Category Archives: rapid melt

Rapid-melt DNP for multidimensional and heteronuclear high-field NMR experiments #DNPNMR

Meerten, S.G.J. van, G.E. Janssen, and A.P.M. Kentgens. “Rapid-Melt DNP for Multidimensional and Heteronuclear High-Field NMR Experiments.” Journal of Magnetic Resonance 310 (January 2020): 106656.

Low sensitivity is the main limitation of NMR for efficient chemical analysis of mass-limited samples. Hyperpolarization techniques such as Dynamic Nuclear Polarization (DNP) have greatly improved the efficiency of NMR experiments. In this manuscript, we demonstrate a 400 MHz rapid-melt DNP setup. With this setup it is possible to perform liquid-state NMR experiments with solid-state DNP enhancement at high magnetic field. Sample volumes of 100 nL in fused-silica capillaries are detected using a stripline microcoil. Due to the small heat capacity of these samples it is possible to melt them with relatively low relaxation losses. With this 400 MHz setup, proton enhancements of up to À175 have been obtained in the liquid-state. The probe is double tuned, so it can be used for heteronuclear DNP-NMR and since the sample composition does not change during the experiment, it is possible to perform signal averaging and multidimensional experiments. This type of rapid-melt DNP setup thus allows for most types of liquid-state NMR experiments to be combined with efficient solid-state DNP. This makes rapid-melt DNP an interesting method for high-throughput chemical analysis of mass-limited samples.

500-fold enhancement of in situ (13)C liquid state NMR using gyrotron-driven temperature-jump DNP #DNPNMR

Yoon, D., et al., 500-fold enhancement of in situ (13)C liquid state NMR using gyrotron-driven temperature-jump DNP. J Magn Reson, 2016. 270: p. 142-6.

A 550-fold increase in the liquid state (13)C NMR signal of a 50muL sample was obtained by first hyperpolarizing the sample at 20K using a gyrotron (260GHz), then, switching its frequency in order to apply 100W for 1.5s so as to melt the sample, finally, turning off the gyrotron to acquire the (13)C NMR signal. The sample stays in its NMR resonator, so the sequence can be repeated with rapid cooling as the entire cryostat stays cold. DNP and thawing of the sample are performed only by the switchable and tunable gyrotron without external devices. Rapid transition from DNP to thawing in one second time scale was necessary especially in order to enhance liquid (1)H NMR signal.

Solid Effect DNP in a Rapid-melt setup #DNPNMR

van Bentum, P.J.M., et al., Solid Effect DNP in a Rapid-melt setup. J. Magn. Reson., 2016. 263: p. 126-135.

Dynamic Nuclear Polarization (DNP) has become a key element in nuclear magnetic resonance (NMR). Recently, we developed a novel approach to DNP enhanced liquid-state NMR based on rapid melting of a solid hyperpolarized sample followed by ‘in situ’ liquid-state NMR detection. This method allows 1 H detection with fast cycling options for signal averaging. In nonpolar solvents, doped with BDPA radicals, proton enhancement factors were achieved of up to 400. A short recycling delay of about 5 s allows for a fast determination of the hyper-polarization dynamics as function of the microwave frequency and power. Here, we use the rapid melt dnp method to study the mechanisms for DNP in the solid phase in more detail. Solid Effect, Cross Effect, Solid Overhauser and Liquid-state (supercritical) Overhauser DNP enhancement can be observed in the same setup. In this paper, we concentrate on Solid Effect DNP observed with both homogeneous narrow line radicals such as BDPA and with wide line anisotropic nitroxide radicals such as TEMPOL. We find indications that BDPA protons play an important role in Solid Effect DNP with this radical. A simplified spin diffusion model for BDPA can give a semi-quantitative description of the enhancements as function of the microwave power and as function of the proton concentration in the solid solution. For aqueous frozen samples we observe a similar Solid Effect DNP enhancement, which is analyzed within the simplified spin diffusion model.

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