Project description
Unleashing the potential of metal carbonitrides
Metal carbonitrides – compounds combining earth-abundant metals with carbon and nitrogen – display remarkable mechanical, electronic, catalytic and superconducting properties with potential applications across clean energy, catalysis and quantum technologies. They have remained under-explored due to the cost and time of using conventional density functional theory (DFT) methods to explore this vast chemical space systematically. With the support of the Marie Skłodowska-Curie Actions programme, the CarMeN project aims to achieve near-DFT accuracy at a fraction of the computational cost. Machine-learned potentials based on high-quality DFT data will be combined with crystal structure prediction to enable systematic mapping of stable and metastable metal carbonitride compounds with desirable properties. Predicted candidates will be validated for their experimental feasibility.
Objective
The CarMeN (Carbonitride Metal Navigator) project aims to revolutionize the discovery of functional materials by combining machine learning (ML) with crystal structure prediction (CSP) to accelerate exploration of the vast and underexplored space of metal carbonitrides (MCNs). MCNs, composed of earth-abundant metals with carbon and nitrogen, exhibit exceptional mechanical, electronic, catalytic, and superconducting properties, making them highly relevant for sustainable energy, catalysis, quantum technologies, and advanced manufacturing. Despite this promise, only a small fraction of MCN compounds has been studied due to the limitations of conventional density functional theory (DFT) methods.
The project overcomes these bottlenecks by developing machine-learned potentials (MLPs) trained on high-quality DFT data, achieving near-DFT accuracy at orders-of-magnitude lower cost. These MLPs will enable high-throughput CSP, systematically mapping stable and metastable MCN phases while incorporating multi-objective optimization to identify compounds with technologically desirable properties. Predicted structures will be rigorously validated through phonon stability checks, property calculations (mechanical, electronic, catalytic, and energetic), and synthetic pathway analysis, ensuring experimental feasibility.
The methodology is structured across five work packages: (i) project and data management under FAIR principles, (ii) MLP development, (iii) ML-accelerated CSP, (iv) property evaluation and synthesis-informed validation, and (v) dissemination and open science practices. By uniting interdisciplinary advances in machine learning, computational chemistry, and materials science, CarMeN will establish a scalable discovery paradigm that bridges theoretical prediction and practical application. Ultimately, the project seeks to deliver sustainable, high-performance materials while advancing open, reproducible practices in computational materials research.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been human-validated.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
This project's classification has been human-validated.
- natural sciences physical sciences quantum physics
- natural sciences physical sciences atomic physics
- natural sciences computer and information sciences computational science
- natural sciences chemical sciences catalysis
- natural sciences computer and information sciences artificial intelligence machine learning
Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.2 - Marie Skłodowska-Curie Actions (MSCA)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-TMA-MSCA-PF-EF - HORIZON TMA MSCA Postdoctoral Fellowships - European Fellowships
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) HORIZON-MSCA-2025-PF
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Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.
86034 POITIERS CEDEX
France
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.