Research team

Louvain-La-Neuve

Xavier Gonze (PI - spoke person) - UCLouvain

Xavier Gonze has a long track record of contributions to the first-principles formalism, especially focusing on vibrations, response to electric fields and IR spectroscopy but also on Raman spectroscopies and plasmons in nanostructures.
(Research group : PhD students : 3 ; Post-docs : 2 ; Research logistician 1)
(Funded by the project : 1 PhD student ; 1 PhD student 2020 ; 1 Post-doc part time)

Luc Henrard (PI) - UNamur

Luc Henrard brings to the project more than 20 years of experience in the numerical simulations by classical methods of plasmons excitations by light and electrons of various type systems including metallic nanoparticles. On another hand, he has also worked on the Raman response of carbon-based systems with semi-empirical methods. He has also expertise as user of first-principles simulations, including ABINIT.
(Research group : PhD students : 2 ; Post-docs : 2)
(Funded by the project : 1 PhD student ; 1 Post-doc part time)

Vincent Liégeois (co-PI) - UNamur

Vincent Liégeois has developed and implemented quantum chemistry methods as well as graphical tools for the simulation and interpretation of vibrational signatures of isolated and adsorbed molecules.
(Research group : PhD student : 1 ; Post-doc : 1)
(Funded by the project : 1 PhD student 2020-2022 ; 1 Post-doc part time, 1 Post-doc 2023-now)

Gian-Marco Rignanese (co-PI) - UCLouvain

Gian-Marco Rignanese has been involved in the development of first-principles codes for more than 20 years (with a special interest on the ABINIT project). More recently, he collaborated with Ph. Ghosez on the second-principles code MULTIBINIT. Actually, he also always had a strong interest in response functions (vibrational, dielectric, mechanical, and thermodynamical),of materials computed using Density Functional Perturbation Theory (DFPT). Recently, he started collaborating on this topic with Profs. G. Ceder and K. A. Persson at UC Berkeley, and delivered high-throughput DFPT phonon calculations which were released on the Materials Project website. He has also been involved in a community effort about reproducibility in DFT calculations of solids which also lead to the release of accurate pseudopotential tables in the PseudoDojo. His work also focuses on machine learning for predicting material properties.
(Research group : 6 PhD students and 7 Post-docs)
(Funded by the project : 1 PhD student ; 1 Post-doc part time)