. Cottenier, M. Callsen, K. Lejaeghere, M. Sluydts, T. Ruh

ISBN/ISSN:

Invited talk

Conference / event / venue

https://www.dft2022.be/

Brussels, Belgium

Sunday, 28 August, 2022 to Friday, 2 September, 2022

Bringing energy materials to market using deep learning for natural language processing

F. Hubau

2021

Supervisors

Dr. ir. M. Sluydts; Prof. dr. S. Cottenier

The Fe-Si phase diagram: from electrical steel to the planet Mercury

Modifying the order-disorder transition in Fe-Si

Inverse design of energy materials using atomistic deep learning

Inhibiting Hydrogen entry in repurposed pipelines for H2-transport

Charting the magnetocrystalline anisotropy energy in iron space

Pages