1 citations · 1 across the 5 of their papers we have counts for
6 papers
RaspAssistant as an Agentic Framework for Automating Adsorption Simulation Research in Porous Materials
Marko Petković, Susanne Gooijer, José Manuel Vicent-Luna +2
Porous-material adsorption studies require coordinated structure preparation, force-field selection, simulation, validation, and interpretation, making end-to-end automation diffic…
A Dataset of Equilibrium State Configurations of Adsorption in Zeolites
Marko Petković, Rachna Ramesh, Vlado Menkovski +1
Zeolites are crystalline nanoporous materials widely used in adsorption, separation, and catalytic processes. Molecular simulations are commonly used to predict adsorption properti…
Influence of Ultramicroporosity and Surface Chemistry on Dynamic CO2 Capture in Activated Carbons
S. Gooijer, P. Goosen, C. G. Díaz-Maroto +4
Activated carbons are promising adsorbents for post-combustion CO2 capture due to their high surface area, tunable microporosity, and resistance to moisture and flue-gas impurities…
Enhancing Direct Air Capture through Potassium Carbonate Doping of Activated Carbons
N. van Dongen, A. J. F. van Hoof, S. Calero +1
Direct air capture of carbon dioxide (CO) is one of the most promising strategies to mitigate rising atmospheric CO levels. Among various techniques, adsorption using porou…
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…
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…