Solvent Exchange Module for LC-NMR Hyphenation Using Machine

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A solvent exchange module for LC-NMR hyphenation using machine vision-controlled droplet evaporation Jan-Willem Schoonen, Paul Vulto, Niels de Roo, John van Duynhoven, Heiko J. van der Linden, and Thomas Hankemeier Anal. Chem., Just Accepted Manuscript • DOI: 10.1021/ac401068j • Publication Date (Web): 16 May 2013 Downloaded from http://pubs.acs.org on June 1, 2013

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Analytical Chemistry

A solvent exchange module for LC-NMR hyphenation using machine vision-controlled droplet evaporation

Jan-Willem Schoonen † , Paul Vulto † , Niels de Roo §, John van Duynhoven § ‡ , Heiko van der Linden † , Thomas Hankemeier †

*

† Leiden/Amsterdam Center for Drug Research, Leiden University, Einsteinweg 55, 2333 CE, The Netherlands § Unilever R&D, Olivier van Noortlaan 120, 3133 AT, Vlaardingen, The Netherlands ‡ Laboratory of Biophysics and Wageningen NMR Centre, Dreijenlaan 3, 6703HA, Wageningen, The Netherlands ǂ Netherlands Metabolomics Centre, Einsteinweg 55, 2333 CL, The Netherlands

Solvent switch, evaporation, NMR interface, NMR, pendant droplet evaporation, machine vision, liquid chromatography NMR hyphenation, hyphenated NMR

ACS Paragon Plus Environment

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Abstract We report the use of pendant droplet evaporation for exchange of eluents for 1H Nuclear Magnetic Resonance (1H NMR) purposes. Analytes are fed and retained in 500 nL droplets, which are concentrated by evaporation and subsequently redissolved in deuterated solvent. Droplet size is monitored by Machine Vision (MV) and heating rates are adjusted concordingly to maintain a stable droplet volume. Evaporation control is independent of solvent properties and the setup handles feed rates up to 7 µL min-1. The interface is capable of exchanging up to 90% of solvent for deuterated solvent, with a good recovery and repeatability for tomato extracts (Solanum lycopersicum). The system was capable of handling both polar and nonpolar analytes in one run. Volatiles such as formate, acetate and lactate and the thermosensitive compound epigallocatechin gallate were recovered without significant losses. Ethanol and propionate were recovered with significant losses due to the formation of a minimum boiling azeotrope. The current setup is ideally suited for on- and off-line hyphenation of liquid chromatography and NMR, as it is comprehensive, fully automated and easy to operate.

Introduction Structural identification of compounds in complex mixtures is a recurrent problem in chemistry and the life sciences. In chemistry, molecular characterization is a requirement for understanding compound reactivity and stability. Furthermore, in the life sciences structural elucidation of biomolecules in formulations and biofluids is a prerequisite for understanding biological mechanisms of action1. For example, in the emerging field of metabolomics, the identification of metabolites has become a critical step2, 3. One major bottleneck in molecular identification in complex mixtures is to obtain sufficient molecular separation and enrichment to enable structural elucidation or confirmation by spectrometric and spectroscopic techniques. For


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unambiguous structural elucidation it is crucial to combine the complementary information provided by e.g. NMR and Mass Spectrometry (MS), especially if reference compounds are not available. Whereas effective LC-MS4,

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and GC-MS interfaces have been designed in the last

decades, the hyphenation of LC with NMR remains cumbersome6. The largest technical drawbacks are the inherent insensitivity of NMR7 and the large background signals produced by common LC eluents8. There is a long history of attempts to overcome these hurdles. On-flow LC-NMR applications were already described three decades ago, but found only limited use due to low sensitivity, high deuterated solvent consumption and

inefficient solvent signal

suppression techniques. The use of LC-NMR in the stopped-flow mode is more widespread, but this method typically compromises molecular separation. The introduction of small volume capillary-scale NMR flow probes7 has not been able to counteract all of these issues. A breakthrough has been the introduction of Solid Phase Extraction8-14 (SPE) or guard columns15, 16 for trapping and enriching compounds that are separated by conventional reverse phase LC. By using an automated LC-SPE interface8, 17, 18, compounds can be isolated from complex biological mixtures, enriched significantly, eluted in NMR compatible solvents and subsequently measured by NMR in either flow-through or off-line mode. The use of microcoils15, 19-21 and cryogenically cooled probes22 nowadays allows detection of compounds at sub-microgram levels. LC-SPENMR based identification approaches have been proven particularly powerful for identification of semi-polar metabolites23, which can be separated well using reverse-phase LC. However, the majority of SPE techniques are based on the use of octadecyl sorbent material which creates a bias towards semi-polar compounds. Conventional LC-SPE is therefore less suited for other, more polar, metabolite classes1, 24. Hence, there is a need for a more universal LC-NMR interface without the current limitations of the already existing LC-SPE solutions.


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In this paper we demonstrate the use of droplet evaporation for the exchange of eluents. An interface was developed in which a pendant droplet is evaporated in a controlled manner using a Machine Vision (MV) controlled feedback loop. Evaporation was chosen in order to address the handling of both polar and nonpolar analytes in one run. The droplets are easily restored in deuterated solvent to decrease NMR background signals. We assessed the reproducibility and recovery of the solvent-exchange interface for both polar and nonpolar metabolites. The performance of the evaporation setup was characterized by measuring 1H NMR signals for academic and biological samples containing volatile, thermosensitive, polar and nonpolar analytes.

Materials and methods Setup of the evaporation system The evaporation setup (Figure 1) consists of a Harvard pump (model 22) delivering a 5 µL min-1 flow of solvent through a fused silica capillary (length 70 cm, ID 100 µm, OD 365 µm) which is coupled to a stainless steel capillary (length 15 cm, ID 100 µm, OD 1.57 mm). A droplet emerges at the distal end of the capillary and is freely hanging, balanced by the equilibrium between upward capillary and downward gravitational forces. The width of the droplet was monitored by long distance microscope optics coupled to a CCD image sensor (Proximity Infinitube & Basler A601f). A proportional-integral-derivative (PID) control loop was programmed in LabVIEW, National Instruments, Austin, Texas, United States of America, version 10.0.1 (with Control Design & Simulation, Machine Vision and Mathematic modules installed) to continuously measure the droplet size and adjust the heating power of a tungsten heating coil which was positioned underneath the droplet. The heating coil had a length of 15 cm, a diameter of 135 µm and an electrical resistance of 40 Ohm m-1. The coil was placed


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approximately 3 mm underneath the droplet and was operated at 0 - 9 Volt with a maximum current of 2.16 A, corresponding to a maximum heating power of 19.4 Watt. The stainless steel capillary was mounted on an XYZ CNC-stage (Taig 3000 mill, Supertech EMC-xyz-GSBX driver) to dip droplets by z-translation into an Eppendorf tube containing 100 µL of deuterated solvent.

Figure 1 Eluent or a liquid sample is fed into a pendant droplet. A Machine Vision software platform controls the heating power to maintain the droplet at a constant volume. An NMR sample is prepared by dipping the droplet into a sample tube pre-filled with deuterated solvent.

Sample preparation To determine the analytical performance of the evaporation system, recoveries of volatile, thermosensitive, polar and nonpolar analytes present in tomato extracts and samples taken from in vitro colon models26 were assessed by quantitative 1H NMR. Tomato extracts were prepared by homogenizing mashed and peeled tomatoes (Solanum lycopersicum bought at Albert Heijn Supermarket, Vlaardingen, The Netherlands), diluting the obtained mixture 4 times with MilliQ water, and centrifuging the pulp for 60 min at 9000 rates per minute at 6 °C. The supernatant was


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diluted 2 times with MilliQ water and served as tomato sample extract used in the experiments. These samples were kindly provided by Unilever, Vlaardingen, The Netherlands. Evaporation and control samples were prepared in such a way that, under assumption of full recovery, they have equal concentrations. Samples for evaporation experiments were prepared by diluting the stock solution 10 times, evaporating 100 µL of this solution at a feed rate of 5 µL min-1, and transferring the droplets every two minutes into a 1.5 mL Eppendorf tube which was pre-filled with 90 µL deuterated solvent (deuterium oxide; 99.9 atom%, Sigma Aldrich Chemie, Steinheim, Germany) for a total of 10 times per run. When the evaporation run was completed, the deuterated solvent volume was raised to a total of 250 µL with deuterium oxide. The control samples were prepared by pipetting 10 µL stock solution into 90 µL deuterated solvent (deuterium oxide 99.9 atom%) and raising the volume to 250 µL with deuterium oxide. For the solvent exchange experiment, 225 µL of tomato stock extract was added to 25 µL D2O 90/10 (v/v) H2O/D2O in an Eppendorf tube and analyzed by NMR. Subsequently, 250 µL of the same sample solution was evaporated down to effectively 25 µL and restored in 225 µL D2O resulting in a solvent composition of 10/90 %v/v H2O/D2O. The processed samples were transported on dry ice to the Unilever NMR lab and were transferred to 3 mm NMR tubes using conventional glass Pasteur pipettes.

NMR data acquisition 1D 1H NMR spectra were recorded on a Bruker Avance III 600 MHz spectrometer, equipped with a 5-mm cryo-cooled probe head. The probe head was tuned to detect 1H resonances at 600.25 MHz. The internal probe head temperature was set to 300 K. The spectra were recorded with pre-saturation of the water resonance using a noesygppr1d pulse sequence RD-90°-ρ1-90°-


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ρmix-90°-FID (Bruker Biospin, Germany). Here, ρ1 is a 4 µs delay time, and ρmix is the mixing time (10 ms). Sixty four scans were collected in 64k data points with a relaxation delay of 30 seconds, an acquisition time of 3.63 seconds, a spectral width of 15.0 ppm (8993 Hz) and an offset of 2821 Hz (4.70 ppm). The data were processed in TopSpin software version 1.3.10 (Bruker BioSpin GmbH, Rheinstetten, Germany). An exponential window function was applied to the free induction decay (FID) with a line-broadening factor of 0.3 Hz prior to the Fourier transformation. Manual phase and baseline correction was applied to all NMR spectra.

Results and discussion Characterization of the evaporation system The droplet volume was determined by measuring the droplet width as a function of time at a calibrated liquid feed rate without any evaporation. The fit of this curve was used for dynamic determination of the droplet size. Figure 2A shows the droplet calibration curve in which the measured droplet width was plotted against the true droplet volume. The droplet volume and the droplet radius scale as a third power equation. Figure 2B shows the stability of the droplet volume at integer flow rate increments from 1 to 10 µL min-1, whereby heating power was increased with increasing flow speed to keep the droplet at a stable volume of 500 ± 20 nL. For flow rates above 8 µL min-1, the system could not maintain a stable droplet due to boiling effects. To stay well within system limits and to minimize experimental errors, subsequent 1H NMR experiments were performed with 5 µL min-1 flow rates and a preset droplet volume of 280 ± 11 nL.


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2A

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2B

Figure 2 Liquid volume feed is plotted against the droplet width without any evaporation, to allow the dynamic determination of the droplet volume (2A). The evaporation interface was capable of maintaining a stable droplet volume for liquid feeds up to 7 µL min-1 (2B). Recovery of analytes of biological sample Figure 3 shows the 1H NMR spectrum of a tomato extract (bottom black spectrum) that was ten times diluted in water, subsequently concentrated ten times by the evaporator system and redissolved in deuterated water. The sample contained primarily amino acids and sugars, in agreement with previous reports for whole tomato extracts27,

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. The 1H NMR spectrum was

compared with a non-diluted tomato extract that was directly dissolved in deuterated water (top red spectrum). The signals in both spectra are largely the same with respect to spectral position, size and shape. An exception was found for a peak in the evaporated sample at 4.4 ppm and in some cases for methanol, which appears with a higher signal intensity in the evaporated sample in comparison to the positive control. The latter can be explained by the fact that the setup was rinsed with methanol, giving rise to methanol residing in dead volume areas of the tubing connections. Pendant droplet evaporation offers the advantage that precipitation of compounds mostly is avoided, because the sample is not evaporated to dryness. However, if the sample concentration is relatively high, one may observe caramelization, boiling explosions and the


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formation of black particulates at the bottom of the droplet. Machine Vision technology enables the recognition of visual clues (e.g. droplet deformation, droplet discoloring and droplet width irregularities) which can be utilized to discard improper runs.

Figure 3 Comparison of 1H NMR spectra between a non-evaporated (top red spectrum) and a diluted (bottom black spectrum) tomato extract which was concentrated by the evaporator set-up. The analyte concentration and solvent composition were identical in both cases. Intra- and interday variability coefficients In order to investigate the reproducibility of the evaporator setup, we repeated the evaporation of a tomato extract three times per day for a total of seven days. The resulting intra- and interday variabilities and recovery yields based on the 1H NMR signal were determined for nine key tomato extract analytes (Table 1). The interday variability was acceptable and comparable to the intraday variability, indicating a good stability of the evaporation procedure. Recovery yields


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were generally around 100%, except for asparagine and lactate, which had a slightly higher (110%) and lower (93%) yield, respectively. The intra- and interday errors for the quantification of the two aforementioned analytes were relatively large, especially for asparagine, which may be an explanation for their deviating yields.

Table 1 Intra- and interday variability coefficients and recoveries for nine tomato metabolites

Sample

Positive control

mg/g

mg/g

Analyte

Intraday variability

Interday variability

C.V. %

C.V. %

n=3

n=7

Recovery

%

Glucose

2.91

2.90

3.8

4.9

100

Fructose

1.31

1.33

4.3

5.3

99

Glutamate

7.02 10-1

6.86 10-1

7.0

6.7

102

Pyroglutamate

7.30 10-1

7.26 10-1

7.7

7.8

101

4-aminobutyrate

2.32 10-1

2.29 10-1

8.1

8.5

101

Asparagine

1.63 10-1

1.48 10-1

24.1

22.9

110

Alanine

6.69 10-2

6.78 10-2

7.1

6.6

99

Lactate

5.21 10-2

5.59 10-2

9.2

11.0

93

Choline

1.91 10-2

1.86 10-2

8.7

10.3

100

Solvent exchange capability The interface can be used to evaporate solvent and transfer droplet residues in another solvent. Figure 4 demonstrates the benefit of the increased deuterated solvent proportion on the NMR spectrum of a tomato extract. The top 1H NMR spectrum (top red spectrum) is a control sample containing a 225 µL tomato stock solution and 25 µL D2O. The 1H NMR spectrum (bottom blue


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line) corresponds to the evaporated sample, where the previously described solution was evaporated down to 25 µL and subsequently restored in D2O. A solvent exchange from a 10% to 90% D2O solvent proportion was realized. Although water-peak suppression was applied, the non-evaporated sample still showed a disturbing water peak in the NMR spectrum, which could not be observed in such an extent for the evaporated sample. The β-glucose signal near 4.6 ppm for the non-evaporated sample was therefore more difficult to quantify than the same signal of the evaporated sample. In this experiment the deuterated exchange solvent was chemically identical to the protonated starting solvent, however, the sample droplets also could have been redissolved in any other suitable deuterated solvent.

Figure 4 The effect of an increase of the deuterated solvent content on an 1H NMR spectrum of tomato extract containing primarily sugars: sample in 10% D2O (top red spectrum) and sample which was evaporated and solvent exchanged to 90% D2O (bottom blue spectrum). The analyte concentrations were identical in both cases. Recovery of volatiles and thermosensitive compounds The interface was designed to prevent evaporation to dryness to minimize loss of volatile compounds and degradation of thermosensitive compounds. Recovery of volatile compounds was determined in samples taken from in vitro colon models29 containing high levels of short


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chain fatty acids such a propionate and butyrate. To assess possible losses caused by degradation, epigallocatechin gallate (EGCG) was taken as an example of compounds being prone to oxidative degradation at elevated temperatures. Table 2 shows the recovery of volatile and thermosensitive compounds after evaporation. Formate, acetate, lactate, ethanol and propionate are all compounds having boiling points in the same order of magnitude as the solvent (water). Satisfactory recoveries were obtained for the volatiles acetate and formate, while recoveries for ethanol and propionate were low (22% and 59%, respectively). The low recovery for ethanol can be explained by its high vapor pressure and the lowered boiling point caused by the formation of a water azeotrope. Although propionate has a higher boiling point than ethanol, it is possible that the lower recovery is attributable to the water azeotrope, lowering the boiling point by approximately 41 °C from 141°C to 100°C. The recovery of 92% for the thermosensitive test compound EGCG was satisfying and suggests that no significant degradation has taken place.. For unknown samples, the approach comprises a degree of uncertainty as volatile compounds can form a minimum boiling azeotrope. However, this may be resolved retrospectively using a calibration curve.

Table 2 Recovery rates after evaporation of aqueous samples of several volatiles and a thermosensitive compound in relation to vapor pressure, boiling point and azeotropic composition30, 31

Sample

St. dev.

mg/g

mg/g

Vapor RSD pressure (25 ºC) %

kPa

Boiling point

ºC

Boiling point of azeotrop e

Azeotropic composition

ºC

% H2O

Recover y

%


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Formate

8.13 10-3

1.62 10-3

20

5.68

101

108

22

121

Acetate

6.15 10-2

3.24 10-3

5

2.08

118

*No

*No

88

Lactate

2.35 10-1

3.60 10-3

2

n.a.

228

*1

*1

121

Ethanol

1.91 10-2

1.80 10-3

9

7.92

78

78

5

22

Propionate

1.68 10-2

9.92 10-4

6

1.75

141

100

82

59

Alanine

1.50 10-1

4.28 10-3

3

n.a.

>300

*1

*1

114

Isoleucine

9.05 10-2

4.15 10-3

5

n.a.

>300

*1

*1

110

2.038

1.52 10-1

7

n.a.

>300

*1

*1

92

Epigallocate -chin gallate *No *1

no azeotrope formed with water no information on azeotrope provided

Discussion In this paper, we have shown the feasibility of controlled droplet evaporation as a means for solvent-exchange in LC-NMR hyphenation. We demonstrated that no information was lost upon evaporation of complex samples, such as whole tomato extract. Instead, distortive peaks through excessive presence of non-deuterated solvents could be strongly reduced. We assessed the limits of the method in terms of volatile components and thermo sensitive compounds and found that the system is rather robust with respect to these two classes. Also the system was shown to function independent of analyte properties such as polarity and charge. An efficient solvent exchange module for LC-NMR brings a number of crucial advantages to the field. Without solvent exchange module, the best results would be obtained by running the complete LC system on deuterated solvents. However, many LC solvents are not or hardly obtainable in its deuterated version. Particularly when working with gradients, it becomes highly advantageous to redissolve analytes in a single deuterated buffer. Lastly, since D-solvents are


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expensive, running a complete LC separation of D-solvents implies significant costs, particularly when working with large volume LC systems and systems using a solvent split. With the current efforts in downsizing NMR setups towards bench-top analyzers, it may well be expected that micro coils will become a standard. When dealing with micro NMR coils, purity and concentration is the limiting factor, while often the addition of D-solvent is not strictly required. Purity of sample can be enhanced with an a-priori LC fractionation, however this leads to dilution of the analyte plug. The droplet evaporator module that we present here can also function as a concentrator, rather than a solvent exchange module. In this paper we have shown that samples could be concentrated at least 10-fold. It can therefore be expected that the droplet evaporator will become a powerful addition in a surge toward bench-top LC NMR equipment. The major limitation of the current setup lies in the maximum flowrates that can be evaporated. In the current paper, a maximum flow rate up to 8 µL min-1 was achieved. For this flow rate and on-line coupling with NMR, the evaporation interface is compatible with microLC setups. For larger scale LC fractionation setups, an intermediate storage loop can be used to de-couple LC run times from evaporation speed capacity. Also we see ample opportunities for increasing the feed rate capacity of the setup. A straightforward improvement comprises the use of a hot air flow for faster evaporation. Also preheating the distal end of the evaporation feed capillary will increase evaporation capacity. A trade-off needs to be found between the speed of evaporation and the prerequisite to avoid boiling of the droplet. This implies that the droplet surface should be maximized, while droplet volume is minimized. An effective manner to increase evaporation surface is the parallel evaporation of multiple droplets. Clearly this puts significant demands on the control mechanism.


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In the setup proposed here, we make use of machine vision for process monitoring and control. Machine vision is highly advantageous over alternative techniques, such as based on refractive index, conductivity, capacity and mass. Machine vision renders monitoring independent of droplet constitution and therefore independent from solvent constitution. This becomes particularly important for gradient runs, but also in single buffer system as the evaporation process continuously changes the ratio between analyte and running buffer. Moreover, the machine vision interface enables to detect discontinuities in the process, such as crystal formation, dry-cooking and boiling effects.

Conclusions A unique setup for the exchange of solvents using a machine vision controlled pendant droplet evaporation was demonstrated. The setup was employed as a solvent exchange device for 1H NMR applications. The interface was capable of enriching the analyte up to 10-fold and changing the solvent composition from 0 to 90% deuterated solvent proportion. The system shows a good recovery of several tomato extract metabolites and the thermosensitive compound epigallocatechin gallate. Volatile organic acids such as formate, acetate and lactate could be efficiently recovered, while ethanol and propionate lead to significant losses in recovery. Nevertheless, the machine vision-controlled droplet evaporation seems suitable for handling a wide variety of both polar and nonpolar analytes. Therefore, LC-EV-NMR is a fully comprehensive, low-loss and fully automated alternative for LC-SPE-NMR techniques.

Corresponding Author *E-mail: [email protected]. Notes


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The authors declare no competing ﬁnancial interest. Acknowledgements This project was financed by The Netherlands Metabolomics Centre (NMC), which is part of The Netherlands Genomics Initiative/Netherlands Organization for Scientific Research (NWO). References (1) H. R. Tang, C. N. Xiao, Y. L. Wang, Magn Reson Chem, 2009, 47, S157-S162, Doi 10.1002/Mrc.2513 (2) S. Moco, R. J. Bino, R. C. H. De Vos, J. Vervoort, Trac-Trend Anal Chem, 2007, 26, 855-866, DOI 10.1016/j.trac.2007.08.003 (3) S. C. Zhang, G. A. N. Gowda, T. Ye, D. Raftery, Analyst, 2010, 135, 1490-1498, Doi 10.1039/C000091d (4) A. Medvedovici, Albu, F., David, V., J Liq Chromatogr R T, 2010, 33, 1255-1286, Doi 10.1080/10826076.2010.484375 (5) G. Theodoridis, Gika, H. G., Wilson, I. D., Mass Spectrom Rev, 2011, 30, 884-906, Doi 10.1002/Mas.20306 (6) I. D. Wilson, U. A. T. Brinkman, J Chromatogr A, 2003, 1000, 325-356, Doi 10.1016/S0021-9673(03)00504-1 (7) R. J. Lewis, M. A. Bernstein, S. J. Duncan, C. J. Sleigh, Magn Reson Chem, 2005, 43, 783-789, Doi 10.1002/Mrc.1614


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Solvent Exchange Module for LC-NMR Hyphenation Using Machine

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