Computationally Assisted Design of Polarizing Agents for Dynamic Nuclear Polarization Enhanced NMR: The AsymPol Family #DNPNMR

Published: Friday, 09 November 2018 - 16:00 UTC

Author:

Mentink-Vigier, Frédéric, Ildefonso Marin-Montesinos, Anil P. Jagtap, Thomas Halbritter, Johan van Tol, Sabine Hediger, Daniel Lee, Snorri Th. Sigurdsson, and Gaël De Paëpe. “Computationally Assisted Design of Polarizing Agents for Dynamic Nuclear Polarization Enhanced NMR: The AsymPol Family.” Journal of the American Chemical Society 140, no. 35 (September 5, 2018): 11013–19.

https://doi.org/10.1021/jacs.8b04911.

We introduce a new family of highly efficient polarizing agents for dynamic nuclear polarization (DNP)-enhanced nuclear magnetic resonance (NMR) applications, composed of asymmetric bis-nitroxides, in which a piperidine-based radical and a pyrrolinoxyl or a proxyl radical are linked together. The design of the AsymPol family was guided by the use of advanced simulations that allow computation of the impact of the radical structure on DNP efficiency. These simulations suggested the use of a relatively short linker with the intention to generate a sizable intramolecular electron dipolar coupling/J-exchange interaction, while avoiding parallel nitroxide orientations. The characteristics of AsymPol were further tuned, for instance with the addition of a conjugated carbon−carbon double bond in the 5-membered ring to improve the rigidity and provide a favorable relative orientation, the replacement of methyls by spirocyclohexanolyl groups to slow the electron spin relaxation, and the introduction of phosphate groups to yield highly water-soluble dopants. An in-depth experimental and theoretical study for two members of the family, AsymPol and AsymPolPOK, is presented here. We report substantial sensitivity gains at both 9.4 and 18.8 T. The robust efficiency of this new family is further demonstrated through high-resolution surface characterization of an important industrial catalyst using fast sample spinning at 18.8 T. This work highlights a new direction for polarizing agent design and the critical importance of computations in this process.