CCC Gruppe
Computational Carbon Chemistry

Computational Carbon Chemistry (CCC)

! The CCC group moved to the University of Birmingham, UK. The group pages on this website are not updated since April 2024. Latest news and research are available on the group’s website.

The Computational Carbon Chemistry (CCC) group uses theoretical and computational chemistry, physics, and materials science in combination with chemical machine learning to explore and exploit diverse functional organic and hybrid materials. We are particularly interested in several classes of materials: graphene-based materials (GBMs), covalent-organic frameworks (COFs), and hyperbranched polymers (HBPs) – in the context of their applications in capture, storage, transport, and catalytic transformations of therapeutic molecules and environmental pollutants. Functional organic materials are central to our research efforts (1) to establish the role of topology in materials chemistry, (2) to predict emergent properties in molecule-material complexes from their individual components, and (3) to build reliable yet interpretable machine learning models of materials’ chemical properties. Specific projects in the group include:

  • (electro)chemistry of graphene-based materials in their applications as sensors and catalysts
  • metal- and covalent-organic frameworks for molecular storage and transport
  • stability and reactivity of open-shell N-heteropolycycles
  • new cathode materials for rechargeable batteries
  • development of molecular representations and similarity metrics

The group is part of the SFB1249 “N-Heteropolycycles as Functional Materials” and the SIMPLAIX strategic initiative on bridging scales from molecules to molecular materials by multiscale simulation and machine learning.

Check out our GitHub for in-house codes, data repositories, etc.

Follow us on Fediverse/Mastodon, Bluesky, or Twitter/X.

External funding sources:

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