Objective
PREDICTOR aims to establish a rapid, high-throughput method to identify and develop materials for electrochemical energy storage. This method will comprise:
• A modelling and simulation tool for the computational screening of organic chemicals based on their potential performance in energy storage systems.
• Automated chemical synthesis, electrolyte production and characterization methods, so that the chemicals identified in the screening step can be rapidly produced and tested for their suitability in energy storage applications.
• Artificial-intelligence-based self-optimization methods that allow experimental data from material characterization to be fed back into automated experimental methods to enable self-driving laboratory laboratory platforms and for modelling and simulation tools, improving their accuracy.
• Data management systems to standardize and store the data generated for further use in model validation and self-optimization procedures
This approach will allow the rapid identification, synthesis and characterization of materials within a coherent development chain, replacing conventional trial-and-error developments. It will exploit the synergies between several emerging markets (digital technologies, artificial intelligence, high-throughput experimentation, renewable energy storage), providing the recruited doctoral candidates (DCs) with a valuable interdisciplinary skill set. To validate the PREDICTOR system, the case study will be active materials and electrolytes for redox-flow batteries. Within the project, three demonstrator battery cells (TRL3-4) will be assembled and tested with the newly developed materials.
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.
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.
- natural sciences computer and information sciences artificial intelligence
- engineering and technology environmental engineering energy and fuels renewable energy
- natural sciences computer and information sciences software software applications simulation software
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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-DN - HORIZON TMA MSCA Doctoral Networks
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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-2023-DN-01
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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.
80686 Munchen
Germany
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Participants (7)
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2800 Kongens Lyngby
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1081 HV AMSTERDAM
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20014 Turku
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75794 Paris
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76131 Karlsruhe
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2355 Wiener Neudorf
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02150 Espoo
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Partners (15)
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8401 Winterthur
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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69123 Heidelberg
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95447 Bayreuth
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02138 Cambridge
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85579 NEUBIBERG
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2052 Sydney
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Participation ended
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2596 HR 's-Gravenhage (Den Haag)
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10825 Berlin
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52062 Aachen
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1012WX Amsterdam
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2311 EZ Leiden
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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9000 Gent
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80025 Amiens
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Partner organisations contribute to the implementation of the action, but do not sign the Grant Agreement.
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CB2 1TN CAMBRIDGE
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WC2H 9JQ LONDON
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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.
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.