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OPerando analyses and modelling of INterface dynamics and CHARGE transport in lithium-ion batteries

Project description

DEENESFRITPL

Improved analytical techniques could reveal charge transport phenomena in batteries at a nano level

Battery innovation is key in the evolution of new energy production and transport technologies. However, progress in the field is currently impeded by insufficient understanding of atomic-level processes occurring within the interfaces and interphases of batteries. The EU-funded OPINCHARGE project aims to develop a set of operando nanoanalytical techniques to understand such processes in unprecedented detail. The consortium, comprising 10 organisations from 7 countries, will pioneer different chemical and physical techniques. They will also integrate AI/machine learning to enhance data acquisition and analysis. Strong focus will be placed on data sharing – a critical aspect of the Battery Interface Genome – Materials Acceleration Platform (BIG-MAP).

Objective

Battery innovation has played a major role in the development of new energy production & transport technologies, becoming true enablers of a clean, affordable and secure energy economy. However, innovation is currently being hindered by the lack of understanding of the processes happening at atomic levels in the batteries' interfaces and interphases. Thus, the OPINCHARGE consortium aims to develop a set of effective operando nanoanalytical techniques and methodologies to understand the interfacial processes in batteries in unprecedented level of detail.

For this, 10 organizations from 7 different countries will work together, combining their expertise and infrastructure, to find new ways of addressing this challenge. This will be fostered through 3 main pillars of technique innovation: chemical-based, isotope-based, and physics-based. Consequently, main techniques to be addressed operando will be: X-ray scattering, enhanced Raman, STEM-EELS & EDX, FIB-SIMS, Neutron imaging, OEMS and NMR.

Parallelly, the consortium will integrate AI/Machine Learning support, in order to improve data acquisition and analysis, making the data crunching processes more efficient and meaningful. Likewise, data treatment and sharing are cornerstones of the project, as Open Science practices and scientific collaboration with the community are recognized by the consortium as key aspects of the BIG-MAP objectives of the Batteries partnership and 2030+ programmes.

With a 36 month duration, the project is divided in 7 work packages distributed among the partners according to their expertise, with LIST as leader of the consortium. Dissemination, exploitation and communication activities will allow to maximize the impact of the results and the outreach of these, by actively promoting the diffusion of the information derived from the activities of the project.

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Call for proposal

HORIZON-CL5-2022-D2-01

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Funding Scheme

HORIZON-RIA - HORIZON Research and Innovation Actions

Coordinator

LUXEMBOURG INSTITUTE OF SCIENCE AND TECHNOLOGY
Net EU contribution
€ 829 485,00
Address
5 AVENUE DES HAUTS FOURNEAUX
4362 Esch Sur Alzette
Luxembourg

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Region
Luxembourg Luxembourg Luxembourg
Activity type
Research Organisations
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Total cost
€ 829 485,00

Participants (9)

Partners (1)

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Last update: 28 June 2023

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Permalink: https://cordis.europa.eu/project/id/101104032

European Union, 2024