George E. Froudakis

University of Crete — Greece

Chemistry · Physical Sciences

52h-index11.7kcitations237works8.22yr avg
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Research Topics

Metal-Organic Frameworks: Synthesis and Applications(75), Graphene research and applications(44), X-ray Diffraction in Crystallography(37), Advanced Chemical Physics Studies(31), Carbon Nanotubes in Composites(31)

Publications237 total

RetNeXt: A Pretrained Model for Transfer Learning Across the MOF Adsorption Space
Journal of Chemical Information and Modeling·2026Open Access
Assembly of Face Decorated Cuboidal Cages into Ultraporous Structures with Hierarchical Porosity: Accessing MOFs with the Awaited <b>red-a</b> Topology
Journal of the American Chemical Society·2025Open Access
Accelerating materials discovery for water crisis: Multi-objective machine learning for atmospheric water harvesting by MOFs
2025· 1 citedOpen Access
Assembly of Face Decorated Cuboidal Cages into Ultraporous Structures with Hierarchical Porosity: Accessing MOFs with the Awaited red-a Topology
2025
Artificial Intelligence Paradigms for Next-Generation Metal–Organic Framework Research
Journal of the American Chemical Society·2025· 16 citedOpen Access
Author response for "Multiscale computational insights into 5-Fluorouracil delivery via Zeolite Imidazole Frameworks (ZIFs)"
2025
Multiscale computational insights into 5-fluorouracil delivery <i>via</i> zeolite imidazole frameworks (ZIFs)
RSC Pharmaceutics·2025Open Access
Computational investigation of the potential of a zinc-based metal–organic framework as a quercetin and 5-fluorouracil anticancer drug carrier
New Journal of Chemistry·2025· 1 cited
Efficient Gas Adsorption in <b>MUT-11</b>: Insights from Theoretical Calculations and GCMC Simulations
Crystal Growth & Design·2024· 2 cited
Gas adsorption meets geometric deep learning: points, set and match
Scientific Reports·2024· 4 citedOpen Access
MOFSynth: A Computational Tool toward Synthetic Likelihood Predictions of MOFs
Journal of Chemical Information and Modeling·2024· 8 citedOpen Access
Predicting and optimizing CO2 foam performance for enhanced oil recovery: A machine learning approach to foam formulation focusing on apparent viscosity and interfacial tension
Marine and Petroleum Geology·2024· 8 cited
Chemically Tailored Metal‐Organic Frameworks for Enhanced Capture of Short‐ and Long‐Chain Per‐ and Polyfluoroalkyl Substances from Water
Advanced Functional Materials·2024· 47 citedOpen Access
Machine learning prediction and optimization of CO2 foam performance for enhanced oil recovery and carbon sequestration: Effect of surfactant type and operating conditions
Geoenergy Science and Engineering·2024· 6 cited
Nanoporous Metal–Organic Framework Based on Furan-2,5-Dicarboxylic Acid with High Potential in Selective Adsorption and Separation of Gas Mixtures
Crystal Growth & Design·2024· 21 cited
Tailoring ammonia capture in MOFs and COFs: A multi‐scale and machine learning comprehensive investigation of functional group modification
ChemPhysChem·2024· 9 cited
Gas adsorption meets deep learning: voxelizing the potential energy surface of metal-organic frameworks
Scientific Reports·2024· 17 citedOpen Access
Comparison of machine learning approaches for the identification of top-performing materials for hydrogen storage
Sustainable Chemistry for the Environment·2023· 4 citedOpen Access
CCDC 2216495: Experimental Crystal Structure Determination
The Cambridge Structural Database·2023Open Access
Comparison of Energy-Based Machine Learning Descriptors for Gas Adsorption
The Journal of Physical Chemistry C·2023· 12 cited
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Frequent Co-authors

Emmanuel Tylianakis(16), Emmanuel Klontzas(15), Madhu Menon(8), Antonis N. Andriotis(8), Andreas Mavrandonakis(7), Giannis Mpourmpakis(5), George S. Fanourgakis(5), George Psofogiannakis(5), Michael Hirscher(4), Darren P. Broom(4), C. J. Webb(4), Pantelis N. Trikalitis(4), Max Mühlhäuser(3), Theodore Steriotis(3), Konstantinos Gkagkas(3), Wim Klopper(2), Ioannis Spanopoulos(2), Katherine E. Hurst(2), A. K. Stubos(2), Marianna Kotzabasaki(2)