cond-mat.mtrl-sci · 2026-07-22 · No. 61

Materials Science, 2026-07-22.

2 new papers in cond-mat.mtrl-sci. Titles, authors, abstracts. Links to arXiv. Want this in your inbox every morning? Subscribe →

01 — The papers

2 entries
  1. 01

    ATLAS: A Foundation Neural Sampler for Amorphous Materials

    Mouyang Cheng, Denis Blessing, Botao Yu, Gerhard Neumann, Mingda Li, Carles Domingo-Enrich, Yuanqi Du

    cond-mat.mtrl-sci · cs.LG · physics.comp-ph

    Amorphous materials exhibit exceptional mechanical and functional properties, yet their rugged energy landscapes are notoriously difficult to sample. Below the glass-transition temperature, conventional molecular dynamics and Monte Carlo become inefficient because equilibration relies on rare barrier-crossing events, while data-driven generative models are constrained by scarce and biased reference ensembles. Here, we introduce ATLAS, an...

    arxiv.org/abs/2607.19198 · PDF

  2. 02

    GQD-AdsNet: Graph Neural Networks Unlock Rapid Exploration of Transition Metal Adsorption on Graphene Quantum Dots

    Lara Goncebat, Rodrigo Echeveste, Matías Gerard, Frederik Tielens, Gustavo Belletti, Paola Quaino

    cond-mat.mtrl-sci · cs.LG

    In recent years, interest in single-atom catalysts supported on carbon-based structures has grown considerably due to their high catalytic activity and efficient uses of metal atoms. However, the design and characterization of these materials through first-principles calculations are computationally expensive, limiting the exploration of a large number of possible configurations. Here, we developed a framework based on graph neural networks...

    arxiv.org/abs/2607.18591 · PDF

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