SOURCE-LINKED INTELLIGENCE
Shape and Topology as Descriptors of Chemical and Physical Properties in Functional Organic Materials
fundamental physical and chemical properties. These patterns comprise a universal chemical language. Numerous molecular representations exist, from strings in chemoinformatics to matrices in chemical machine learning. While these big data-oriented fingerprints generally reduce the dimensionality of atomic composition and connectivity, they do not capture the intricacies of shape and topology. In PATTERNCHEM, several families of functional organic materials – graphenes, covalent-organic frameworks, and hyperbranched polymers – will provide a unique foundation for developing application-oriented fingerprints of their topological and non-covalent interaction features. After elucidating diverse structural descriptors of atomistic arrangement, substitution patterns, and two- and three-dimensional shapes of these materials, we will establish a scheme for quantifying the propensity for non-covalent interactions and assessing host-guest complementarity. Using this scheme, chemical and physical performance indicators relevant to targeted applications (e.g., as sensors, filters, and nanocarrie
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- recordType
- award
- status
- TERMINATED
- region
- EU
- value
- 1492821
- unit
- EUR
Evidence & attribution
European Commission, CORDIS Horizon Europe project dataset. Metadata adapted.
License: CORDIS reuse policy
First collected: 2026-09-20T00:21:03.701Z. This is not the publication date.