SOURCE-LINKED INTELLIGENCE
Understanding and designing inorganic materials properties based on two- and multicenter bonds
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 sc
Read original source ↗ Open in workspace
- recordType
- award
- status
- SIGNED
- region
- EU
- value
- 1500000
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T03:21:21.440Z. This is not the publication date.