Coherent polarization transfer in chemically exchanging systems

Literature Information

Publication Date 2020-03-24
DOI 10.1039/C9CP06873B
Impact Factor 3.676
Authors

Andrey N. Pravdivtsev, Jan-Bernd Hövener


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Abstract

Signal Amplification by Reversible Exchange (SABRE) uses para-enriched dihydrogen, pH2, to boost the NMR signal by several orders of magnitude. Although the method was discovered more than a decade ago, the quest to optimize SABRE and to establish a complete description in silico is ever ongoing. The simulation of SABRE is exacerbated by a complex interplay of chemical exchange and coherent polarization transfer. Here, we compare two different simulation approaches, Markov chain Monte Carlo (MC) simulations and a modification of the Liouville von Neumann equation with superoperators of chemical exchange (SO). We apply these methods to simulate the fate of truncated and full, three and four spin-½ systems in two different experiments: continuous polarization at a constant or alternating B0 field. For all cases, MC and SO provided similar results, and previously reported experimental data were well reproduced. It appears that both methods are well suited to approach this matter, while SO was faster than MC by several orders of magnitude in the cases discussed.

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Physical Chemistry Chemical Physics

Physical Chemistry Chemical Physics
CiteScore: 5.5
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Physical Chemistry Chemical Physics (PCCP) is an international journal co-owned by 19 physical chemistry and physics societies from around the world. This journal publishes original, cutting-edge research in physical chemistry, chemical physics and biophysical chemistry. To be suitable for publication in PCCP, articles must include significant innovation and/or insight into physical chemistry; this is the most important criterion that reviewers and Editors will judge against when evaluating submissions. The journal has a broad scope and welcomes contributions spanning experiment, theory, computation and data science. Topical coverage includes spectroscopy, dynamics, kinetics, statistical mechanics, thermodynamics, electrochemistry, catalysis, surface science, quantum mechanics, quantum computing and machine learning. Interdisciplinary research areas such as polymers and soft matter, materials, nanoscience, energy, surfaces/interfaces, and biophysical chemistry are welcomed if they demonstrate significant innovation and/or insight into physical chemistry. Joined experimental/theoretical studies are particularly appreciated when complementary and based on up-to-date approaches.

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