Project description
AI-accelerated identification of stable wide-bandgap perovskites
Wide-bandgap perovskites are semiconductor materials with high-energy bandgaps. When used in tandem solar cells (layered with commercially available silicon cells), they enable more effective use of the solar spectrum to surpass standard efficiency limits. Long-term operation stability is a persistent challenge. With the support of the Marie Skłodowska-Curie Actions programme, the Perov-AccTEST project aims to address this by replacing traditional trial-and-error experimentation with a machine learning-guided framework. Targeted screening of diverse perovskite formulations will be supported by machine learning-assisted generation of composition-quality maps. The long-term stability of predicted compositions under intensified stress conditions will be assessed with high-throughput optical characterisation. The best candidate will be integrated into multi-junction perovskite-silicon solar cell prototypes.
Objective
The conversion of solar energy into electricity is critical for reducing carbon emissions and expanding renewable energy generation. Photovoltaic (PV) technologies offer a compelling solution for grid-connected and building-integrated applications. Among emerging materials, halide perovskites have shown exceptional promise for next-generation PV devices. In particular, wide bandgap halide perovskites, when integrated in tandem with commercially available silicon solar cells, are revolutionizing the solar industry. These multi-junction architectures enable significantly higher power conversion efficiencies by more effectively harvesting the solar spectrum.
However, the long-term operational stability of wide bandgap perovskites remains a key bottleneck in advancing perovskite–silicon tandem technologies. Traditional trial-and-error approaches to materials discovery are slow and labor-intensive, limiting progress. This project proposes a machine learning–guided closed-loop experimental framework to accelerate the identification of stable wide bandgap perovskite compositions. The workflow integrates robotic synthesis, high-throughput optical characterization, rapid data analysis, and predictive modeling to efficiently navigate complex multi-dimensional composition spaces.
In Phase I, a Materials Acceleration Platform (MAP) will be deployed to screen diverse perovskite formulations. Machine learning algorithms will generate composition–quality maps, enabling targeted exploration without exhaustive testing. In Phase II, an Accelerated Testing Platform (ATP) will be used to evaluate the long-term stability of ML-predicted compositions under intensified stress conditions. Multiple samples will be tested in a high throughput manner to identify robust candidates. The most stable composition will then be advanced for integration into multi-junction perovskite–silicon solar cell prototypes.
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.
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.
52428 JULICH
Germany
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.