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FULLy integrated, autonomous & chemistry agnostic Materials Acceleration Platform for sustainable batteries

Project description

Accelerating the future of battery innovation

The slow pace of battery innovation has hindered efforts to address global carbon emissions, especially in transportation, energy, and industrial sectors. Traditional research methods, based on trial and error, typically result in long development cycles, often taking a decade to optimise new materials. This reliance on sequential processes impedes rapid progress in creating more efficient and sustainable batteries. To accelerate change, a more efficient approach to battery development is urgently needed. The EU-funded FULL-MAP project will create an advanced materials acceleration platform. Through automation, AI-driven modelling, and high-throughput testing, it will enable faster, smarter discovery of next-generation materials and interfaces, significantly advancing sustainable battery technology.

Objective

Battery technology emerges as a key solution for cutting carbon dioxide emissions across transportation, energy, and industrial sectors. Nonetheless, traditional research methods for developing new battery materials have typically depended on an Edisonian approach, characterised by trial and error, where each phase in the discovery value chain is sequentially reliant on the successful execution of preceding steps. Development and optimization of novel batteries is a process that spanned around a decade. To face this challenge, it is necessary to accelerate the discovery and optimization of next-generation batteries through the development of materials and interface acceleration platforms. The FULL-MAP project aims to revolutionize battery innovation by developing a materials acceleration platform that amplifies human capabilities and expedites the discovery of new materials and interfaces. This pivotal initiative focuses on automating laboratory operations and conducting fast, high-throughput experiments. It integrates AI and machine learning-accelerated multi-scale and multi-physics modeling, supporting intelligent decision-making. FULL-MAP's comprehensive, modular approach encompasses the inverse design of materials, autonomous orchestrated production via both traditional and novel synthesis routes, and extensive high-throughput characterization methods. These methods span ex-situ, in-situ, operando, on-line, and post-mortem analyses at various levels, from material to cell assembly and testing. It simulates the entire battery development process, from material design to battery testing, considering environmental and economic factors. By integrating computational and experimental methods with AI, Big Data, Autonomous Synthesis, and High-Throughput Testing, FULL-MAP aims to fast-track the development and deployment of next-generation materials and batteries, significantly advancing sustainable battery technology.

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Coordinator

VRIJE UNIVERSITEIT BRUSSEL
Net EU contribution
€ 2 465 000,00
Address
PLEINLAAN 2
1050 Bruxelles / Brussel
Belgium

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Region
Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest Région de Bruxelles-Capitale/ Brussels Hoofdstedelijk Gewest Arr. de Bruxelles-Capitale/Arr. Brussel-Hoofdstad
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 2 465 000,00

Participants (30)

Partners (1)