The quality of a chemical product, such as petroleum, biodiesel or edible oil, is the result of a carefully controlled process. In process control, industrial and chemical engineers continually check various aspects of the health of a process.
- Monitoring and optimizing reaction dynamics
- Batch sampling for content and purity
- Preprocess analysis
- Dilution control
- Identifying impurities
- Monitoring concentration gradients
Modifications in chemical content arising from oxidative processes, chemical transformation due to prolonged exposure to heat (thermal decomposition) or light (polymerization) or other variations in a chemical process are typically monitored by gas- and liquid-phase chromatography. These are static techniques often requiring chemical modification prior to analysis. This can be costly and time-consuming since samples may need to be sent out for synthesis and analysis.
Process NMR is a method of process control, utilizing NMR for analytical testing. NMR is ideally suited for analyzing changes in reaction mixtures, identifying changes in chemical structure, monitoring concentrations, mixing conditions and detecting impurities. NMR is a noninvasive, nondestructive technique providing information under static or dynamic conditions – the latter being particularly attractive for in situ monitoring and testing of process applications, without the need for separation and derivatization of chemical species.
The Thermo Scientific™ picoSpin™ NMR spectrometer offers high performance, low cost, and compact size, making it ideal for many process NMR applications:
- Biofuels – fatty acid methyl ester fuels composition analysis
- Food – edible oils composition analysis, oxidation/shelf-life analysis, soluble fat/water content
The Thermo Scientific™ picoSpin™ 80 1H NMR spectra of methyl esters of oleic acid and linolenic acid below suggest applications to process control of fatty acid composition in a range of edible oils and biofuels.
The spectrum of methyl oleate (methyl (Z)-9-octadecenoate), the methyl ester of the monounsaturated fatty acid oleic acid, is characterized by several distinct proton groups. Two olefinic protons (C9,10) produce a signal down field at δ 5.4, three methyl ester protons (C20) appear midfield as a single peak at δ 3.62, four allylic protons (C8,11) produce the multiple signal at δ 2.15. The remaining aliphatic methylene protons (C2-7,12-15) produce an intense singlet at δ 1.37, α-methylene protons (C17) appear as a triplet at δ 2.12, and a β-methylene signal (C16) appears at δ 1.6 as a shoulder peak on the intense methylene backbone signal. The terminal methyl protons (C1) appear on the trailing edge of the large methylene singlet at δ 0.98.
Methyl Linoleate (methyl (Z,Z)-9,12-octadecadienoate) is the methyl ester of the polyunsaturated fatty acid linoleaic acid. This fatty acid methyl ester (FAME) has two vinyl groups in the aliphatic chain resulting in an increase in intensity of the olefinic proton signal (C6,7, C9,10; δ 5.4) relative to the allyic proton signal (C5,11) at δ 2.05, and the appearance of a new signal at δ 2.75 due to 2 divinyl methylene protons at C8. As the the aliphatic methylene proton signal decreases, the terminal methyl-to-methylene ratio increase gives rise to a more prominent terminal methyl (C20) signal at δ 0.96.
Methyl linolenate is the methyl ester of the polyunsaturated fatty acid linolenic acid with two additional vinyl groups relative to methyl oleate. In this spectrum we see an expected increase of the olefinic proton signal (C3,4, C6,7, C9,10; δ 5.4), a moderately strong allylic proton signal (C2,11) at δ 2.1, and a growing divinyl proton signal (C5,8) at δ 2.8. The large methylene signal (C12-15) at δ 1.38 is still a dominate feature in the spectrum but lower in intensity, allowing the α-methylene proton signal (C17; δ 2.13) to appear more prominent. The methyl ester proton signal (C20; δ 3.62) is unaffected by the additional vinyl groups, whereas the terminal methyl signal at δ 1.00 is better resolved due to the narrowing of the large aliphatic-methylene peak.
We used the Thermo Scientific™ picoSpin™ 45 NMR spectrometer to examine the complex spectrum of gasoline and estimate the amount of ethanol blended into the fuel. Gasoline is a complex mixture of hydrocarbons and additives. Ethanol is often added to gasoline as a way to incorporate more renewable energy sources into fuels while simultaneously improving the octane rating.1 The regular unleaded gasoline we obtained was labeled as containing up to 10% ethanol (E10) by volume; other fuel blends, such as E85, can contain up to 85% ethanol. While the complex mixture of compounds that make up gasoline would typically make identification and quantification of a single constituent difficult, the absence of any significant resonance lines in the chemical shift range of 3.0 – 6.5 ppm makes the identification and quantification of ethanol in gasoline possible.
All spectra were acquired from a single sample of 85 octane, regular unleaded gasoline and used without further purification. Proton (1H) NMR spectra were acquired using a 90 degree pulse angle, 750 ms acquisition time, 10 s recovery delay; all spectra are an average of 49 scans.
1. Renzoni, G. E.; Shankland, E. G.; Gaines, J. A.; Callis, J. B. Anal. Chem. 1985, 57, 2864-2867.
2. Edwards, John C. Principles of NMR. www.process-nmr.com/pdfs/NMR Overview.pdf; (accessed Nov 9, 11).
Alcohol proof measures the amount of ethyl alcohol (ethanol) in an alcoholic beverage. Absolute alcohol is 200 proof, or 100% pure ethanol, 100 proof is 50% alcohol by volume, 50 proof is 25% alcohol, and so on. We tested this proofing system with the Thermo Scientific™ picoSpin™ 45 NMR spectrometer by measuring the proton (1H) NMR spectrum of several beverages ranging in proof from 42 (21% alcohol) up to 100 (50% alcohol). In Figure 1 individual, unnormalized spectra of 7 beverages are compiled: 42 and 55 proof; rum, 60 proof; schnapps, 70 and 80 proof; vodka, 94 proof; gin, and 100 proof; whiskey. Except for the 'walk' of the hydroxyl (-OH) signal centered near 4.7 ppm the spectra look very similar. To observe differences is alcohol content we expand two regions of this figure, the methyl (-CH3) group region (Figure 2) and the -OH signal (Figure 3).
In Figure 2 the difference in percent alcohol content becomes evident. Our whiskey sample (100 proof) has the largest methyl signal due to the larger concentration of -CH3 groups, while the 42-proof rum beverage has the lowest alcohol content and, hence, the weakest methyl signal. As the beverage proof increases from 42 to 100 in our tested samples we see the -CH3 signal likewise increase. Only the 55-proof rum signal is out of order. This may be due to the coconut flavoring compound in our rum sample increasing the methyl signal, or the 60-proof schnapps alcohol content is not properly labeled. Based on the trend from 70 – 100 proof, it would appear the 55 proof signal is larger than it should be while the 60 proof signal is lower than expected.
What is apparent in Figure 3, is that the behavior of the -OH peak is different than that of the methyl group upon changing alcohol concentration. The chemical shift of the this signal is sensitive to the alcohol content in solution and appears to 'walk' as the alcohol/water ratio changes. There is also an inverse relationship in the -CH3 to -OH signal, as the alcohol content increases the water content decreases. So as the -CH3 signal increases there should be a commensurate decrease in -OH signal. The 100-proof whiskey sample saw the largest -CH3 signal, and its -OH signal should be the smallest. Some of these beverage samples also contain sweeteners which cause broadening of the -OH signal. The beverages which contain sweeteners are the 42- and 55-proof rum, and 60-proof schnapps. The 60-proof schnapps beverage, which contains sugar sweeteners, shows considerable broadening in the -OH signal. There also is evidence of sugars in the methylene (-CH2-) region (not shown) of the 60 proof spectrum.
Tinctures are also alcoholic solutions. Their alcohol content is not subject to the same proof labeling regulations as alcoholic beverages, but their proof can be determined by simply doubling the stated percent alcohol content. A 50% alcohol tincture would be equivalent to a 100 proof beverage in ethanol content. We tested this by comparing a picoSpin 1H NMR spectrum (Figure 4 and 5) of pure vanilla extract with a stated alcohol content of 35% (70 proof) to that of a vodka beverage of the same proof. Clearly the labeling of alcohol content in the vanilla tincture and vodka beverage is accurate since the -CH3 signal from both samples have identical intensity.
The -OH signal, again, depends on other factors such as sugar content. Thus, the vanilla extract tincture, which also contains sugar, produces a broad -OH signal. This is similar to the behavior of the -OH signal in the 60-proof schnapps sample seen in Figure 3.
Essential oils (EO) are highly aromatic compounds extracted from the tree bark, flowers, stems, leaves, needles, roots of plants, trees, and grasses. We may associate a particular aroma with a single compound, but most pure essential oils are actually mixtures of varying concentrations of several compounds. Essential oils are used in various applications, from fragrances to air fresheners to aromatherapy.
Essential oils are not oils in the conventional sense, that is, they are not long-chain hydrocarbon compounds, and their strong aroma does not always arise from the presence of an aromatic group in the oil's chemical composition. Instead, essential oils are mixtures of low viscosity fluids containing a surprising variety of molecular species and functional groups. The complexity of essential oil mixtures and the functional group chemistry they contain is easily visualized using proton (1H) NMR spectroscopy. As a diagnostic tool, NMR can distinguish similarly classed essential oil mixtures, such as lemon and lime EO. Furthermore, the NMR technique is non-destructive, providing a method of analysis that does not alter the nature of the sample.
With the Thermo Scientific™ picoSpin™ 45 NMR spectrometer we examined at a variety essential oils. Since essential oils are a mixture of compounds with a wide range of concentrations, we expect the proton signal from higher concentration components to dominate the spectrum. For many of the oils this is true, but for others more than one chemical species was evident. Chemical structures of the principal constituents in the oil are included on the spectra.
All spectra were acquired from pure samples of essential oils obtained from a local market and used without further purification. Proton NMR spectra were acquired using a 90-degree pulse angle and are presented as the average of 16 co-added scans.
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