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

Project Information

DAMOCLES

Grant agreement ID: 101108769

DOI

10.3030/101108769

Project closed

EC signature date 12 April 2023

Start date 1 September 2023

End date 31 August 2025

Funded under

• Marie Skłodowska-Curie Actions (MSCA)

Total cost

No data

EU contribution

€ 196 829,28

Coordinated by

AARHUS UNIVERSITET
Denmark

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Links to deliverables and publications from FP7 projects, as well as links to some specific result types such as dataset and software, are dynamically retrieved from OpenAIRE .

Deliverables

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.

Publications

Peer reviewed articles (8)

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

Author(s): Kareem Abdelmaqsoud, Muhammed Shuaibi, Adeesh Kolluru, Raffaele Cheula, John R. Kitchin
Published in: Catalysis Science & Technology, 2024, ISSN 2044-4761
Publisher: Royal Society of Chemistry
DOI: 10.1039/D4CY00615A

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

Author(s): Sigmund Jensen, Raffaele Cheula, Martin Hedevang, Mie Andersen, Jeppe V. Lauritsen
Published in: Angewandte Chemie International Edition, 2024, ISSN 1521-3773
Publisher: Wiley
DOI: 10.1002/anie.202405554

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

Author(s): Bjarne Kreitz; Gandhali Kogekar; Raffaele Cheula; Franklin Goldsmith
Published in: Journal of Catalysis, Issue 452, 2025, ISSN 1090-2694
Publisher: Elsevier
DOI: 10.26434/CHEMRXIV-2025-L7135

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

Author(s): Marius Juul Nielsen, Luuk H. E. Kempen, Julie de Neergaard Ravn, Raffaele Cheula, Mie Andersen
Published in: The Journal of Chemical Physics, Issue 163, 2025, ISSN 0021-9606
Publisher: AIP Publishing
DOI: 10.48550/ARXIV.2505.21428

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

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

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

Author(s): Raffaele Cheula, Thien An Michael Quoc Tran, and Mie Andersen
Published in: ACS Catalysis, Issue 14, 2024, ISSN 2155-5435
Publisher: 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

Author(s): Raffaele Cheula, Mie Andersen
Published in: ACS Catalysis, Issue 15, 2025, ISSN 2155-5435
Publisher: 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

Author(s): Gabriele Spanò, Matteo Ferri, Raffaele Cheula, Matteo Monai, Bert M. Weckhuysen, Matteo Maestri
Published in: ACS Catalysis, Issue 15, 2025, ISSN 2155-5435
Publisher: American Chemical Society (ACS)
DOI: 10.1021/ACSCATAL.4C08084