Objective
A major challenge for the green transition is our inability to rationally design inorganic materials with tailor-made properties. This project will tackle this inability by transforming our understanding of chemical bonding in inorganic materials.
Understandable rules based on chemical bonds have greatly advanced chemistry but are missing for most material properties, severely limiting the rational design of materials. Until recently, quantum chemical bonding analysis of inorganic materials has only been carried out on a small scale, making it impossible to derive such rules using machine learning. In addition, quantum chemical bonding analysis primarily focuses on two-center bonds. However, multicenter bonds play a critical role in material properties: For example, multicenter bonds have been held responsible for the superhardness of boron-containing compounds and the unusual properties of phase-change materials. By significantly going beyond my recent results on two-center bonds predicting materials properties with simple machine-learning models, I propose to overcome these challenges. The overarching objective of MultiBonds is to derive understandable and universal rules based on chemical bonds for inorganic materials properties through large-scale quantum-chemical bonding analysis considering multicenter bonds. We will 1) develop and apply innovative automated quantum-chemical methods to compute, for the first time, multicenter bonding indicators on a large scale. The generated database will then be used for 2) developing novel predictive deep-learning models and 3) intuitive human-understandable rules for materials properties. As initial applications, we will focus on phase-change materials with low thermal conductivities, magnetic and hard materials, since their properties are known to be governed by multicenter bonds, and they have critical applications (e.g. as thermoelectrics and in the green transition of vehicles).
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
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Keywords
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Project’s keywords as indicated by the project coordinator. Not to be confused with the EuroSciVoc taxonomy (Fields of science)
Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
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HORIZON.1.1 - European Research Council (ERC)
MAIN PROGRAMME
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Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
HORIZON-ERC - HORIZON ERC Grants
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Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
(opens in new window) ERC-2024-STG
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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.
12205 Berlin
Germany
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.