BIG-MAP

Battery Interface Genome - Materials Acceleration Platform

Grant period2020-09-01 - 2024-02-29
Funding bodyEuropean Union
Call numberH2020-LC-BAT-2020-3
Grant number957189
IdentifierG:(EU-Grant)957189

Note: 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.
   

Recent Publications

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Blended Salt Electrolyte Design for Enhanced NMC811||Graphite Cell Performance
Small structures 5(4), 2300425 () [10.1002/sstr.202300425] OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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Conductivity experiments for electrolyte formulations and their automated analysis
Scientific data 10(1), 43 () [10.1038/s41597-023-01936-3] OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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Ionic conductivity, viscosity, and self-diffusion coefficients of novel imidazole salts for lithium-ion battery electrolytes
Journal of materials chemistry / A 11(25), 13483 - 13492 () [10.1039/D3TA01217D] OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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Mechanistic understanding of the correlation between structure and dynamics of liquid carbonate electrolytes: impact of polarization
Physical chemistry, chemical physics 25(30), 20350 - 20364 () [10.1039/D3CP01236K] Embargoed OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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Understanding Battery Interfaces by Combined Characterizationand Simulation Approaches: Challenges and Perspectives
Advanced energy materials 12(17), 2102687 () [10.1002/aenm.202102687] OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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Learning the laws of lithium-ion transport inelectrolytes using symbolic regression†
Digital discovery 1(4), 440-447 () [10.1039/D2DD00027J] OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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Data‐Driven Analysis of High‐Throughput Experiments on Liquid Battery Electrolyte Formulations: Unraveling the Impact of Composition on Conductivity**
Chemistry methods 2(9), e202200008 () [10.1002/cmtd.202200008] OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

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One‐Shot Active Learning for Globally Optimal Battery Electrolyte Conductivity**
Batteries & supercaps 5(10), e202200228 () [10.1002/batt.202200228] OpenAccess  Download fulltext Files BibTeX | EndNote: XML, Text | RIS

All known publications ...
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 Record created 2021-10-08, last modified 2023-08-25



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