Summary
Today, energy production and transport are evolving fast to meet challenging environmental targets and growing demand. The Achilles’ heel is energy storage, which is incapable of providing both low cost and high-performance solutions. The answer is not a simple evolution of existing batteries but disruptive technologies that must be discovered fast.
The BIG-MAP vision is to develop a modular, closed-loop infrastructure and methodology to bridge physical insights and data-driven approaches to accelerate the discovery of sustainable battery chemistries and technologies. BIG-MAP’s strategy is to cohesively integrate machine learning, computer simulations and AI-orchestrated experiments and synthesis to accelerate battery materials discovery and optimization. The project will be a lever to create the infrastructural backbone of a versatile and chemistry-neutral European Materials Acceleration Platform, capable of reaching a 10-fold increase in the rate of discovery of novel battery materials and interfaces.
To succeed in this unprecedented international initiative, the BIG-MAP consortium covers the entire battery discovery value chain from atoms to battery cells, totaling 34 partners from 15 countries and spanning world-leading academic experts, research laboratories and industry leaders. The consortium is a joint European battery community effort, and the large-scale European Research Initiative BATTERY 2030+ stands united behind the BIG-MAP consortium. In addition to 13 core partners from BATTERY 2030+, the BIG-MAP consortium includes 21 leading European partners with complementary battery skills and essential competences from critical research areas such as quantum machine learning, deep learning and autonomous synthesis robotics. All partners will work to create an innovative methodology relying on unique competences and cross-cutting initiatives to deliver a shared infrastructure and 12 key demonstrators to showcase the value of AI-orchestrated materials discovery.
The BIG-MAP vision is to develop a modular, closed-loop infrastructure and methodology to bridge physical insights and data-driven approaches to accelerate the discovery of sustainable battery chemistries and technologies. BIG-MAP’s strategy is to cohesively integrate machine learning, computer simulations and AI-orchestrated experiments and synthesis to accelerate battery materials discovery and optimization. The project will be a lever to create the infrastructural backbone of a versatile and chemistry-neutral European Materials Acceleration Platform, capable of reaching a 10-fold increase in the rate of discovery of novel battery materials and interfaces.
To succeed in this unprecedented international initiative, the BIG-MAP consortium covers the entire battery discovery value chain from atoms to battery cells, totaling 34 partners from 15 countries and spanning world-leading academic experts, research laboratories and industry leaders. The consortium is a joint European battery community effort, and the large-scale European Research Initiative BATTERY 2030+ stands united behind the BIG-MAP consortium. In addition to 13 core partners from BATTERY 2030+, the BIG-MAP consortium includes 21 leading European partners with complementary battery skills and essential competences from critical research areas such as quantum machine learning, deep learning and autonomous synthesis robotics. All partners will work to create an innovative methodology relying on unique competences and cross-cutting initiatives to deliver a shared infrastructure and 12 key demonstrators to showcase the value of AI-orchestrated materials discovery.
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More information & hyperlinks
| Web resources: | https://cordis.europa.eu/project/id/957189 |
| Start date: | 01-09-2020 |
| End date: | 29-02-2024 |
| Total budget - Public funding: | 19 997 812,50 Euro - 19 997 812,00 Euro |
Cordis data
Original description
Today, energy production and transport are evolving fast to meet challenging environmental targets and growing demand. The Achilles’ heel is energy storage, which is incapable of providing both low cost and high-performance solutions. The answer is not a simple evolution of existing batteries but disruptive technologies that must be discovered fast.The BIG-MAP vision is to develop a modular, closed-loop infrastructure and methodology to bridge physical insights and data-driven approaches to accelerate the discovery of sustainable battery chemistries and technologies. BIG-MAP’s strategy is to cohesively integrate machine learning, computer simulations and AI-orchestrated experiments and synthesis to accelerate battery materials discovery and optimization. The project will be a lever to create the infrastructural backbone of a versatile and chemistry-neutral European Materials Acceleration Platform, capable of reaching a 10-fold increase in the rate of discovery of novel battery materials and interfaces.
To succeed in this unprecedented international initiative, the BIG-MAP consortium covers the entire battery discovery value chain from atoms to battery cells, totaling 34 partners from 15 countries and spanning world-leading academic experts, research laboratories and industry leaders. The consortium is a joint European battery community effort, and the large-scale European Research Initiative BATTERY 2030+ stands united behind the BIG-MAP consortium. In addition to 13 core partners from BATTERY 2030+, the BIG-MAP consortium includes 21 leading European partners with complementary battery skills and essential competences from critical research areas such as quantum machine learning, deep learning and autonomous synthesis robotics. All partners will work to create an innovative methodology relying on unique competences and cross-cutting initiatives to deliver a shared infrastructure and 12 key demonstrators to showcase the value of AI-orchestrated materials discovery.
Status
SIGNEDCall topic
LC-BAT-12-2020Update Date
27-04-2024
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Organisations
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| DANMARKS TEKNISKE UNIVERSITET (Coördinator)
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| AGENCIA ESTATAL CONSEJO SUPERIOR DE INVESTIGACIONES CIENTIFICAS
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| BASF SE
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| CENTRE NATIONAL DE LA RECHERCHE SCIENTIFIQUE (CNRS)
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| CIDETEC
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| COMMISSARIAT A L ENERGIE ATOMIQUE ET AUX ENERGIES ALTERNATIVES (CEA)
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| CONSIGLIO NAZIONALE DELLE RICERCHE (CNR)
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| Chalmers University of Technology
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| DASSAULT SYSTEMES DEUTSCHLAND GMBH
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| ECOLE POLYTECHNIQUE FEDERALE DE LAUSANNE (EPFL)
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| ENERGY MATERIALS INDUSTRIAL RESEARCH INITIATIVE
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| EUROPEAN SYNCHROTRON RADIATION FACILITY
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| FORSCHUNGSZENTRUM JULICH GMBH (JUELICH)
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| FRAUNHOFER GESELLSCHAFT ZUR FOERDERUNG DER ANGEWANDTEN FORSCHUNG E.V.
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| INSTITUT MAX VON LAUE - PAUL LANGEVIN