Dear visitor, welcome to my homepage. My name is Julien Lam and after working in Lyon, Bristol, Brussels and Toulouse, I now hold a CNRS permanent position to work in UMET (Lille). My research focuses on the use of machine-learning potentials and free energy calculations to study nucleation mechanisms related to the formation of nanocrystals.
Research interests:
Nucleation, Crystallization, Machine-learning interaction potentials, Free energy sampling, Nanoparticle synthesis
Few links:
Orcid – Google scholar – ResearchGate – Twitter
Newsfeed:
January 15th, 2024
Glad to welcome the whole bunch of enthousiastic new students for this new year including:
– Lorena Chabeaud from Montpellier as PhD student co-advised with Hazar Guesmi
– Valentino Sanguinetti from Argentina as Master student
– Roberto Tabacco from Italy as Master student
– Gaetan Loubet dit Gajol as Bachelor student
December 12th, 2023
Delighted to announce the first paper of our PhD student Q. Gromoff published in Nanoscale. Experiments and simulations were coupled to study the formation of AuAg nanoparticles. (See LINK)
June 20th, 2023
Happy about this paper in collaboration with Kevin Rossi, Claudio Zenny and Daniel Förster published in CarbonTrends. We combined data-driven approaches with molecular dynamics simulations to observe the formation of carbon nanoparticles. (See LINK)
January 31st, 2023
Excited to share this new paper in collaboration with Fabio Pietrucci from IMPMC. Huge thanks to Pablo Piaggi for early assisting me with the PLUMED setup (See link)
January 1st, 2023
Very pleased to move back to the North in Lille working at the Unité Matériaux et Transformation. Gratefull to CNRS for allowing me to do this long-term mission in a new institute and location while keeping my permanent position.
October 3rd, 2022
Happy to officially welcome Quentin Gromoff in the group as the second PhD student. He will be using our PLIP model to construct new machine-learning interaction potential and will develop innovative structural analysis tools to investigate crystallization in nanoparticles.z
September 30th, 2022
Just like every beginning of school year, we have plenty of opportunities for research internships (L3, M1, M2) that may be pursued into PhD if lucky. Here is a non-exhaustive list of possibilities:
– Machine-learning approaches to model interatomic interactions in materials
– Observing crystal at birth from experiments to simulations
– Data-driven structure analysis at the atomic scale for nanostructures
– Controlling seeded crystallization by optical trapping
September 29th, 2022
Verry happy that Simon Tricard from LPCNO has invited me to give a seminar. It was a pleasure discussing with him but also Lise-Marie Lacroix, Guillaume Viau and Katerina Soulantica. Looking forward to build further collaborations!
April 11th, 2022
Pr. Pavlo Dral solicited me few months ago to participate in a book edited with Elsevier. I was glad to write the chapter dedicated to “Potentials based on linear models”. Today, I am very happy to announce that it can be pre-ordered now using the following link.
November 15th, 2021
Happy to welcome Akshay Krishna Ammothum Kandy from Uppsala University who will work as Postdoc for two years on developing new strategies for machine-learning interaction potentials based on linear regressions.
August 15th, 2021
Following almost 5 years in the wonderful city of Brussels, I finally moved to Toulouse to continue my adventures at CEMES!
July 15th, 2021
Grateful to ANR for financing my JCJC research project: “Studying nucleation in nanoparticle synthesis using machine-learning assisted atomistic simulation” I will have the chance to hire a Postdoc (2y.) and PhD student (3y.). Here, you can find the advertisement for the postdoc position in collaboration with Magali Benoit and Rémi Arras.
June 10th, 2021
Very honored to officially welcome my first PhD student César Jara in co-suppervision with Anne Hemeryck (LAAS-CNRS). Since March 2020, César is studying the modelling of defects at the interface layers in silicides. Me, I am simply jumping on board to help with the development of machine-learning interaction potentials and the subsequent study of inherent phase-transitions.
June 2th, 2021
While Owen Fresse–Colson and Thomas Da Rocha are finishing their internship, I am glad to welcome a new L3 student: Alexis Raulin-Foissac. His work will focus a comparison between our own machine-learning method “Physical LassoLars Interaction Potential” (PLIP) and the more commonly employed “Artificial Neural Network Potentials”.
March 24th, 2021
Very happy to announce that our project entitled “Crystallization of nanoalloys for electrocatalysis: Synthesis, characterization and simulation” has been selected by NanoX for funding within the call for disruptive research project. Special thanks to my partners in crime: Magali Benoit, Patrizio Benzo and Mathieu Prévot!
January 19th, 2021
Yesterday, I had the chance to present my work in a TimeMan Virtual Seminar. The group was very welcoming and it fostered an interesting discussion. Please find the video of my presentation here.
December 31th, 2020
After answering the call for proposals for usage of the Toulouse’s HPC center, CALMIP, we got awarded 1.1 million computing hours for 2 projects:
– Crystallization and glass transition in Germanium Telluride (500 000 hours)
– Polymorph selection in Zinc oxyde (600 000 hours)
I am grateful to CALMIP’s scientific committee for supporting these new and exciting research projects.
November 29th, 2020
Happy to welcome two students who will start their 5 months internship by February 2021: Owen Fresse–Colson and Thomas Da Rocha. The first one will work on some technical developpments for our Φ-LassoLars method and the second one will work on the Seeding method for binary crystallization. Special thanks to the Licence Physique Parcours SPÉCIAL of Université Paul Sabatier.
November 12th, 2020
Our work on “Measuring transferability issues in machine-learning force fields” in collaboration with M. Benoit and J. Amodeo is now published in Machine Learning: Science and Technology. It’s the first paper where we detail our PLIP method to generate machine-learning interaction potentials. (See Link)
September 3rd, 2020
Our work on “Out-of-Equilibrium Polymorph Selection in Nanoparticle Freezing” in collaboration with F. Piettrucci and J. Amodeo is now published in Journal of Physical Chemistry Letters. It deals with a problem that I first encountered during my thesis and I can finaly study using MD and metadynamics. (See Link)
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