Nuclear magnetic resonance (NMR) and the related method of magnetic resonance imaging (MRI) has important applications in chemistry and medicine respectively. In chemistry NMR provides molecular structure information and information of dynamics. From MRI, images of soft matter are obtained thus playing an important role in medical investigations. However, NMR/MRI are insensitive methods with weak signal at physiological temperatures, limiting studies to molecules
present at high concentration (for instance water if we want an MRI image).
Thus there is an interest in delivering molecules that can provide enhances signal, so called hyperpolarized molecules. Within this topic two main computational challenges are identified that are required for in depth understanding and development of applications, namely (i): how can quantum chemistry assist in providing detailed information of NMR relaxation processes and (ii): development of molecular dynamics models that with sufficient accuracy can model the slow processes, required to understand NMR relaxation in complex media. These are the challenges addressed in the proposal.
The first paper provide simulation-methods and the prediction of the time constant for a long lived spin state (LLS) and thus contributes to challenge (i). With this theoretical understanding of LLS, we can learn how to design molecules with LLS and thereby obtained a delivery vehicle for hyperpolarized molecules that in turn gives us improved MRI imaging or NMR results. A second paper address challenge (ii), and provides a simulation technique to, at sufficiently long lengths and timescales, compute the relaxation in biomembrane model systems. With these tools at hand the long-lived spin state can in future work be developed to play an important role in MRI imaging as well as materials research and thus benefit the society as a whole.
