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ab initio PRediction Of MaterIal SynthEsis

Project description

An open-source computational platform predicting if and how new materials can be made

Thanks to the power of computer simulations, materials scientists can now search very large databases for theoretical materials with specific properties. The usefulness of these databases is hindered by the fact that we do not know whether these materials can actually be made. The ERC-funded PROMISE project plans to develop the software necessary to predict if and how a material can be made. Its computational methods will integrate crystal structure prediction, advanced statistical sampling, and state-of-the-art machine learning techniques in a generic open-source platform. It will not only predict which materials can be produced but also shed light on the physical processes leading to the formation of the materials.

Objective

ab initio simulation techniques have evolved to the point that we can reliably predict many properties of materials before they have been synthesized. This paradigmatic change has led to databases that contain millions of theoretically predicted materials with desirable attributes. However, all this information is of little use if we cannot predict if these novel materials can be made at all. I will develop a framework based on first-principles computer simulations to predict if and how a material can be made. The proposed approach will boost the success rate of “materials by design”, expedite experiments to create novel materials, and thus greatly enhance the speed of materials discovery. To achieve this goal, computational methods that combine crystal structure prediction, advanced statistical sampling, and state-ofthe- art machine learning techniques will be designed. The whole framework will be benchmarked on model systems with known properties. The resulting software will be made generic and open-source. The computational framework will be used to gain mechanistic insight into the physical processes that control the formation of specific functional materials including high-pressure phases of matter, perovskites, and molecular crystals.

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Call for proposal

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(opens in new window) ERC-2023-STG

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Host institution

INSTITUTE OF SCIENCE AND TECHNOLOGY AUSTRIA
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.

€ 1 496 991,00
Address
Am Campus 1
3400 KLOSTERNEUBURG
Austria

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Region
Ostösterreich Niederösterreich Wiener Umland/Nordteil
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.

€ 1 496 991,00

Beneficiaries (1)

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