AI-guided Materials Design & Synthesis

Integrating computational property prediction with in-house organic synthesis

AI-guided Materials Design & Synthesis

AI-guided Materials Design & Synthesis

Integrating computational property prediction with in-house organic synthesis.

We collaborate closely with research groups doing computational materials design and synthesis of new semiconductor materials. We also synthesize materials in house.

Model-to-Molecule Discovery DFT Molecular Dynamics Simulations

Key questions

  • How do we reliably bridge single-molecule quantum chemical predictions with complex thin-film morphology?
  • Can design algorithms lead to industrially and practically accessible chemical structures?

Recent highlights

Other research areas

Optical & Electronic Materials Properties

Probing excited state dynamics and charge transport in semiconductors

Materials Structure & Morphology

Resolving materials structures with atomic-resolution electron microscopy and x-ray scattering

Applications of Energy Materials

Converting solar energy into electricity and solar fuels

Interested in collaborating?

We welcome joint projects, student applications, and shared instrumentation requests.

Contact coordinator