Inverse design of molecules and reactions
The project aims to fundamentally change how molecules and materials are discovered by inverse design. This new design paradigm could drastically reduce the 15-20 years from scientific breakthrough to application for molecules and materials, helping to address urgent challenges like renewable energy and sustainable chemical production.
In inverse design you first specify the desired properties of a molecule and then optimize for these properties using machine learning and computer simulations. The most promising candidates could then be investigated experimentally. I will first develop inverse design platforms for molecules and reactions based on machine learning and genetic algorithms (year 1). These inverse design platforms will then be applied in finding novel Baird-aromatic molecules (year 2), as well as reagents and catalysts for valuable chemical reactions (year 2 and 3). Successful completion of the project would in the long term contribute towards future artificially intelligent automated design platforms where experiments and computations work in synergy to accelerate discovery. It would also investigate the potential of artificial intelligence to discover qualitative chemical reactivity principles and explore promising main group catalysts with potential to complement or replace today´s transition metal catalysts. In the short term, the project could discover molecules with potential application in organic electronics, chemical biology and materials science.
Kjell Jorner (contact)
Post doc at Chalmers, Chemistry and Chemical Engineering, Chemistry and Biochemistry
Swedish Research Council (VR)
Project ID: 2020-00314
Funding Chalmers participation during 2021–2023