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Quantitative NMR spectroscopy for gas analysis for production of primary reference gas mixtures
Accepted Manuscript Quantitative NMR spectroscopy for gas analysis for production of primary reference gas mixtures K. Meyer, K. Rademann, U. Panne, M. Maiwald PII: DOI: Reference:
S1090-7807(16)30251-8 http://dx.doi.org/10.1016/j.jmr.2016.11.016 YJMRE 5996
To appear in:
Journal of Magnetic Resonance
Received Date: Revised Date: Accepted Date:
20 September 2016 24 November 2016 25 November 2016
Please cite this article as: K. Meyer, K. Rademann, U. Panne, M. Maiwald, Quantitative NMR spectroscopy for gas analysis for production of primary reference gas mixtures, Journal of Magnetic Resonance (2016), doi: http:// dx.doi.org/10.1016/j.jmr.2016.11.016
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Quantitative NMR spectroscopy for gas analysis for production of primary reference gas mixtures K. MEYER1; K. RADEMANN2; U. PANNE1,2; M. MAIWALD1 1
Bundesanstalt für Materialforschung und -prüfung (BAM), Richard-Willstätter-Straße 11, D-12489 Berlin, Germany 2
Department of Chemistry, Humboldt-Universität zu Berlin, Brook-Taylor-Str.2, D-12489 Berlin, Germany Abstract Due to its direct correlation to the number of spins within a sample quantitative NMR spectroscopy (qNMR) is a promising method with absolute comparison abilities in complex systems in technical, as well as metrological applications. Most of the samples studied with qNMR are in liquid state in diluted solutions, while gas-phase applications represent a rarely applied case. Commercially available NMR equipment was used for purity assessment of liquid and liquefied hydrocarbons serving as raw materials for production of primary reference gas standards. Additionally, gas-phase studies were performed within an online NMR flow probe, as well as in a high-pressure NMR setup to check feasibility as verification method for the composition of gas mixtures. Keywords Quantitative NMR spectroscopy, Gas-phase NMR spectroscopy, Purity assessment, Reference gas mixtures
1. Introduction In the last decades NMR spectroscopy has become a common method used in a variety of different applications in several fields of science and technology. Especially for research and development tasks it provides useful information on both identity and structure of chemical compounds. Most of the performed analysis aiming at identification and structure elucidation of natural, as well as synthetic chemical products. Besides these qualitative approaches, quantitative NMR spectroscopy (qNMR) becomes more and more popular, especially for determinations in complex systems when the application of other analytical methods, mainly chromatography, is complicated. The quantitative information obtained from qNMR is based on the proportionality of NMR signal with number of NMR active nuclei in the observed sample volume. This is comparable with a simple “counting of spins” and has the advantage of a direct calibration-free quantification, provided that the NMR experiment is performed quantitatively with regard to nuclear spin relaxation. Therefore, it represents an ideal reference method for acquisition of quantitative data, which can be used for the system-dependent calibration often required by other analytical techniques. In contrast to gravimetric reference data qNMR provides additional information on non-isolable compounds like transition states and intermediates over the course of a chemical reaction. This is very useful, especially in the field of process analytical technology and the development of online analytical methods for process monitoring and control applications [1]. 1
Most of all samples for NMR experiments are in the liquid state, mainly in diluted solutions using deuterated solvents for avoiding large solvent signals. However, process analytical applications usually take place in highly concentrated technical mixtures without any sample preparation [1, 2]. Besides liquid phase applications solid material is accessible with NMR spectroscopy by using special experiments and probe hardware like Magic-Angle-Spinning (MAS) technology [3]. On the other hand, gas phase applications represent a rarely applied case, mainly because of the low density of the samples when working at atmospheric pressure conditions. Therefore, sensitivity of NMR spectroscopy can be increased by application of pressure, which requires specialized pressureresistant NMR equipment [4]. While vessels made of non-magnetic metal alloys like beryllium copper allow very high pressure ratings [5], cell-based setups using sapphire and high-performance ceramics have the advantage of higher flexibility and shorter conversion times due to compatibility with regular NMR probes and equipment. Pioneer work in this field was done by Yamada utilizing glass cells that reach burst pressures of up to 290 MPa [6] and Roe developing a single crystal sapphire NMR tube with a pressure rating of up to 100 MPa [7]. This cell design was further improved by Horvath and Ponce [8], as well as Bai et al. [9]. Today, first commercial solutions for high-pressure NMR applications are available in the pressure range of up to 300 MPa [10]. Most of the gas phase applications published aim for confirmation of theoretical approaches concerning medium and solvent effects [11, 12], nuclear magnetic shielding, as well as relaxation mechanisms [13, 14, 15]. Additionally, kinetic studies on exchange processes, as well as gas phase reactions were reported by Suarez et al. [16] and Shtarov et al. [17] using 1H and 19F NMR spectroscopy. Another promising field is the combination of gas chromatography with NMR spectroscopy. First published from Buddrus and Herzog [18, 19] this application was further investigated and further developed by the research group of Albert [20, 21, 22, 23]. The abovementioned advantages of qNMR make it a promising technology to be used within metrological applications, e.g., for purity assessment or gas mixture composition analysis. According to the Joint Committee for Guides in Metrology (JCGM) metrology is defined as consideration of all theoretical and practical aspects of measurement, regardless of the measurement uncertainty or field of application [24]. A core concept in metrology is traceability, which implies that a result can be related through a documented chain of calibrations all contributing to measurement uncertainty. This is usually done based on the SI system, which ensures comparability between results obtained at different location and/or time. A global aim of metrological research is the traceability of all measurements to well-known fundamental relationships like velocity of light, replacing physical standards, which can suffer from changes over time even when stored under controlled conditions. As a designated institute (DI) the Bundesanstalt für Materialforschung und -prüfung (BAM) is responsible for the national gas standards in the sectors of energy gases and automotive exhaust gases. This task is part of legal gas metrology delegated from Physikalisch-Technische Bundesanstalt (PTB) as the national metrological institute (NMI) of Germany. It includes preparation of highaccuracy primary reference gas mixtures (PRG), as well as the development and improvement of advanced measurement capabilities. The production process of these PRG’s is based on a static gravimetric procedure with sequential fillings of single components or pre-manufactured mixtures according to the ISO standard 6142 within ISO/TC 158 “analysis of gases” [25]. The final PRG, which are traceable to SI by weight, are then used for certification of secondary gas standards manufactured by specialty gas distributors. Latter or related tertiary standards are then used for calibration of instruments within technical applications, in which traceability is required due to legal 2
or commercial regulatory affairs, e.g., the determination of heat of combustion of natural gas streams. For maintaining highest accuracy of the composition of the produced PRG a rigorous purity assessment of every single component used for production is essential. Especially crosscontaminations with different isomers of the higher hydrocarbons up to C 6 have to be considered during the preparation process. This is usually performed using gas chromatography (GC), which requires a calibration for each of the species to determine. Additionally, identification of unknown substances can be challenging depending on the available detectors and the handling of some of the components for GC is not feasible, especially when they are in the liquid state. In this work we evaluate and present a new method for purity assessment of components used for the production of PRG’s by using carbon-13 quantitative NMR. In contrast to GC, direct relative quantification of impurities, as well as identification of formerly unknown contaminants was possible. Pressure-resistant NMR tubes enabled the method to be used for analysis of components with a vapor pressure up to 1.5 MPa under liquefied conditions. Besides the determination of impurities in the liquid phase, quantitative NMR spectroscopy was applied in the gas phase up to a pressure of 3 MPa on different gas mixtures. In a first approach, an online NMR flow probe was utilized by using a valve setup combined with a high-pressure syringe pump for compression of the gas samples. Later, studies were performed within a commercially available high-pressure NMR tube made of zirconia providing a higher pressure rating and better pressure stability for conduction of long-term experiments.
2. Experimental 2.1 Liquid and gas samples The samples investigated in this work were provided from stock of gas analysis group at BAM. Originally, these were supplied by different distributors of industrial and specialty gases, as well as fine chemicals. The origin and purity information of all used substances is specified in Tab. S1 within the supplemental information. 2.2 NMR spectroscopy All experiments were conducted on a high-resolution NMR system with 500 MHz proton frequency (Varian Assoc., Palo Alto, CA, USA). It was equipped with either an Interchangeable Flow Cell (IFC) probe or a 5 mm OneNMR probe depending on the certain application, which is described in detail in the following sections. To ensure quantitative conditions longitudinal relaxation times T1 were determined in initial experiments using inversion recovery pulse sequence. Depending on these results relaxation delay d1 was set to at least 5-times of the longest T1 to achieve a sufficient relaxation of the observed nuclei between excitation pulses. In case of carbon-13 NMR spectra decoupling was applied only during acquisition for avoiding disturbances based on 13C-1H heteronuclear Nuclear Overhauser Effect (NOE), which would otherwise have an influence on the intensity of carbon nuclei bonded to different number of protons. This procedure is also known as inverse gated decoupling. The determination of signal areas was performed using methods of numerical integration in a range of several multiples of line width, as well as line fitting. The latter is based on fitting the lineshape 3
with a number of lorentzian-gaussian profiles and determines the signal area from a combination of these adapted functions. 2.3 Liquid and liquefied samples For the observation of liquid and liquefied samples standard NMR tubes with an outer diameter of 5 mm were used. Depending on boiling point and vapor pressure, the components were filled or condensed into the tube while cooling with liquid nitrogen. The experiments were carried out directly in technical mixture, without addition of standards or dilution of the sample unless otherwise stated. The samples were torch-sealed to ensure a high shelf-life and preventing contamination after sample preparation. For applications on components showing higher vapor pressure specialized pressure-resistant tubes (524-PV-9, Wilmad Labglass, Vineland, NJ, USA) were used. These are equipped with a PTFE valve and 1/8” Swagelok connector, suitable for a pressure up to 1.5 MPa. 2.4 Gaseous samples The first setup discussed for gaseous samples is based on a commercial available NMR flow probe (Interchangeable Flow Cell, Varian Assoc., Palo Alto, CA, USA), which contains a glass-made flow cell with a volume of 95 µL and a pressure rating of 3 MPa. The probe outlet is sealed with a ball valve V4 (P-732, IDEX Health&Science, Oak Harbor, WA, USA), while the inlet is connected to a valve setup (Fig. 1). This contains two three-way valves V1 and V2 (SS-41GXHLS1-SC11-049, Swagelok, Solon, OH, USA), as well as another ball valve V3 (P-732, IDEX H&S). The internal volume of this assembly including tubing and NMR probe was determined with 0.9 mL. In the later application sealing of the probe outlet was optimized using 2-component epoxy adhesive directly at the upper end of a defective flow cell. This simplified the pressurization of the sample by decreasing internal volume, because the internal backflow line within the probe was no longer necessary. To introduce samples independent of available pressure of the sample container, a high-pressure syringe pump (neMESYS high-pressure module, cetoni GmbH, Korbußen, Germany) with a 50 mL stainless steel syringe was used for compression of the gas samples. The valve V3 allows a stepwise compression to reach the desired pressure limit of 3 MPa. Monitoring of the actual pressure within the system was realized with a low-volume pressure transducer directly at the NMR probe inlet (XTM-76-190M, Kulite Semiconductor Products Inc., Leonia, NJ, USA). All parts of the system were evacuated before and after measurements by a turbomolecular pump (TSH 064, Pfeiffer Vacuum GmbH, Asslar, Germany). The setup can also be used for filling of the pressure-resistant NMR tubes mentioned in the last section up to the pressure rating of 1.5 MPa by connecting it to valve V2.
Fig. 1: Experimental setup for analysis of gas samples with NMR spectroscopy up to 3 MPa within a commercial available Online-NMR flow probe. Additionally, filling of pressure-resistant glass tubes, equipped with a 1/8” PTFE needle valve is possible.
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The second setup used for gas phase NMR studies was based on a commercially available highpressure NMR tube made of zirconia (Daedalus Innovations LLC, Aston, PA, USA) with a pressure rating of 100 MPa. This was connected to a valve setup for controlling the evacuation of the system, the introduction of the sample directly from a gas cylinder exploiting the cylinder filling pressure, as well as including a pressure transducer (81530-1000, Burster Präzisionsmesstechnik GmbH&Co. KG, Gernsbach, Germany) for monitoring the actual filling pressure inside the system (Fig. 2). All parts of the setup are pressure rated up to a maximum of 100 MPa (Taper Seal, High-Pressure Equipment Company, Erie, PA, USA) and connected with 1/8” stainless steel tubing, even when the studies conducted so far were fairly limited in pressure, because of the available filling pressure of the sample cylinders.
Fig. 2: Experimental setup for gas-phase NMR experiments using a commercially available high-pressure NMR tube made of zirconia with an overall pressure rating of up to 100 MPa.
3. Results and Discussion 3.1 Purity assessment of components for PRG’s All liquid and, with regard to the setup ratings liquefiable components used for production of PRG’s were checked for purity. This ranges from C3 up to C6 components. In the following the procedure is demonstrated on pentane and neopentane serving as two examples for the whole range of raw materials. To maintain quantitative conditions, the longest T1 relaxation time for proton, as well as carbon-13 was determined (Tab. S2). After these initial experiments the components were investigated using quantitative proton and carbon-13 NMR spectroscopy. Because of waiving the addition of deuterated solvents no lock signal was capable for field-frequency stabilization. Therefore, the overall measurement time was limited to a reasonable level of a few hours to prevent undesired signal drifts. Additionally, this amount of time is within a competitive range with other analytical methods used for purity assessment like suitable calibrated gas chromatography. The proton spectra of the components show broad signals in most of the cases, which complicate the application of numerical integration in certain range of line width without overlapping of integral regions. Because of the close resemblance of the expected impurities, mainly linear and branched hydrocarbon isotopes, observation of signal overlapping is very likely. As an example Fig. 3A shows the proton NMR spectrum of pentane, within quantification of impurities is not possible due to overlap with the signals of the main compound. This becomes especially obvious when looking at the expansion. Signal area determination of small peaks based on probable impurities was influenced by the tail of a main signal, preventing an accurate separate quantification. 5
Fig. 3: (A) Proton NMR spectrum of pentane (nt=16, d1=30s, overall measurement time 9.33 min). (B) Carbon-13 NMR spectrum of pentane (nt=64, d1=150s, overall measurement time 163 min).
To demonstrate this influence Tab. S3 shows the determined area ratio of corresponding signals compared to the theoretical expectation. Only in the two cases of butane and pentane the experimental results meet the expectation with negligible deviations. In contrast, carbon-13 NMR spectroscopy is a promising alternative, showing a broader spectral range and higher signal dispersion. The application of proton decoupling, providing spectra consisting of singlets only, facilitates the application of integration and line fitting methods. As a result of lower natural abundance of only 1.1 %, as well as longer T1 relaxation times (Tab. S2) these experiments require longer measurement times. The carbon-13 NMR spectrum of pentane shows well separated signals based on a contaminant (Fig. 2B). These peaks occur at chemical shifts of 31.17, 29.38, 21.22, and 10.73 ppm. The area ratio obtained from a line fitting method is 1:1:2:1. According to this information the contaminant was identified as the constitutional isomer 2-methylbutane, which was confirmed by comparison with a pure component spectrum of this compound. For relative quantification of the impurity a 100 %-approach was used, assuming that every contamination could be detected within the spectrum. The quantification based on three repetitions showed a content of 0.200 ± 0.01 % of 2-methylbutane. More details on this result can be found in Tab. S4. This type of impurity represents a cross-contamination, if 2-methylbutane is also part of the planned mixture within the production process. Already transferred amounts of this compound during filling of pentane can be corrected, which helps to achieve a higher accuracy in composition of the final 6
mixture. Uncertainties given in Tab. S4 are based on standard uncertainties obtained from repeated measurement. This allows an estimation of the repeatability of the NMR measurements, without any possibility to evaluate the trueness, which is assumed to be correct due to direct physical correlation given that the NMR parameters are chosen correctly. Another example of a compound used for production of PRG’s is 2,2-dimethylpropane, which is also known under its trivial name neopentane. In contrast to the other investigated alkane isomers in this study the production process of this compound is not based on rectification of crude oil. Following that, different impurities were expected.
Fig. 4: Carbon-13 NMR spectrum of 2,2-dimethylpropane including contaminations with signal assignment of main component and contaminants. Spectrum was obtained accumulating 64 Scans with a relaxation delay of 300 s, leading to an overall measurement time of 323,2 min.
As already shown previous cases proton spectra show broad signals of the main component, which leads to overlaps with signals of chemical or structural similar contaminants. Therefore, carbon-13 NMR spectra of 2,2-dimethylpropane were acquired for identification and quantification of impurities in the sample. The signal assignment to the identified components is given in Fig. 3. For identification of the content, spectra were compared to entries of SDBS database of National Institute of Advances Industrial Science and Technology (AIST) [26]. Suspected contaminants were purchased and verified by reference measurements (Fig. S1). Thus it was possible to identify 2methylpropane, 2-methylbutane, as well as 2-butyne as impurities within the sample of 2,2dimethylpropane. Besides, there are still unresolved signals left, which are marked with an “x” instead of assignment to a structure in Fig. 4. This includes two signals at 28.25 and 22.64 ppm, which show an area ratio of 2.77:1. Therefore these signals were assigned to a fictive unknown compound with an expected area ratio of 3:1 to be able to use the quantification approach. After identification of impurities and signal assignment within the carbon-13 NMR spectra, signal areas were determined using a line fitting method. These signal areas were processed according to the already described 100 % approach. The results of the quantification based on four repeated measurements on the sample of 2,2-dimethylpropane is shown in Tab. 1.
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Tab. 1: Results of quantification based on four carbon-13 NMR spectra of 2,2-dimethylpropane. All numbers represent molar fractions given in %. Component 1 2 3 4 mean
2,2-dimethylpropane 98.554 98.504 98.492 98.553 98.526±0.033
2-butyne 0.631 0.632 0.648 0.605 0.629±0.018
2-methylbutane 0.508 0.530 0.508 0.483 0.507±0.019
2-methylpropane 0.140 0.161 0.170 0.175 0.162±0.015
unresolved 0.166 0.172 0.183 0.183 0.176±0.008
Just like in Tab. S4, given uncertainty values are based on repeated measurements and are related to repeatability of the NMR experiment and quantification. As an approach to resolve the so far unidentified compound a long-term experiment using 1300 scans was performed. Therefore, deuterated acetone was added to the sample to establish field-frequency stabilization based on the deuterium lock signal. This was needed to avoid broad signals as a result of accumulation of misaligned spectra due to field drifts over time of the experiment. Because of observed artifacts, which were assumed to be based on the proton decoupling, two different decoupling schemes were used for comparison and distinction of artifacts and genuine signals (Fig. S2). Latter occur in both spectra with the same chemical shift values and are framed with a dotted line within Fig. S2. To compare the results of quantification the waltz-decoupled spectrum using 1300 scans was evaluated by line fitting. These results are mostly within the uncertainty range of the results given in Tab. 1. In contrast to the experiments using only 64 scans two unresolved compounds could be detected. The first one is based on a signal at 124.95 ppm, while the second one is related to three signals at 30.00, 27.93, and 22.39 ppm with an area ratio of around 3:3:1. Unfortunately, it was not possible to identify the structure of the unresolved compounds. Therefore, these were handled like unidentified compounds according to the already described 100 % approach (Tab. S5). The chemical shift value of 124.95 ppm leads to the assumption of the presence of an alkene within the sample, but there was no possibility for verification at this time.
3.2 Gas phase measurements Besides the experiments in liquid and liquefied hydrocarbons gas phase measurements were performed using proton and carbon-13 NMR spectroscopy. First experiments were conducted on a pure sample of methane 5.5 (≥ 99.9995 %) in the gas phase to investigate influences of changes in temperature and gas density on quantitative NMR spectroscopy. For considering real gas behavior of methane in the investigated pressure range gas densities given in Fig. 5 were calculated based on the van- der-Waals equation. Solving this equation to the amount of substance results in a non-trivial cubic equation. Alternatively, an iterative approach (Eq. 1) was used for determining the amount of substance at a certain pressure level, which was used for estimation of gas density with respect to the active volume of the NMR flow cell of 95 µL. The parameters a = 2.313·10–1 Pa·m6·mol–2 und b = 4.278·10–5 m3·mol–1 were taken from literature [27].
pV nx RT
2 nx 1a nx 1b 1 1 pV 2 V
(1)
8
Fig. 5A shows the proton signal area of the CH4 singlet over the variation of gas density by application of pressure from atmospheric conditions up to 2.5 MPa in increments of 0.25 MPa at a constant temperature of 300.15 K. The variation was performed by increasing, as well as decreasing pressure to check behavior for possible hysteresis effects. As shown in Fig. 5A, the variation of gas density shows a good agreement with the expected linearity in signal area of qNMR without any signs for hysteresis. Additionally, temperature variation was performed between 300.15 K and 320.15 K in increments of 5 K (Fig. 5B). It shows slight deviations between signal areas while increasing and decreasing temperature at a constant pressure of 3 MPa. A possible explanation is the location of the temperature sensor within the NMR probe, which can lead to an inadequate representation of the sample temperature itself. Temperature was controlled with variable temperature system (VT) of the NMR spectrometer and equilibrated for several minutes after reaching the desired temperature setpoint. Furthermore, the influence of gas density on spin-lattice relaxation time T1 was investigated by determination for proton and carbon-13 nucleus. Pressure was varied from atmospheric pressure to 3 MPa in increments of 0.5 MPa for proton and from 0.75 MPa to 3 MPa in increments of 0.25 MPa for carbon-13, respectively. Pure gas samples like methane show short relaxation times of less than 1 s, especially carbon-13 relaxation times are very low compared to experiments in solution [28]. Fig. 5C shows the influence of density changes on the spin-lattice relaxation time T1, resulting in a linear dependency for both proton and carbon-13 nuclei, which is in a good agreement with data found in literature obtained by Jameson et al. on methane and carbon-13 enriched methane samples [28].
Fig. 5: Signal area of methane signal in methane 5.5 during variation of gas density by application of pressure at a constant temperature of 300.15 K (A) and temperature at a constant pressure of 3 MPa (B) in increasing, as well as decreasing direction. Investigation of density dependence of proton and carbon-13 relaxation times in a range from atmospheric pressure and 0.75 MPa, respectively, up to 3 MPa (C). Latter are shown in comparison with obtained data from literature [28].
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As an example of determination of several components a sample of primary reference gas mixture (PRG’s) manufactured at BAM was studied. The certified gravimetric composition of the mixture BAM-G492 from production process according to ISO 6142 is shown in Tab. S6. For determination of mixture composition proton NMR spectra were acquired. Fig. 6A shows a proton NMR spectrum of BAM-G492 at a pressure of 2.79 MPa with signal assignment to the different components.
Fig. 6: (A) Proton NMR spectrum (nt=64, d1=90s, measurement time 98 min) and (B) carbon-13 NMR spectrum (nt=256, d1=10s, measurement time ~55 min) of reference gas mixtures BAM-G492 at p=2.79 MPa, T=300.15 K.
When looking at the assignment in Fig. 6A, the problem of signal overlapping becomes obvious. Only the signals of the matrix component methane at 1.59 ppm, as well as the CH signal of 2methylpropane at 3.23–3.16 ppm were isolated. Unfortunately, the signals of the methyl and methylene groups of propane and butane at 2.40–2.34 ppm and 2.88–2.79 ppm cannot be divided to allow a separate quantification. A possible approach to solve this problem is, like applied for liquid components, the use of carbon-13 NMR spectroscopy. The lack of sensitivity due to the low natural abundance of this isotope is clearly noticeable, because of the already lower number of nuclei in the active region within the gaseous sample. This requires long measurement times, which highly depend on long-term pressure stability of the system to avoid deviations based on a pressure-drop within the experiment runtime. Fig. 6B shows an example of a carbon-13 NMR spectrum of BAMG492. Due to the lower sensitivity of this method only the main components methane, ethane and carbon dioxide are detectable, while even after acquisition of 256 scans the signal-to-noise ratio is not sufficient to detect signals of lower concentrated components. Despite limitation of the experiment time by setting a short relaxation delay, pressure dropped down during this study, which prevents 10
reliable information based on the signal area. This issue is mainly caused by the hardware designed for liquid applications within HPLC setups, which shows insufficient pressure stability when using gaseous samples. A solution for this problem was found by development of the abovementioned high-pressure NMR setup. On a second PRG sample with the identifier BAM-G430 the feasibility of this setup was proved during long-term experiments acquiring carbon-13 NMR spectra over several hours up to days. All experiments were conducted at the available cylinder filling pressure of 4.4 MPa. The certified composition of this mixture, consisting of 11 components, is given in Tab. S6. In this case the already mentioned problem of the absence of deuterated substances for establishing a field-frequency lock shows a high impact on the acquired spectra in terms of signal shifts due to changes in magnetic field over time. Common procedures adding an internal standard for obtaining a stable lock signal are not applicable in the gas phase [29], nor meeting the demand for investigation of the unmodified sample. In literature, the implementation of external lock devices containing liquid deuterated substances is proposed to solve this problem [30 ,31]. Although, this represents no modification of the sample itself, it results in a displacement of gas volume by introduction of a suitable container, e.g., a sealed glass capillary in the active region of the spectrometer affecting sensitivity, as well as likely having an influence on the window profile during the applied gradient shimming routine prior to the experiments. Gradient shimming was used for optimizing z-shims only, while x- and y-shims were previously adjusted by using a regular line shape test sample (1% CHCl3 in 99% acetone-d6). As an alternative we considered an approach based on spectra accumulation in the frequency domain. Therefore, a high number of single spectra consisting of 64 scans were acquired regularly, assuming that field drifts over the measurement time of 2–3 hours are negligible. Following that, spectra were preprocessed by application of phase and baseline correction, as well as an alignment for compensation of signal shifts. The subsequent accumulation is done by adding up intensities of all points within the spectra in the frequency domain, which was implemented in a LabVIEW program. Spectra obtained from that can be treated like any NMR data and evaluated easily in common software solutions like Mestrenova. Tab. 2 shows the results of a line fitting method applied to three long-term experiments on PRG sample of BAM-G430 with overall measurement times between 47 and 169 hours. Degrees of equivalence DNMR, as published by Ratel [32] were used to facilitate comparison of the results, regardless of absolute molar fraction level. The value and corresponding uncertainties were calculated according to Eq.2 and 3.
DNMR xNMR xcert
(2)
2 2 u D uNMR ucert
(3)
The molar fractions taken from the certificate xcert were normalized in a way that the sum of all detectable components equal 100 %. This was required to ensure comparability of the results due to nitrogen contained in the mixture, which is not accessible with carbon-13 NMR spectroscopy. Uncertainties related to the certified values within Tab. 2 were obtained from calibrated GC measurements during certification of the PRG after preparation process.
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Tab. 2: Quantitative results obtained on PRG sample of BAM-G430 from three long-term carbon-13 NMR studies compared to certified reference data by using degrees of equivalence.
Component Methane Ethane Propane Butane Isobutane Pentane Isopentane Neopentane Hexane Carbon Dioxide
xNMR / % 92.541 4.324 1.051 0.188 0.243 0.067 0.052 0.048 0.055
uNMR / % ±0.1794 ±0.0463 ±0.0336 ±0.0201 ±0.0433 ±0.0252 ±0.0063 ±0.0182 ±0.0211
xcert / % 92.604 4.157 1.045 0.208 0.210 0.054 0.055 0.053 0.053
ucert / % ±0.0098 ±0.0075 ±0.0008 ±0.0002 ±0.0002 ±0.0002 ±0.0002 ±0.0001 ±0.0002
DNMR / % -0.063 0.167 0.006 -0.020 0.033 0.013 -0.003 -0.005 0.002
uD / % ±0.1797 ±0.0469 ±0.0336 ±0.0201 ±0.0433 ±0.0252 ±0.0063 ±0.0182 ±0.0211
1.432
0.1908
1.560
±0.0063
-0.128
±0.1909
These results are graphically visualized within Fig. 7 based on the degrees of equivalence introduced in Tab. 2. It shows a good agreement of the quantitative information obtained from carbon-13 NMR spectroscopy with the certified values for most of the observed components. Only in case of ethane a significant systematic deviation from the expected reference value is observable. The reason for that deviation is not completely resolved so far and possibly caused by the 100 % method applied for calibration-free quantification. Due to the normalization to 100 % errors occurring during determination of a single component can have an influence on the whole quantification approach. This hypothesis is supported by the observed underestimation of the mean values for both, methane and carbon dioxide. Despite that, an overlap of the uncertainty ranges with the reference value is achieved due to generally higher uncertainties obtained for these components.
Fig. 7: Quantitative results obtained from three long-term experiments on PRG sample BAM-G430 at p=4.4 MPa and T=300.15 K in comparison with certified reference value by using degrees of equivalence.
This is likely expected for the matrix component methane because of the large area of the related singlet signal compared to the other compounds in the mixture. Therefore, variations during the long experiment times, as well as application of line fitting method are assumed to be particularly distinct in this case. Like for methane, the signal of carbon dioxide in carbon-13 NMR spectroscopy is based on a single nucleus in the molecule. Due to the low amount contained in the sample uncertainty 12
values might increase with regard to sensitivity. Additionally, spin-lattice relaxation time T1 is expected to be higher in comparison with other components due to the quaternary fashion of the observed nucleus. Unfortunately, the described method for accumulation of spectra in the frequency domain is not applicable for determination of relaxation times with common inversion-recovery sequences. Therefore, relaxation delay d1 was set to a constant value of 30 s based on experiences from preliminary studies of natural gas like samples. Even there is no evidence of saturation effects over measurement time this might have an impact on the quantification, especially expected for the component carbon dioxide due to abovementioned properties. The need for very long measurement times, up to several days, for acquisition of carbon-13 NMR data is likely to have an impact on the obtained uncertainty ranges. This is mainly based on the limitation of the high-pressure setup to the available gas cylinder filling pressure. By introduction of a displacement element for compressing the gaseous samples within the active volume of the NMR spectrometer, gas density can be increased, which is resulting in a higher sensitivity and decreasing demand of measurement time. This compression step is obviously limited to the thermodynamic properties of the studied mixtures, provided that no partial condensation of higher components occurs. Compression up to the regular filling pressure of cylinders after PRG production, likely around 15 MPa, can straightforwardly be reached without concerns. When increasing pressure above this limit, calculations based on equations of state, like GERG-2008 [33], can help to confirm mixture stability dependent on the conditions and composition of the mixture prior to the experiments. Because of the higher sensitivity achieved for carbon-13 NMR spectroscopy, direct determination of relaxation times would possibly become feasible. Additionally, a decrease in experiment time is likely to have an influence on achievable uncertainty ranges due to less fluctuations and variances in the shorter time period of measurement. A piston-cylinder-setup designed for a maximum pressure of 60 MPa is currently developed and will be presented in a subsequent article shortly.
4. Conclusions Quantitative NMR spectroscopy turned out to be a powerful tool for analysis of liquid and liquefied hydrocarbon samples, as well as gas-phase applications at elevated pressure. The method allows purity assessment including identification and quantification without the need for calibration for every single contaminant like needed for comparable gas chromatography applications. Additionally, there is no sample preparation needed and handling of liquid components is more feasible than on a standard GC setup. Nevertheless, gas chromatography is still predominant concerning limit of detection, because of the lower sensitivity of NMR spectroscopy. Therefore, qNMR represents not a replacement for GC standard applications of gas analysis in science and industry, but can be interesting for highly specialized fields. As an example NMR is highly promising in metrological applications, because of the direct correlation between number of nuclei and area of the NMR signal as a calibration-free comparison method. Carbon-13 NMR experiments for quantification of impurities in raw materials used for production of primary reference gas mixtures were shown. Additionally, the application of quantitative NMR spectroscopy in the gas phase was checked for feasibility on two samples of natural gas like mixtures using an online NMR flow probe, as well as a specialized high-pressure NMR setup. 13
References [1] N. Zientek, K. Meyer, S. Kern, M. Maiwald, Quantitative Online NMR Spectroscopy in a Nutshell, Chemie Ingenieur Technik 88(6) (2016) 698–709. [2] K. Meyer, S. Kern, N. Zientek, G. Guthausen, M. Maiwald, Process control with compact NMR, Trends Anal. Chem. 83 (2016) 39–52. [3] J. W. Hennel, J. Klinowski, Magic-Angle Spinning: A Historical Perspective, Top. Curr. Chem. 246 (2004) 1–14. [4] I. T. Horvath, J. M. Millar, NMR under High Gas Pressure, Chem. Rev. 91 (1991) 1339–1351. [5] W. Paul, G. B. Benedek, D. M. Warschauer, Nonmagnetic High-Pressure Vessels, Rev. Sci. Instrum. 30(10) (1959) 874–880. [6] H. Yamada, Pressure-resisting glass cell for high pressure, high resolution NMR measurement, Rev. Sci. Instrum. 45(5) (1974) 640–642. [7] C. D. Roe, Sapphire NMR tube for high-resolution studies at elevated pressure, J. Magn. Res. 63(2) (1985) 388–391. [8] I. T. Horvath, E. C. Ponce, New valve design for high-pressure sapphire tubes for NMR measurements, Rev. Sci. Instrum. 62(4) (1991) 1104–1105. [9] S. Bai, C. M. Taylor, C. L. Mayne, R. J. Pugmire, D. M. Grant, A new high pressure sapphire nuclear magnetic resonance cell, Rev. Sci. Instrum. 67(1) (1996) 240–243. [10] Website of Daedalus Innovations LLC, http://www.daedalusinnovations.com/apparatus/highpressure.html (last accessed 24.10.2016). [11] W. T. Raynes, A. D. Buckingham, H. J. Bernstein, Medium Effects in Proton Magnetic Resonance. I. Gases, J. Chem. Phys. 36 (1962) 3481–3488. [12] A. D. Buckingham, T. Schaefer, W. G. Schneider, Solvent Effects in Nuclear Magnetic Resonance Spectra, J. Chem. Phys. 32 (1960) 1227–1233. [13] G. Govil, Nuclear Magnetic Resonance Studies in Gases, Appl. Spectrosc. Rev. 7(1) (1973) 47–78. [14] C. J. Jameson, Gas-Phase NMR Spectroscopy, Chem. Rev. 91 (1991) 1375–1395. [15] K. Jackowski, Multinuclear NMR spectroscopy in the gas phase, J. Mol. Struct. 786 (2006) 215–219. [16] C. Suarez, Gas-Phase NMR Specotroscopy, The Chemical Educator 3(2) (1998) 1–18. [17] A. B. Shtarov, P. J. Krusic, B. E. Smart, W. R. Dolbier Jr., Bimolecular Kinetic Studies with High-Temperature Gas-Phase 19F NMR: Cycloaddition Reactions of Fluoroolefins, J. Am. Chem. Soc. 123 (2001) 9956–9962. [18] J. Buddrus, H. Herzog, Coupling of Chromatography and NMR, Org. Magn. Res. 15(2) (1981) 211–213. [19] H. Herzog, J. Buddrus, Coupling of Chromatography and NMR Part 5: Analysis of High-Boiling GasChromatographic Fractions by On-Line Nuclear Magnetic Resonance, Chromatographia 18(1) (1984) 31–33. [20] K. Albert: On-line use of NMR detection in separation chemistry, J. Chrom. A 1995, 703, 123–147. [21] T. Zuschneid, H. Fischer, T. Handel, K. Albert, G. Häfelinger, Experimental Gas Phase 1H NMR Spectra and 1 13 Basis Set Dependence of ab initio GIAO MO Calculations of H and C NMR Absolute Shieldings and Chemical Shifts of Small Hydrocarbons, Z. Naturforsch. 59b (2004) 1153–1176. [22] M. D. Grynbaum, D. Kreidler, J. Rehbein, A. Purea, P. Schuler, W. Schaal, H. Czesla, A. Webb, V. Schurig, K. 1 Albert, Hyphenation of Gas Chromatography to Microcoil H Nuclear Magnetic Resonance Spectroscopy, Anal. Chem. 79 (2007) 2708–2713. [23] M. Kühnle, D. Kreidler, K. Holtin, H. Czesla, P. Schuler, W. Schaal, V. Schurig, K. Albert, Online Coupling of Gas Chromatography to Nuclear Magnetic Resonance Spectroscopy: Method for the Analysis of Volatile Stereoisomers, Anal. Chem. 80 (2008) 5481–5486. [24] JCGM 200:2012: International vocabulary of metrology – Basic and general concepts and associated terms (VIM), 3rd Edition, Bureau International des Poids et Mesures (BIPM), Sèvres Cedex, France. [25] Gas analysis – Preparation of calibration gas mixtures – Part 1: Gravimetric method for Class I mixtures. ISO 6142-1:2015. Geneva, Switzerland. [26] Spectral Database for Organic Compounds (SDBS), National Institute of Advanced Industrial Science and Technology (AIST), Japan, http://sdbs.db.aist.go.jp/ (last accessed 25.10.2016). [27] P. W. Atkins, Physical Chemistry, Fifth Edition, Oxford University Press, 1994. [28] C. J. Jameson, A. K. Jameson, N. C. Smith, J. K. Hwang, T. Zia, 13C and 1H Spin Relaxation in CH4 in the Gas Phase, J. Phys. Chem. 95 (1991) 1092–1098. [29] A. A. Marchione, B. Conklin, Gas Phase NMR for the Study of Chemical Reactions: Kinetics and Product Identification, in K. Jackowski, M. Jaszuński (Eds.) Gas Phase NMR, Royal Society of Chemistry, Cambridge, 2016, pp. 126–151.
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Highlights
Purity assessment of hydrocarbon components for reference gas mixture production Gas-phase studies on methane at different temperatures and pressures Feasibility studies of using qNMR for determination of gas mixture composition Long-term carbon-13 NMR studies using a high-pressure NMR setup
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S1090-7807(16)30251-8 http://dx.doi.org/10.1016/j.jmr.2016.11.016 YJMRE 5996
To appear in:
Journal of Magnetic Resonance
Received Date: Revised Date: Accepted Date:
20 September 2016 24 November 2016 25 November 2016
Please cite this article as: K. Meyer, K. Rademann, U. Panne, M. Maiwald, Quantitative NMR spectroscopy for gas analysis for production of primary reference gas mixtures, Journal of Magnetic Resonance (2016), doi: http:// dx.doi.org/10.1016/j.jmr.2016.11.016
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Quantitative NMR spectroscopy for gas analysis for production of primary reference gas mixtures K. MEYER1; K. RADEMANN2; U. PANNE1,2; M. MAIWALD1 1
Bundesanstalt für Materialforschung und -prüfung (BAM), Richard-Willstätter-Straße 11, D-12489 Berlin, Germany 2
Department of Chemistry, Humboldt-Universität zu Berlin, Brook-Taylor-Str.2, D-12489 Berlin, Germany Abstract Due to its direct correlation to the number of spins within a sample quantitative NMR spectroscopy (qNMR) is a promising method with absolute comparison abilities in complex systems in technical, as well as metrological applications. Most of the samples studied with qNMR are in liquid state in diluted solutions, while gas-phase applications represent a rarely applied case. Commercially available NMR equipment was used for purity assessment of liquid and liquefied hydrocarbons serving as raw materials for production of primary reference gas standards. Additionally, gas-phase studies were performed within an online NMR flow probe, as well as in a high-pressure NMR setup to check feasibility as verification method for the composition of gas mixtures. Keywords Quantitative NMR spectroscopy, Gas-phase NMR spectroscopy, Purity assessment, Reference gas mixtures
1. Introduction In the last decades NMR spectroscopy has become a common method used in a variety of different applications in several fields of science and technology. Especially for research and development tasks it provides useful information on both identity and structure of chemical compounds. Most of the performed analysis aiming at identification and structure elucidation of natural, as well as synthetic chemical products. Besides these qualitative approaches, quantitative NMR spectroscopy (qNMR) becomes more and more popular, especially for determinations in complex systems when the application of other analytical methods, mainly chromatography, is complicated. The quantitative information obtained from qNMR is based on the proportionality of NMR signal with number of NMR active nuclei in the observed sample volume. This is comparable with a simple “counting of spins” and has the advantage of a direct calibration-free quantification, provided that the NMR experiment is performed quantitatively with regard to nuclear spin relaxation. Therefore, it represents an ideal reference method for acquisition of quantitative data, which can be used for the system-dependent calibration often required by other analytical techniques. In contrast to gravimetric reference data qNMR provides additional information on non-isolable compounds like transition states and intermediates over the course of a chemical reaction. This is very useful, especially in the field of process analytical technology and the development of online analytical methods for process monitoring and control applications [1]. 1
Most of all samples for NMR experiments are in the liquid state, mainly in diluted solutions using deuterated solvents for avoiding large solvent signals. However, process analytical applications usually take place in highly concentrated technical mixtures without any sample preparation [1, 2]. Besides liquid phase applications solid material is accessible with NMR spectroscopy by using special experiments and probe hardware like Magic-Angle-Spinning (MAS) technology [3]. On the other hand, gas phase applications represent a rarely applied case, mainly because of the low density of the samples when working at atmospheric pressure conditions. Therefore, sensitivity of NMR spectroscopy can be increased by application of pressure, which requires specialized pressureresistant NMR equipment [4]. While vessels made of non-magnetic metal alloys like beryllium copper allow very high pressure ratings [5], cell-based setups using sapphire and high-performance ceramics have the advantage of higher flexibility and shorter conversion times due to compatibility with regular NMR probes and equipment. Pioneer work in this field was done by Yamada utilizing glass cells that reach burst pressures of up to 290 MPa [6] and Roe developing a single crystal sapphire NMR tube with a pressure rating of up to 100 MPa [7]. This cell design was further improved by Horvath and Ponce [8], as well as Bai et al. [9]. Today, first commercial solutions for high-pressure NMR applications are available in the pressure range of up to 300 MPa [10]. Most of the gas phase applications published aim for confirmation of theoretical approaches concerning medium and solvent effects [11, 12], nuclear magnetic shielding, as well as relaxation mechanisms [13, 14, 15]. Additionally, kinetic studies on exchange processes, as well as gas phase reactions were reported by Suarez et al. [16] and Shtarov et al. [17] using 1H and 19F NMR spectroscopy. Another promising field is the combination of gas chromatography with NMR spectroscopy. First published from Buddrus and Herzog [18, 19] this application was further investigated and further developed by the research group of Albert [20, 21, 22, 23]. The abovementioned advantages of qNMR make it a promising technology to be used within metrological applications, e.g., for purity assessment or gas mixture composition analysis. According to the Joint Committee for Guides in Metrology (JCGM) metrology is defined as consideration of all theoretical and practical aspects of measurement, regardless of the measurement uncertainty or field of application [24]. A core concept in metrology is traceability, which implies that a result can be related through a documented chain of calibrations all contributing to measurement uncertainty. This is usually done based on the SI system, which ensures comparability between results obtained at different location and/or time. A global aim of metrological research is the traceability of all measurements to well-known fundamental relationships like velocity of light, replacing physical standards, which can suffer from changes over time even when stored under controlled conditions. As a designated institute (DI) the Bundesanstalt für Materialforschung und -prüfung (BAM) is responsible for the national gas standards in the sectors of energy gases and automotive exhaust gases. This task is part of legal gas metrology delegated from Physikalisch-Technische Bundesanstalt (PTB) as the national metrological institute (NMI) of Germany. It includes preparation of highaccuracy primary reference gas mixtures (PRG), as well as the development and improvement of advanced measurement capabilities. The production process of these PRG’s is based on a static gravimetric procedure with sequential fillings of single components or pre-manufactured mixtures according to the ISO standard 6142 within ISO/TC 158 “analysis of gases” [25]. The final PRG, which are traceable to SI by weight, are then used for certification of secondary gas standards manufactured by specialty gas distributors. Latter or related tertiary standards are then used for calibration of instruments within technical applications, in which traceability is required due to legal 2
or commercial regulatory affairs, e.g., the determination of heat of combustion of natural gas streams. For maintaining highest accuracy of the composition of the produced PRG a rigorous purity assessment of every single component used for production is essential. Especially crosscontaminations with different isomers of the higher hydrocarbons up to C 6 have to be considered during the preparation process. This is usually performed using gas chromatography (GC), which requires a calibration for each of the species to determine. Additionally, identification of unknown substances can be challenging depending on the available detectors and the handling of some of the components for GC is not feasible, especially when they are in the liquid state. In this work we evaluate and present a new method for purity assessment of components used for the production of PRG’s by using carbon-13 quantitative NMR. In contrast to GC, direct relative quantification of impurities, as well as identification of formerly unknown contaminants was possible. Pressure-resistant NMR tubes enabled the method to be used for analysis of components with a vapor pressure up to 1.5 MPa under liquefied conditions. Besides the determination of impurities in the liquid phase, quantitative NMR spectroscopy was applied in the gas phase up to a pressure of 3 MPa on different gas mixtures. In a first approach, an online NMR flow probe was utilized by using a valve setup combined with a high-pressure syringe pump for compression of the gas samples. Later, studies were performed within a commercially available high-pressure NMR tube made of zirconia providing a higher pressure rating and better pressure stability for conduction of long-term experiments.
2. Experimental 2.1 Liquid and gas samples The samples investigated in this work were provided from stock of gas analysis group at BAM. Originally, these were supplied by different distributors of industrial and specialty gases, as well as fine chemicals. The origin and purity information of all used substances is specified in Tab. S1 within the supplemental information. 2.2 NMR spectroscopy All experiments were conducted on a high-resolution NMR system with 500 MHz proton frequency (Varian Assoc., Palo Alto, CA, USA). It was equipped with either an Interchangeable Flow Cell (IFC) probe or a 5 mm OneNMR probe depending on the certain application, which is described in detail in the following sections. To ensure quantitative conditions longitudinal relaxation times T1 were determined in initial experiments using inversion recovery pulse sequence. Depending on these results relaxation delay d1 was set to at least 5-times of the longest T1 to achieve a sufficient relaxation of the observed nuclei between excitation pulses. In case of carbon-13 NMR spectra decoupling was applied only during acquisition for avoiding disturbances based on 13C-1H heteronuclear Nuclear Overhauser Effect (NOE), which would otherwise have an influence on the intensity of carbon nuclei bonded to different number of protons. This procedure is also known as inverse gated decoupling. The determination of signal areas was performed using methods of numerical integration in a range of several multiples of line width, as well as line fitting. The latter is based on fitting the lineshape 3
with a number of lorentzian-gaussian profiles and determines the signal area from a combination of these adapted functions. 2.3 Liquid and liquefied samples For the observation of liquid and liquefied samples standard NMR tubes with an outer diameter of 5 mm were used. Depending on boiling point and vapor pressure, the components were filled or condensed into the tube while cooling with liquid nitrogen. The experiments were carried out directly in technical mixture, without addition of standards or dilution of the sample unless otherwise stated. The samples were torch-sealed to ensure a high shelf-life and preventing contamination after sample preparation. For applications on components showing higher vapor pressure specialized pressure-resistant tubes (524-PV-9, Wilmad Labglass, Vineland, NJ, USA) were used. These are equipped with a PTFE valve and 1/8” Swagelok connector, suitable for a pressure up to 1.5 MPa. 2.4 Gaseous samples The first setup discussed for gaseous samples is based on a commercial available NMR flow probe (Interchangeable Flow Cell, Varian Assoc., Palo Alto, CA, USA), which contains a glass-made flow cell with a volume of 95 µL and a pressure rating of 3 MPa. The probe outlet is sealed with a ball valve V4 (P-732, IDEX Health&Science, Oak Harbor, WA, USA), while the inlet is connected to a valve setup (Fig. 1). This contains two three-way valves V1 and V2 (SS-41GXHLS1-SC11-049, Swagelok, Solon, OH, USA), as well as another ball valve V3 (P-732, IDEX H&S). The internal volume of this assembly including tubing and NMR probe was determined with 0.9 mL. In the later application sealing of the probe outlet was optimized using 2-component epoxy adhesive directly at the upper end of a defective flow cell. This simplified the pressurization of the sample by decreasing internal volume, because the internal backflow line within the probe was no longer necessary. To introduce samples independent of available pressure of the sample container, a high-pressure syringe pump (neMESYS high-pressure module, cetoni GmbH, Korbußen, Germany) with a 50 mL stainless steel syringe was used for compression of the gas samples. The valve V3 allows a stepwise compression to reach the desired pressure limit of 3 MPa. Monitoring of the actual pressure within the system was realized with a low-volume pressure transducer directly at the NMR probe inlet (XTM-76-190M, Kulite Semiconductor Products Inc., Leonia, NJ, USA). All parts of the system were evacuated before and after measurements by a turbomolecular pump (TSH 064, Pfeiffer Vacuum GmbH, Asslar, Germany). The setup can also be used for filling of the pressure-resistant NMR tubes mentioned in the last section up to the pressure rating of 1.5 MPa by connecting it to valve V2.
Fig. 1: Experimental setup for analysis of gas samples with NMR spectroscopy up to 3 MPa within a commercial available Online-NMR flow probe. Additionally, filling of pressure-resistant glass tubes, equipped with a 1/8” PTFE needle valve is possible.
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The second setup used for gas phase NMR studies was based on a commercially available highpressure NMR tube made of zirconia (Daedalus Innovations LLC, Aston, PA, USA) with a pressure rating of 100 MPa. This was connected to a valve setup for controlling the evacuation of the system, the introduction of the sample directly from a gas cylinder exploiting the cylinder filling pressure, as well as including a pressure transducer (81530-1000, Burster Präzisionsmesstechnik GmbH&Co. KG, Gernsbach, Germany) for monitoring the actual filling pressure inside the system (Fig. 2). All parts of the setup are pressure rated up to a maximum of 100 MPa (Taper Seal, High-Pressure Equipment Company, Erie, PA, USA) and connected with 1/8” stainless steel tubing, even when the studies conducted so far were fairly limited in pressure, because of the available filling pressure of the sample cylinders.
Fig. 2: Experimental setup for gas-phase NMR experiments using a commercially available high-pressure NMR tube made of zirconia with an overall pressure rating of up to 100 MPa.
3. Results and Discussion 3.1 Purity assessment of components for PRG’s All liquid and, with regard to the setup ratings liquefiable components used for production of PRG’s were checked for purity. This ranges from C3 up to C6 components. In the following the procedure is demonstrated on pentane and neopentane serving as two examples for the whole range of raw materials. To maintain quantitative conditions, the longest T1 relaxation time for proton, as well as carbon-13 was determined (Tab. S2). After these initial experiments the components were investigated using quantitative proton and carbon-13 NMR spectroscopy. Because of waiving the addition of deuterated solvents no lock signal was capable for field-frequency stabilization. Therefore, the overall measurement time was limited to a reasonable level of a few hours to prevent undesired signal drifts. Additionally, this amount of time is within a competitive range with other analytical methods used for purity assessment like suitable calibrated gas chromatography. The proton spectra of the components show broad signals in most of the cases, which complicate the application of numerical integration in certain range of line width without overlapping of integral regions. Because of the close resemblance of the expected impurities, mainly linear and branched hydrocarbon isotopes, observation of signal overlapping is very likely. As an example Fig. 3A shows the proton NMR spectrum of pentane, within quantification of impurities is not possible due to overlap with the signals of the main compound. This becomes especially obvious when looking at the expansion. Signal area determination of small peaks based on probable impurities was influenced by the tail of a main signal, preventing an accurate separate quantification. 5
Fig. 3: (A) Proton NMR spectrum of pentane (nt=16, d1=30s, overall measurement time 9.33 min). (B) Carbon-13 NMR spectrum of pentane (nt=64, d1=150s, overall measurement time 163 min).
To demonstrate this influence Tab. S3 shows the determined area ratio of corresponding signals compared to the theoretical expectation. Only in the two cases of butane and pentane the experimental results meet the expectation with negligible deviations. In contrast, carbon-13 NMR spectroscopy is a promising alternative, showing a broader spectral range and higher signal dispersion. The application of proton decoupling, providing spectra consisting of singlets only, facilitates the application of integration and line fitting methods. As a result of lower natural abundance of only 1.1 %, as well as longer T1 relaxation times (Tab. S2) these experiments require longer measurement times. The carbon-13 NMR spectrum of pentane shows well separated signals based on a contaminant (Fig. 2B). These peaks occur at chemical shifts of 31.17, 29.38, 21.22, and 10.73 ppm. The area ratio obtained from a line fitting method is 1:1:2:1. According to this information the contaminant was identified as the constitutional isomer 2-methylbutane, which was confirmed by comparison with a pure component spectrum of this compound. For relative quantification of the impurity a 100 %-approach was used, assuming that every contamination could be detected within the spectrum. The quantification based on three repetitions showed a content of 0.200 ± 0.01 % of 2-methylbutane. More details on this result can be found in Tab. S4. This type of impurity represents a cross-contamination, if 2-methylbutane is also part of the planned mixture within the production process. Already transferred amounts of this compound during filling of pentane can be corrected, which helps to achieve a higher accuracy in composition of the final 6
mixture. Uncertainties given in Tab. S4 are based on standard uncertainties obtained from repeated measurement. This allows an estimation of the repeatability of the NMR measurements, without any possibility to evaluate the trueness, which is assumed to be correct due to direct physical correlation given that the NMR parameters are chosen correctly. Another example of a compound used for production of PRG’s is 2,2-dimethylpropane, which is also known under its trivial name neopentane. In contrast to the other investigated alkane isomers in this study the production process of this compound is not based on rectification of crude oil. Following that, different impurities were expected.
Fig. 4: Carbon-13 NMR spectrum of 2,2-dimethylpropane including contaminations with signal assignment of main component and contaminants. Spectrum was obtained accumulating 64 Scans with a relaxation delay of 300 s, leading to an overall measurement time of 323,2 min.
As already shown previous cases proton spectra show broad signals of the main component, which leads to overlaps with signals of chemical or structural similar contaminants. Therefore, carbon-13 NMR spectra of 2,2-dimethylpropane were acquired for identification and quantification of impurities in the sample. The signal assignment to the identified components is given in Fig. 3. For identification of the content, spectra were compared to entries of SDBS database of National Institute of Advances Industrial Science and Technology (AIST) [26]. Suspected contaminants were purchased and verified by reference measurements (Fig. S1). Thus it was possible to identify 2methylpropane, 2-methylbutane, as well as 2-butyne as impurities within the sample of 2,2dimethylpropane. Besides, there are still unresolved signals left, which are marked with an “x” instead of assignment to a structure in Fig. 4. This includes two signals at 28.25 and 22.64 ppm, which show an area ratio of 2.77:1. Therefore these signals were assigned to a fictive unknown compound with an expected area ratio of 3:1 to be able to use the quantification approach. After identification of impurities and signal assignment within the carbon-13 NMR spectra, signal areas were determined using a line fitting method. These signal areas were processed according to the already described 100 % approach. The results of the quantification based on four repeated measurements on the sample of 2,2-dimethylpropane is shown in Tab. 1.
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Tab. 1: Results of quantification based on four carbon-13 NMR spectra of 2,2-dimethylpropane. All numbers represent molar fractions given in %. Component 1 2 3 4 mean
2,2-dimethylpropane 98.554 98.504 98.492 98.553 98.526±0.033
2-butyne 0.631 0.632 0.648 0.605 0.629±0.018
2-methylbutane 0.508 0.530 0.508 0.483 0.507±0.019
2-methylpropane 0.140 0.161 0.170 0.175 0.162±0.015
unresolved 0.166 0.172 0.183 0.183 0.176±0.008
Just like in Tab. S4, given uncertainty values are based on repeated measurements and are related to repeatability of the NMR experiment and quantification. As an approach to resolve the so far unidentified compound a long-term experiment using 1300 scans was performed. Therefore, deuterated acetone was added to the sample to establish field-frequency stabilization based on the deuterium lock signal. This was needed to avoid broad signals as a result of accumulation of misaligned spectra due to field drifts over time of the experiment. Because of observed artifacts, which were assumed to be based on the proton decoupling, two different decoupling schemes were used for comparison and distinction of artifacts and genuine signals (Fig. S2). Latter occur in both spectra with the same chemical shift values and are framed with a dotted line within Fig. S2. To compare the results of quantification the waltz-decoupled spectrum using 1300 scans was evaluated by line fitting. These results are mostly within the uncertainty range of the results given in Tab. 1. In contrast to the experiments using only 64 scans two unresolved compounds could be detected. The first one is based on a signal at 124.95 ppm, while the second one is related to three signals at 30.00, 27.93, and 22.39 ppm with an area ratio of around 3:3:1. Unfortunately, it was not possible to identify the structure of the unresolved compounds. Therefore, these were handled like unidentified compounds according to the already described 100 % approach (Tab. S5). The chemical shift value of 124.95 ppm leads to the assumption of the presence of an alkene within the sample, but there was no possibility for verification at this time.
3.2 Gas phase measurements Besides the experiments in liquid and liquefied hydrocarbons gas phase measurements were performed using proton and carbon-13 NMR spectroscopy. First experiments were conducted on a pure sample of methane 5.5 (≥ 99.9995 %) in the gas phase to investigate influences of changes in temperature and gas density on quantitative NMR spectroscopy. For considering real gas behavior of methane in the investigated pressure range gas densities given in Fig. 5 were calculated based on the van- der-Waals equation. Solving this equation to the amount of substance results in a non-trivial cubic equation. Alternatively, an iterative approach (Eq. 1) was used for determining the amount of substance at a certain pressure level, which was used for estimation of gas density with respect to the active volume of the NMR flow cell of 95 µL. The parameters a = 2.313·10–1 Pa·m6·mol–2 und b = 4.278·10–5 m3·mol–1 were taken from literature [27].
pV nx RT
2 nx 1a nx 1b 1 1 pV 2 V
(1)
8
Fig. 5A shows the proton signal area of the CH4 singlet over the variation of gas density by application of pressure from atmospheric conditions up to 2.5 MPa in increments of 0.25 MPa at a constant temperature of 300.15 K. The variation was performed by increasing, as well as decreasing pressure to check behavior for possible hysteresis effects. As shown in Fig. 5A, the variation of gas density shows a good agreement with the expected linearity in signal area of qNMR without any signs for hysteresis. Additionally, temperature variation was performed between 300.15 K and 320.15 K in increments of 5 K (Fig. 5B). It shows slight deviations between signal areas while increasing and decreasing temperature at a constant pressure of 3 MPa. A possible explanation is the location of the temperature sensor within the NMR probe, which can lead to an inadequate representation of the sample temperature itself. Temperature was controlled with variable temperature system (VT) of the NMR spectrometer and equilibrated for several minutes after reaching the desired temperature setpoint. Furthermore, the influence of gas density on spin-lattice relaxation time T1 was investigated by determination for proton and carbon-13 nucleus. Pressure was varied from atmospheric pressure to 3 MPa in increments of 0.5 MPa for proton and from 0.75 MPa to 3 MPa in increments of 0.25 MPa for carbon-13, respectively. Pure gas samples like methane show short relaxation times of less than 1 s, especially carbon-13 relaxation times are very low compared to experiments in solution [28]. Fig. 5C shows the influence of density changes on the spin-lattice relaxation time T1, resulting in a linear dependency for both proton and carbon-13 nuclei, which is in a good agreement with data found in literature obtained by Jameson et al. on methane and carbon-13 enriched methane samples [28].
Fig. 5: Signal area of methane signal in methane 5.5 during variation of gas density by application of pressure at a constant temperature of 300.15 K (A) and temperature at a constant pressure of 3 MPa (B) in increasing, as well as decreasing direction. Investigation of density dependence of proton and carbon-13 relaxation times in a range from atmospheric pressure and 0.75 MPa, respectively, up to 3 MPa (C). Latter are shown in comparison with obtained data from literature [28].
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As an example of determination of several components a sample of primary reference gas mixture (PRG’s) manufactured at BAM was studied. The certified gravimetric composition of the mixture BAM-G492 from production process according to ISO 6142 is shown in Tab. S6. For determination of mixture composition proton NMR spectra were acquired. Fig. 6A shows a proton NMR spectrum of BAM-G492 at a pressure of 2.79 MPa with signal assignment to the different components.
Fig. 6: (A) Proton NMR spectrum (nt=64, d1=90s, measurement time 98 min) and (B) carbon-13 NMR spectrum (nt=256, d1=10s, measurement time ~55 min) of reference gas mixtures BAM-G492 at p=2.79 MPa, T=300.15 K.
When looking at the assignment in Fig. 6A, the problem of signal overlapping becomes obvious. Only the signals of the matrix component methane at 1.59 ppm, as well as the CH signal of 2methylpropane at 3.23–3.16 ppm were isolated. Unfortunately, the signals of the methyl and methylene groups of propane and butane at 2.40–2.34 ppm and 2.88–2.79 ppm cannot be divided to allow a separate quantification. A possible approach to solve this problem is, like applied for liquid components, the use of carbon-13 NMR spectroscopy. The lack of sensitivity due to the low natural abundance of this isotope is clearly noticeable, because of the already lower number of nuclei in the active region within the gaseous sample. This requires long measurement times, which highly depend on long-term pressure stability of the system to avoid deviations based on a pressure-drop within the experiment runtime. Fig. 6B shows an example of a carbon-13 NMR spectrum of BAMG492. Due to the lower sensitivity of this method only the main components methane, ethane and carbon dioxide are detectable, while even after acquisition of 256 scans the signal-to-noise ratio is not sufficient to detect signals of lower concentrated components. Despite limitation of the experiment time by setting a short relaxation delay, pressure dropped down during this study, which prevents 10
reliable information based on the signal area. This issue is mainly caused by the hardware designed for liquid applications within HPLC setups, which shows insufficient pressure stability when using gaseous samples. A solution for this problem was found by development of the abovementioned high-pressure NMR setup. On a second PRG sample with the identifier BAM-G430 the feasibility of this setup was proved during long-term experiments acquiring carbon-13 NMR spectra over several hours up to days. All experiments were conducted at the available cylinder filling pressure of 4.4 MPa. The certified composition of this mixture, consisting of 11 components, is given in Tab. S6. In this case the already mentioned problem of the absence of deuterated substances for establishing a field-frequency lock shows a high impact on the acquired spectra in terms of signal shifts due to changes in magnetic field over time. Common procedures adding an internal standard for obtaining a stable lock signal are not applicable in the gas phase [29], nor meeting the demand for investigation of the unmodified sample. In literature, the implementation of external lock devices containing liquid deuterated substances is proposed to solve this problem [30 ,31]. Although, this represents no modification of the sample itself, it results in a displacement of gas volume by introduction of a suitable container, e.g., a sealed glass capillary in the active region of the spectrometer affecting sensitivity, as well as likely having an influence on the window profile during the applied gradient shimming routine prior to the experiments. Gradient shimming was used for optimizing z-shims only, while x- and y-shims were previously adjusted by using a regular line shape test sample (1% CHCl3 in 99% acetone-d6). As an alternative we considered an approach based on spectra accumulation in the frequency domain. Therefore, a high number of single spectra consisting of 64 scans were acquired regularly, assuming that field drifts over the measurement time of 2–3 hours are negligible. Following that, spectra were preprocessed by application of phase and baseline correction, as well as an alignment for compensation of signal shifts. The subsequent accumulation is done by adding up intensities of all points within the spectra in the frequency domain, which was implemented in a LabVIEW program. Spectra obtained from that can be treated like any NMR data and evaluated easily in common software solutions like Mestrenova. Tab. 2 shows the results of a line fitting method applied to three long-term experiments on PRG sample of BAM-G430 with overall measurement times between 47 and 169 hours. Degrees of equivalence DNMR, as published by Ratel [32] were used to facilitate comparison of the results, regardless of absolute molar fraction level. The value and corresponding uncertainties were calculated according to Eq.2 and 3.
DNMR xNMR xcert
(2)
2 2 u D uNMR ucert
(3)
The molar fractions taken from the certificate xcert were normalized in a way that the sum of all detectable components equal 100 %. This was required to ensure comparability of the results due to nitrogen contained in the mixture, which is not accessible with carbon-13 NMR spectroscopy. Uncertainties related to the certified values within Tab. 2 were obtained from calibrated GC measurements during certification of the PRG after preparation process.
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Tab. 2: Quantitative results obtained on PRG sample of BAM-G430 from three long-term carbon-13 NMR studies compared to certified reference data by using degrees of equivalence.
Component Methane Ethane Propane Butane Isobutane Pentane Isopentane Neopentane Hexane Carbon Dioxide
xNMR / % 92.541 4.324 1.051 0.188 0.243 0.067 0.052 0.048 0.055
uNMR / % ±0.1794 ±0.0463 ±0.0336 ±0.0201 ±0.0433 ±0.0252 ±0.0063 ±0.0182 ±0.0211
xcert / % 92.604 4.157 1.045 0.208 0.210 0.054 0.055 0.053 0.053
ucert / % ±0.0098 ±0.0075 ±0.0008 ±0.0002 ±0.0002 ±0.0002 ±0.0002 ±0.0001 ±0.0002
DNMR / % -0.063 0.167 0.006 -0.020 0.033 0.013 -0.003 -0.005 0.002
uD / % ±0.1797 ±0.0469 ±0.0336 ±0.0201 ±0.0433 ±0.0252 ±0.0063 ±0.0182 ±0.0211
1.432
0.1908
1.560
±0.0063
-0.128
±0.1909
These results are graphically visualized within Fig. 7 based on the degrees of equivalence introduced in Tab. 2. It shows a good agreement of the quantitative information obtained from carbon-13 NMR spectroscopy with the certified values for most of the observed components. Only in case of ethane a significant systematic deviation from the expected reference value is observable. The reason for that deviation is not completely resolved so far and possibly caused by the 100 % method applied for calibration-free quantification. Due to the normalization to 100 % errors occurring during determination of a single component can have an influence on the whole quantification approach. This hypothesis is supported by the observed underestimation of the mean values for both, methane and carbon dioxide. Despite that, an overlap of the uncertainty ranges with the reference value is achieved due to generally higher uncertainties obtained for these components.
Fig. 7: Quantitative results obtained from three long-term experiments on PRG sample BAM-G430 at p=4.4 MPa and T=300.15 K in comparison with certified reference value by using degrees of equivalence.
This is likely expected for the matrix component methane because of the large area of the related singlet signal compared to the other compounds in the mixture. Therefore, variations during the long experiment times, as well as application of line fitting method are assumed to be particularly distinct in this case. Like for methane, the signal of carbon dioxide in carbon-13 NMR spectroscopy is based on a single nucleus in the molecule. Due to the low amount contained in the sample uncertainty 12
values might increase with regard to sensitivity. Additionally, spin-lattice relaxation time T1 is expected to be higher in comparison with other components due to the quaternary fashion of the observed nucleus. Unfortunately, the described method for accumulation of spectra in the frequency domain is not applicable for determination of relaxation times with common inversion-recovery sequences. Therefore, relaxation delay d1 was set to a constant value of 30 s based on experiences from preliminary studies of natural gas like samples. Even there is no evidence of saturation effects over measurement time this might have an impact on the quantification, especially expected for the component carbon dioxide due to abovementioned properties. The need for very long measurement times, up to several days, for acquisition of carbon-13 NMR data is likely to have an impact on the obtained uncertainty ranges. This is mainly based on the limitation of the high-pressure setup to the available gas cylinder filling pressure. By introduction of a displacement element for compressing the gaseous samples within the active volume of the NMR spectrometer, gas density can be increased, which is resulting in a higher sensitivity and decreasing demand of measurement time. This compression step is obviously limited to the thermodynamic properties of the studied mixtures, provided that no partial condensation of higher components occurs. Compression up to the regular filling pressure of cylinders after PRG production, likely around 15 MPa, can straightforwardly be reached without concerns. When increasing pressure above this limit, calculations based on equations of state, like GERG-2008 [33], can help to confirm mixture stability dependent on the conditions and composition of the mixture prior to the experiments. Because of the higher sensitivity achieved for carbon-13 NMR spectroscopy, direct determination of relaxation times would possibly become feasible. Additionally, a decrease in experiment time is likely to have an influence on achievable uncertainty ranges due to less fluctuations and variances in the shorter time period of measurement. A piston-cylinder-setup designed for a maximum pressure of 60 MPa is currently developed and will be presented in a subsequent article shortly.
4. Conclusions Quantitative NMR spectroscopy turned out to be a powerful tool for analysis of liquid and liquefied hydrocarbon samples, as well as gas-phase applications at elevated pressure. The method allows purity assessment including identification and quantification without the need for calibration for every single contaminant like needed for comparable gas chromatography applications. Additionally, there is no sample preparation needed and handling of liquid components is more feasible than on a standard GC setup. Nevertheless, gas chromatography is still predominant concerning limit of detection, because of the lower sensitivity of NMR spectroscopy. Therefore, qNMR represents not a replacement for GC standard applications of gas analysis in science and industry, but can be interesting for highly specialized fields. As an example NMR is highly promising in metrological applications, because of the direct correlation between number of nuclei and area of the NMR signal as a calibration-free comparison method. Carbon-13 NMR experiments for quantification of impurities in raw materials used for production of primary reference gas mixtures were shown. Additionally, the application of quantitative NMR spectroscopy in the gas phase was checked for feasibility on two samples of natural gas like mixtures using an online NMR flow probe, as well as a specialized high-pressure NMR setup. 13
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Highlights
Purity assessment of hydrocarbon components for reference gas mixture production Gas-phase studies on methane at different temperatures and pressures Feasibility studies of using qNMR for determination of gas mixture composition Long-term carbon-13 NMR studies using a high-pressure NMR setup
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