Novel metal-organic framework adsorbents for efficient storage of hydrogen

Informazioni relative al progetto

MOST-H2

ID dell’accordo di sovvenzione: 101058547

DOI

10.3030/101058547

Data della firma CE 24 Maggio 2022

Data di avvio 1 Giugno 2022

Data di completamento 31 Maggio 2026

Finanziato da

• Digital, Industry and Space

Costo totale

€ 4 917 262,50

Contributo UE

€ 4 917 262,50

Coordinato da

"NATIONAL CENTER FOR SCIENTIFIC RESEARCH ""DEMOKRITOS"""
Greece

CORDIS fornisce collegamenti ai risultati finali pubblici e alle pubblicazioni dei progetti ORIZZONTE.

I link ai risultati e alle pubblicazioni dei progetti del 7° PQ, così come i link ad alcuni tipi di risultati specifici come dataset e software, sono recuperati dinamicamente da .OpenAIRE .

Risultati finali

Websites, patent fillings, videos etc. (2)

Promotional video

Promotional video - linked to T6.2

Promotional toolkit and website

Promotional toolkit and website - - linked to T6.2

Documents, reports (4)

Cradle-to-gate LCA and LCC of MOST-H2 MOFs: version 1

Cradle-to-gate LCA and LCC of MOST-H2 MOFs: version 1 - linked to T5.1

Cradle-to-gate LCA and LCC of MOST-H2 MOFs: version 3

Cradle-to-gate LCA and LCC of MOST-H2 MOFs: version 3 - linked to T5.1

Initial TEA on FCH trains H2 storage applications

Initial TEA on FCH trains H2 storage applications - linked to T5.2

Cradle-to-gate LCA and LCC of MOST-H2 MOFs: version 2

Cradle-to-gate LCA and LCC of MOST-H2 MOFs: version 2 - linked to T5.1

Pubblicazioni

Peer reviewed articles (9)

Gas adsorption meets deep learning: voxelizing the potential energy surface of metal-organic frameworks

Autori: Antonios P. Sarikas, Konstantinos Gkagkas, George E. Froudakis
Pubblicato in: Scientific Reports, Numero 14, 2024, ISSN 2045-2322
Editore: Springer Science and Business Media LLC
DOI: 10.1038/S41598-023-50309-8

Scientific Reports

Autori: A. P. Sarikas, K. Gkagkas, G. E. Froudakis
Pubblicato in: Scientific Reports, Numero 5, 2024, ISSN 2045-2322
Editore: Nature
DOI: 10.1038/s41598-023-50309-8

Gas adsorption meets geometric deep learning: points, set and match

Autori: Antonios P. Sarikas, Konstantinos Gkagkas, George E. Froudakis
Pubblicato in: Scientific Reports, Numero 14, 2024, ISSN 2045-2322
Editore: Springer Science and Business Media LLC
DOI: 10.1038/S41598-024-76319-8

Improved thermal management in HKUST-1 composites upon graphite flakes incorporation: Hydrogen adsorption properties

Autori: Farrando Pérez, Judit; Rodríguez-Castillo, María; Martinez-Escandell, Manuel; Monge, Miguel; Silvestre-Albero, Joaquín
Pubblicato in: International Journal of Hydrogen Energy, Numero 1, 2023, ISSN 1879-3487
Editore: Elsevier
DOI: 10.1016/J.IJHYDENE.2023.05.357

MOFSynth: A Computational Tool toward Synthetic Likelihood Predictions of MOFs

Autori: Charalampos G. Livas, Pantelis N. Trikalitis, George E. Froudakis
Pubblicato in: Journal of Chemical Information and Modeling, Numero 64, 2024, ISSN 1549-9596
Editore: American Chemical Society (ACS)
DOI: 10.1021/ACS.JCIM.4C01298

Expanding the Reticular Chemistry Building Block Library toward Highly Connected Nets: Ultraporous MOFs Based on 18-Connected Ternary, Trigonal Prismatic Superpolyhedra

Autori: K. G. Froudas, M. Vassaki, K. Papadopoulos, C. Tsangarakis, X. Chen, W. Shepard, D. Fairen-Jimenez, Ch. Tampaxis, G. Charalambopoulou, Th. A. Steriotis, P. N. Trikalitis
Pubblicato in: Journal of the American Chemical Society, Numero 6, 2024, ISSN 1520-5126
Editore: ACS Publications
DOI: 10.1021/jacs.3c12679

Aspects of Gas Storage: Confined Geometry Effects on the High-Pressure Adsorption Behavior of Supercritical Fluids

Autori: S. Eder, P. Guggenberger, T. Priamushko, F. Kleitz, M. Thommes*
Pubblicato in: Langmuir, Numero 4, 2024, ISSN 1520-5827
Editore: American Chemical Society
DOI: 10.1021/acs.langmuir.3c02841

Reticular Synthesis of Flexible Rare-Earth Metal-Organic Frameworks: Control of Structural Dynamics and Sorption Properties Through Ligand Functionalization

Autori: E. Loukopoulos, G. Angeli, C. Tsangarakis, E. Traka, K. Froudas, P. Trikalitis
Pubblicato in: Chemistry – A European Journal, 2023, ISSN 1521-3765
Editore: Wiley-VCH GmbH
DOI: 10.1002/chem.202302709

Comparison of machine learning approaches for the identification of top-performing materials for hydrogen storage

Autori: A. P. Sarikas a, G. S. Fanourgakis,K. Gkagkas, G. E. Froudakis
Pubblicato in: Sustainable Chemistry for the Environment, Numero 3, 2023, ISSN 2949-8392
Editore: Elsevier
DOI: 10.1016/j.scenv.2023.100056