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Artificial Intelligence Guided Develpment of Vanillin-based Flow Batteries

Project description

Renewable materials from lignocellulosic for flow batteries

The EU aims to transition to renewable energy grids, but faces challenges in achieving this goal, particularly meeting the need for scalable, secure, and sustainable electrical energy storage. This challenge is exacerbated by the dependence on critical raw materials sourced from politically unstable regions. The EU-funded VanillaFlow project will develop innovative methods for energy storage. This involves leveraging flow battery technology and integrating it with artificial intelligence and machine learning. The project’s vision includes the replacement of unsustainable and critical raw materials currently used in flow batteries, such as redox-active molecules and membranes, with renewable materials derived from starch and lignocellulosic sources that are readily available. VanillaFlow is poised to bolster European technological leadership by fostering collaboration across various fields.

Objective

The Grand Challenge ahead is to shift fossil-dominated centralized energy systems towards regenerative integrated multi-vector grids. This requires also sustainable electrical energy storage, including the related raw material supply, processes and systems. A real impact on economy, society and ecology is only created if materials, processes and products can be potentially transferred to large scale. This represents a particular challenge for mid to long term, systems-integrated energy storage, also because the EU strongly depends on critical raw materials from politically instable regions. In VanillaFlow, we develop radically new approaches for integrated energy storage which combine artificial intelligence (AI) and machine learning (ML) with flow battery technology to replace currently employed, non-sustainable, and critical raw materials (i.e. redox-active molecules, membranes) in flow batteries by readily-available renewable materials based on starch and lignocellulosics. VanillaFlow will use AI and ML techniques such as physics-informed modeling, causal discovery, and representation learning, and makes use of deep learning and symbolic regression. These approaches are used in designing redox active quinones, and to optimize their interplay with the other components of a battery on single and multi-cell level. The whole research will be guided by toxicology investigations to ensure that sustainable and inherently safe materials will be obtained in the project. Today, the innovation capacity of European scientists and industry in the area of renewable materials makes them already the leading global players in the field. VanillaFlow will further support the European technological leadership in the area by cross-fertilization of different fields (artificial intelligence, battery technology, pulp and paper, biotechnology, polymer technology, toxicity) while addressing needs of sustainable materials in mid to long term energy storage.

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HORIZON-EIC - HORIZON EIC Grants

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Call for proposal

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(opens in new window) HORIZON-EIC-2022-PATHFINDERCHALLENGES-01

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Coordinator

TECHNISCHE UNIVERSITAET GRAZ
Net EU contribution

Net EU financial contribution. The sum of money that the participant receives, deducted by the EU contribution to its linked third party. It considers the distribution of the EU financial contribution between direct beneficiaries of the project and other types of participants, like third-party participants.

€ 1 580 507,19
Address
RECHBAUERSTRASSE 12
8010 Graz
Austria

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Region
Südösterreich Steiermark Graz
Activity type
Higher or Secondary Education Establishments
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Total cost

The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.

€ 1 580 507,19

Participants (4)

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