Molecular Structure and Spectroscopy

A Nobel Prize (2013) was given to Martin Karplus, Michael Levitt and Ari Warshel for "the development of multiscale models for complex chemical systems".

Molecular properties in complex, non-periodic environments are an extremely important part of our life - in biochemistry, in liquid catalysis, in gas-phase catalytic processes, etc.

Current work in the group aims to connect to nuclear magnetic resonance spectroscopies and long-lived nuclear spin states in small molecules, together with the group of Thomas Theis at North Carolina Stare University.

The focus in our group is to make the accuracy of direct quantum-mechanical treatments available to predict the function of complex molecules  in "real" environments. This is a long-term challenge. In fact, there is more than one challenge.

First, there is the issue of length-, time-, and ensemble average scales for a proper statistical treatment based on quantum mechanical techniques (e.g., density functional theory).

Second, there is the issue of being "accurate enough". The fast, empirical multiscale models (force fields) that are so successfully developed by the community around Karplus, Levitt, Warshel and others cleary have their accuracy limits (they are, after all, empirical). However, a much more expensive "first-principles" approach should deserve its name to be worth the money.

We are therefore working to ensure this accuracy for specific systems for which accurate, reliable experimental reference data exist. Some important background work includes:

There is a host of interesting, societally relevant (even transformative) challenges where a first-principles based understanding of processes at the atomic scale may help guide the development of better macroscopic processes: In life sciences, in energy research, chemical catalysis etc.

The real value of "first-principles" approaches, where they become applicable, is that they promise a real, unbiased and predictive understanding beyond a phenomenologial description. With this understanding, a real, direct interaction with experiment to help focus and improve specific processes is possible. This is our long-term vision for the field.