Design And Modeling of Oxide Catalysts by machine LEarning and atomistic Simulations

Informazioni relative al progetto

DAMOCLES

ID dell’accordo di sovvenzione: 101108769

DOI

10.3030/101108769

Progetto chiuso

Data della firma CE 12 Aprile 2023

Data di avvio 1 Settembre 2023

Data di completamento 31 Agosto 2025

Finanziato da

• Marie Skłodowska-Curie Actions (MSCA)

Costo totale

Nessun dato

Contributo UE

€ 196 829,28

Coordinato da

AARHUS UNIVERSITET
Denmark

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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

Documents, reports (1)

Communication, Dissemination & Exploitation Plan

The plan describes the planned measures to maximize the impact of the project, including the dissemination and exploitation measures that are planned, and the target group(s) addressed. Regarding communication measures and public engagement strategy, the aim is to inform and reach out to society and show the activities performed, and the use and the benefits the project will have for citizens.

Data Management Plan (1)

Data Management Plan

The Data Management Plan describes the data management life cycle for all data sets that will be collected, processed or generated by the action. It is a document describing what data will be collected, processed or generated and following what methodology and standards, whether and how this data will be shared and/or made open, and how it will be curated and preserved.

Pubblicazioni

Peer reviewed articles (8)

Investigating the error imbalance of large-scale machine learning potentials in catalysis

Autori: Kareem Abdelmaqsoud, Muhammed Shuaibi, Adeesh Kolluru, Raffaele Cheula, John R. Kitchin
Pubblicato in: Catalysis Science & Technology, 2024, ISSN 2044-4761
Editore: Royal Society of Chemistry
DOI: 10.1039/D4CY00615A

Role of Cu Oxide and Cu Adatoms in the Reactivity of CO2 on Cu(110)

Autori: Sigmund Jensen, Raffaele Cheula, Martin Hedevang, Mie Andersen, Jeppe V. Lauritsen
Pubblicato in: Angewandte Chemie International Edition, 2024, ISSN 1521-3773
Editore: Wiley
DOI: 10.1002/anie.202405554

Structure-Dependent Microkinetic Modeling of the CO2 Desorption with Surface Diffusion

Autori: Bjarne Kreitz; Gandhali Kogekar; Raffaele Cheula; Franklin Goldsmith
Pubblicato in: Journal of Catalysis, Numero 452, 2025, ISSN 1090-2694
Editore: Elsevier
DOI: 10.26434/CHEMRXIV-2025-L7135

Interpretable machine learned predictions of adsorption energies at the metal–oxide interface

Autori: Marius Juul Nielsen, Luuk H. E. Kempen, Julie de Neergaard Ravn, Raffaele Cheula, Mie Andersen
Pubblicato in: The Journal of Chemical Physics, Numero 163, 2025, ISSN 0021-9606
Editore: AIP Publishing
DOI: 10.48550/ARXIV.2505.21428

Accessing Numerical Energy Hessians with Graph Neural Network Potentials and Their Application in Heterogeneous Catalysis

Autori: Brook Wander; Joseph Musielewicz; Raffaele Cheula; John R. Kitchin
Pubblicato in: The Journal of Physical Chemistry C, Numero 129, 2025, ISSN 1932-7455
Editore: American Chemical Society (ACS)
DOI: 10.48550/ARXIV.2410.01650

Unraveling the Effect of Dopants in Zirconia-Based Catalysts for CO2 Hydrogenation to Methanol

Autori: Raffaele Cheula, Thien An Michael Quoc Tran, and Mie Andersen
Pubblicato in: ACS Catalysis, Numero 14, 2024, ISSN 2155-5435
Editore: ACS Publications
DOI: 10.48550/ARXIV.2505.00574

Transition States Energies from Machine Learning: An Application to Reverse Water–Gas Shift on Single-Atom Alloys

Autori: Raffaele Cheula, Mie Andersen
Pubblicato in: ACS Catalysis, Numero 15, 2025, ISSN 2155-5435
Editore: American Chemical Society (ACS)
DOI: 10.1021/ACSCATAL.5C02818

Deciphering Size and Shape Effects on the Structure Sensitivity of the CO₂ Methanation Reaction on Nickel

Autori: Gabriele Spanò, Matteo Ferri, Raffaele Cheula, Matteo Monai, Bert M. Weckhuysen, Matteo Maestri
Pubblicato in: ACS Catalysis, Numero 15, 2025, ISSN 2155-5435
Editore: American Chemical Society (ACS)
DOI: 10.1021/ACSCATAL.4C08084