BIG-MAP – Designing a European platform for the study of standardised and new batteries
BIG-MAP's Advanced Characterisation Work Package (WP5) is responsible for the creation of a European multi-modal, multi-technique platform enabling the investigation of standardised and novel batteries, using coordinated, state-of-the-art experimental techniques both in laboratories and at large-scale facilities (using X-rays and Neutrons).
In this context, the ILL, ESRF and CEA recently organised on 14 June 2023 a two-day joint workshop at the EPN campus in Grenoble, France.
Bringing together BIG-MAP characterization experts from ten EU academic laboratories, the meeting provided every participant with an opportunity to report on their results - based on an ambitious planned workflow of experiments run with a selected battery chemistry.
The exchanges led to discuss ongoing and future collaborations concerning one of the project's Key Demonstrators for data acquisition and analysis.
Two specific, data-oriented sessions were also organised to guide BIG-MAP users towards the best practices for data analysis:
- hands-on training for XPS data analysis - including a round-robin overview to establish normalized analytical protocols,
- general data analysis - highlighting methodologies for big data handling and data fairness, with a highly relevant presentation from V. Favre-Nicolin (ESRF).
(png - 726 Ki)BIG-MAP partners discussing during the hands-on training for XPS data analysis
(jpg - 213 Ki)Presentation on big data handling and data FAIRness at the ESRF
The BIG-MAP project (Battery Interface Genome - Materials Acceleration Platform), as part of the European Battery 2030+ initiative, aims to revolutionise next generation battery innovation whilst greatly accelerating R&D capabilities.
This groundbreaking partnership consisting of over 30 leading European academic, industrial and research partners - leveraging in a coordinated and holistic environment:
- material expertise,
- AI orchestration,
- automated robotics for rapid material synthesis and testing,
- high performance computing,
- machine learning and
- advanced characterization techniques
(jpg - 772 Ki)From left to right: Federico Capone (CNRS), Jack Flowers (KIT), Lucia Pérez Ramírez (Soleil), Alexandre Ponrouch (CSIC-ICMAB), Sandrine Lyonnard (CEA), Lukas Helfen (ILL), Didier Blanchard (ESRF), Cinthya Herrera (ILL), François Cadiou (ESRF), Stefan Fuchs (KIT), Andy Naylor (Uppsala University), Poul Norby (Technical University of Denmark), Quentin Jacquet (CEA)
(jpg - 607 Ki)Top left: Alexandre Ponrouch (CSIC-ICMAB), top right: Cinthya Herrera (ILL), bottom left: Robeto Fantin (CEA-Liten), , bottom right: Anass Beyanad (CEA-Liten)
Also in presence of Shatakshi SAXENA (CEA-Liten), Thanh Loan LAI (CEA-Liten) and Aleksandar Matic (Chalmers University of Technology).
Strengthening and extending synergies with other BIG-MAP Work Packages was also a fundamental objective of the workshop. This was achieved through the participation of scientists representing:
- the AI materials and discovery WP - specifically on the topics of high-throughput data handling and analysis, and
- the Ontology WP - who provided concrete demonstrations applied to characterization activities.
AI materials and discovery WP contribution on high-throughput data analysis
Making your data FAIR. Hands-on session on ontologization of data by the Ontology WP.