BIG-MAP
Financiado
Battery Interface Genome Materials Acceleration Platform
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 soluti...
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.
ver más
Duración del proyecto: 44 meses
Fecha Inicio: 2020-06-22
Fecha Fin: 2024-02-29
Fecha Fin: 2024-02-29
Línea de financiación: concedida
El organismo H2020 notifico la concesión del proyecto el día 2024-02-29
Línea de financiación objetivo
El proyecto se financió a través de la siguiente ayuda:
Presupuesto
El presupuesto total del proyecto asciende a
20M€
Líder del proyecto
DANMARKS TEKNISKE UNIVERSITET
No se ha especificado una descripción o un objeto social para esta compañía.
Perfil tecnológico
TRL
4-5
Perfil tecnológico
TRL
4-5
859.83K€ |
Participante
N.D. |
Participante