arXiv Machine Learning July 22, 2026 By Lara Goncebat (Instituto de Qu\'imica Aplicada del Litoral IQAL), Rodrigo Echeveste (Instituto de Investigaci\'on en Se\~nales, Sistemas e Inteligencia Computacional sinc), Mat\'ias Gerard (Instituto de Investigaci\'on en Se\~nales, Sistemas e Inteligencia Computacional sinc), Frederik Tielens (General Chemistry), Gustavo Belletti (Instituto de Qu\'imica Aplicada del Litoral IQAL), Paola Quaino (Instituto de Qu\'imica Aplicada del Litoral IQAL)

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

Read the original on arXiv Machine Learning →

arXiv:2607. 18591v1 Announce Type: cross Abstract: 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.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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