Project description
On the hunt for the next generation flow battery composition
CompBat aims to take flow batteries to the next level, identifying new prospective molecules for their chemical composition. Tools will be developed to this end, using machine learning paired with a high-throughput screening method to enable large-scale automated testing. Targeted molecules are bio-inspired organic compounds, as well as derivatives of a specialty bulk-manufactured chemical. Sophisticated calculations will be deployed to obtain data on molecules and their properties. Based on the results, The EU-funded CompBat project will perform modelling of flow battery systems to allow for predictions on performance, and a cost estimation approach will be applied. Furthermore, the team will examine the possibility of using solid boosters to enhance battery capacity.
Objective
CompBat will focus on developing tools for discovery of new prospective candidates for next generation flow batteries, based on machine learning assisted high-throughput screening. Density functional theory calculations will be used to obtain data on solubilities and redox potentials of different molecules, and machine learning methods are used to develop high-throughput screening tools based on the obtained data. The results of the high-throughput screening are validated with experimental results. Target molecules will be bio-inspired organic compounds, as well as derivatives of the redox active specialty chemical already manufactured in bulk quantities.
Stability and reversibility of the molecules will also be investigated by DFT calculation, experimental investigations and machine learning methods, for a selected group of interesting molecules.
Numerical modelling of flow battery systems will be performed with finite element method, and with more general zero-dimensional models based on mass-transfer coefficients. The models will be verified experimentally, and the modelling will generate a data-set to allow prediction of the flow battery cell performance based on properties of the prospective candidates obtained from high-throughput screening. This data is used then to predict the flow battery system performance from the stack level modelling. Freely available cost estimation tools are then adapted to estimate the system performance also in terms of cost. This approach will allow prediction of the battery performance from molecular structure to cost.
Furthermore, the concept of using solid boosters to enhance the battery capacity will be investigated by developing models to simulate the performance of such a systems, and validating the models experimentally with the candidates already reported in the literature.
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: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: https://op.europa.eu/en/web/eu-vocabularies/euroscivoc.
- natural sciences chemical sciences electrochemistry electric batteries
- natural sciences chemical sciences organic chemistry
- natural sciences computer and information sciences artificial intelligence machine learning
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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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H2020-EU.3.3. - SOCIETAL CHALLENGES - Secure, clean and efficient energy
MAIN PROGRAMME
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H2020-EU.3.3.4. - A single, smart European electricity grid
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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.
RIA - Research and Innovation action
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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) H2020-LC-BAT-2019-2020
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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.
02150 Espoo
Finland
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.