Cyrille Lavigne

TL;DR: The most recent contributions of this group in this thriving field of machine learning for material science are reviewed, focusing on small molecules as organic electronic materials and crystalline materials and the data-driven approaches they employed to speed up discovery and derive material design strategies.

TL;DR: In this article, gold nanoparticles with mesogenic coatings, tailored to be highly miscible in the liquid phase of n-alkyl-cyanobiphenyl LCs, form reversible micron-scale networks on cooling at the clearing point by enrichment of the NPs at the nematic-isotropic liquid interfaces.

TL;DR: In this article, the authors proposed that the AuNPs concentrate at edge dislocation defects of the smectic phase, based on the dependence of the geometry and periodicity of the arrays on boundary conditions.

TL;DR: Tequila is a development package for quantum algorithms in python, designed for fast and flexible implementation, prototyping and deployment of novel quantumgorithms in electronic structure and other fields, and compiled to run on state of the art quantum simulators or interfaces.

TL;DR: In this paper, the authors describe the first molecules with negative singlet-triplet gaps and considerable fluorescence rates and show that they are more common than hypothesized previously, based on computational studies.