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Marko Petković

3 papers here

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3

Across the 3 of 3 papers where every author was matched, so the position is known.

fields
  • cond-mat.mtrl-sci2
  • cs.AI1
ORCID 0009-0000-4918-6027

identity via Semantic Scholar / OpenAlex

most citedGraph Neural Networks for Carbon Dioxide Adsorption Prediction in Aluminium-Exchanged Zeolites

2 citations · 3 across the 3 of their papers we have counts for

collaborators

3 papers

cs.AI2025★ 1 cited

Towards Fully Automated Molecular Simulations: Multi-Agent Framework for Simulation Setup and Force Field Extraction

Marko Petković, Vlado Menkovski, Sofía Calero

Automated characterization of porous materials has the potential to accelerate materials discovery, but it remains limited by the complexity of simulation setup and force field sel…

cond-mat.mtrl-sci2025

Symmetry-Informed Graph Neural Networks for Carbon Dioxide Isotherm and Adsorption Prediction in Aluminum-Substituted Zeolites

Marko Petković, José-Manuel Vicent Luna, El\=ıza Beate Dinne +2

Accurately predicting adsorption properties in nanoporous materials using Deep Learning models remains a challenging task. This challenge becomes even more pronounced when attempti…

cond-mat.mtrl-sci2024★ 2 cited

Graph Neural Networks for Carbon Dioxide Adsorption Prediction in Aluminium-Exchanged Zeolites

Marko Petković, José Manuel Vicent-Luna, Vlado Menkovski +1

The ability to efficiently predict adsorption properties of zeolites can be of large benefit in accelerating the design process of novel materials. The existing configuration space…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.