collaborators

14 papers

cond-mat.mtrl-sci2026

High-throughput study of electrical conductivity in ordered metals

Thalis H. B. da Silva, Hai-Chen Wang, Tiago F. T. Cerqueira +3

We present a computational framework that integrates machine learning with high-throughput ab initio calculations to screen over 2.8 million compounds for metallic transport. We id…

cond-mat.mtrl-sci2026

Intrinsic Point Defects and Frenkel Pair Formation in Photovoltaic Absorber ZnP: Regulating -type Conductivity through Growth and Annealing Conditions

Nico Kawashima, Silvana Botti

This study investigates the ground-state energetics and thermodynamics of intrinsic point defects in zinc phosphide ZnP using \emph{ab initio} density functional theory com…

cond-mat.mtrl-sci2026

Cathodoluminescence Analysis of Defects and Grain Boundaries in Zn3P2 Thin Films Grown on Graphene by MOVPE and MBE

Thomas Hagger, Mohammadreza Hassanzadeh, Aidas Urbonavicius +12

Zn3P2 is a promising earth-abundant absorber for thin-film photovoltaics, yet its development is hindered by the lack of lattice-matched substrates, its incompatible thermal expans…

cond-mat.mtrl-sci2026

Functional and Density-Driven Errors in Density Functional Theory: Quantum Monte Carlo Benchmarks for Solids

Ayoub Aouina, Nicolas Tancogne-Dejean, Silvana Botti

We introduce a systematic analysis of density functional approximation errors in solids by separating functional-driven from density-driven contributions using quantum Monte Carlo…

cond-mat.mtrl-sci2026

Optical selection rules in hexagonal Ge polytypes and their lifting by symmetry perturbation

Martin Keller, Haichen Wang, Friedhelm Bechstedt +2

Hexagonal germanium polytypes have emerged as promising direct-gap semiconductors for silicon-integrated optoelectronics, yet their optical properties remain largely unexplored bey…

cond-mat.mtrl-sci2026

AI-Driven Expansion and Application of the Alexandria Database

Théo Cavignac, Jonathan Schmidt, Pierre-Paul De Breuck +9

We present a novel multi-stage workflow for computational materials discovery that achieves a 99% success rate in identifying compounds within 100 meV/atom of thermodynamic stabili…