Summary
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.
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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More information & hyperlinks
Web resources: | https://cordis.europa.eu/project/id/101104032 |
Start date: | 01-06-2023 |
End date: | 31-05-2026 |
Total budget - Public funding: | 4 996 340,00 Euro - 4 996 340,00 Euro |
Cordis data
Original description
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.
Status
SIGNEDCall topic
HORIZON-CL5-2022-D2-01-02Update Date
31-07-2023
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