polar aprotic solvents. The most consistent correlations were found with 3-fluoropyridine as the NMR probe, and, as was noted above, the solvent effect on this molecule involves the least complex deshielding mechanism among the more basic probes. Although the Kosower 2-values and the DimrothReichardt transition energies have been used with some success in the original studies on NMR and ESR spectra, such functions often do not correlate well in single and multiple parameter comparisons for nonpolar and polar aprotic solvents. Krygowski and Fawcett (8) as well as others ( 3 ) have concluded that the Dimroth-Reichardt values are sensitive primarily to the Lewis acidity of the medium and to its hydrogen bond donor capacity. In view of the NMR vs. ESR spectral correlation in Figure 3, it is instructive to examine the data for possible relationships to transition energies of bathochromic indicators, since it has been demonstrated that such model chromophores are very responsive to changes in Lewis basicity of the solvent (9).Phenol blue was selected as a representative red shift indicator based upon previous theoretical and experimental investigations (9-11). The curvilinear plot for the N-hyperfine splitting constant of di-tert-butyl nitroxide vs. the electronic r a* transition energy of Phenol blue is shown in Figure 4. Although the curve is nonlinear, the empirical trend places the stronger hydrogen bond donors in the upper left portion of the curve and nonpolar and weakly polar solvents toward the lower righthand extremity. The algebraic form of the correlation was established by empirical curve fitting techniques and was found to be the rational function given in Equation 2.
c and a was achieved. As a predictive function, Equation 2
carries an uncertainty of f0.09 (std dev) in the derived values of AN. Based upon 20 solvents (excluding only the statistically rejected point for diethyl ether), the correlation coefficient is 0.885 for the nonlinear regression. Superficially, the same form of correlation function is obtained when AN values for the other nitroxide radical probes are used; however, the extent of scattering of the data points is greater than in Figure 4 so that additional ESR probe-dependent constants in the equation cannot be reliably evaluated. To summarize, it is evident that the NMR and ESR spectral responses to medium effects given by the specific Lewis bases, 3-fluoropyridine and di-tert -butyl nitroxide radical, yield the best overall correlations to other solvent polarity parameters. Although single and multiple parameter correlations involving macroscopic solvent properties generally fail, pairwise comparisons of NMR or ESR data to electronic spectral shifts for solvatochromic indicators give rise to approximately the same order for increasing solvent polarity. Recent values for 31P NMR coupling constants (Vpt.p) of trans-[PtCl~(PBu~)z] in ten aprotic solvents (12)correlate linearly to the ESR splitting constants for the nitroxide group and to the 19Fchemical shifts as well. However, the greatest un$ertainties in the polarity sequence remain among the hydrogen bond donor solvents, regardless of the NMR probe used.
-
LITERATURE CITED (1) (2) (3) (4)
CET- u ET - b When using the specific data in Table I1 relating AN(ditert-butyl nitroxide) and &(Phenol blue), the constants have the values: a = 712.7 f 0.11; b = 46.7 f 0.03; c = 15.27 f 0.32(std dev). The computation of these constants was initiated with assumed graphic values for b as one of the asymptotes and was followed by iteration until convergence in
(5) (6) (7) (8) (9) (10) (11) (12)
AN=---
C. Giam and J. Lyle, J. Am. Chem. SOC.,95, 3235 (1973). 6.Knauer and J. Napier, J. Am. Chem. Soc., 98, 4395 (1976). F. Fowler, A. Katritzky, and R. Rutherford, J. Chem. SOC.8,1971, 460. M. Greenberg, R. Bodner, and A. Popov, J. Phys. Chem., 77, 2449 (1973). G. Maciel et al., hog. Chem., 5, 554 (1966). J. Dechter and J. Zink, J. Am. Chem. SOC., 97, 2937 (1975). H. Berman and T. Stengie, J. Phys. Chem., 79, 1001 (1975). T. Krygowski and W. Fawcett, J. Am. Chem. SOC.,97, 2143 (1975). 0. Kolling, Anal. Chem., 48, 884, 1814 (1976). E. McRae, J. Phys. Chem., 61, 562 (1957). J. Figueras, J. Am. Chem. Soc., 93, 3255 (1971). K. Dixon, M. Fakley, and A. Pidcock, Can. J, Chem., 54, 2733 (1976).
RECEIVEDfor review October 25,1976. Accepted January 21, 1977.
Determination of Hydrogen Content of Fuel by Low Resolution Proton Nuclear Magnetic Resonance Spectrometry P. T. Ford" and N. J. Friswell Shell Research Ltd., Thornton Research Centre, P.O. Box
I, .Chester, U.K.
1. J. Richmond Newport Oxford Instruments, Ne wport Pagnell, U.K.
A prellmlnary evaluation is reported of the use of low resolution nuclear magnetic spectrometry (NMR) for determination of the hydrogen content of aviation turbine fuels. Wlth correct choke of instrument condltlons, the technique is shown to be accurate and simple to use, and to require a comparatively short tline for determination.
Combustion characteristics of aviation turbine fuels are controlled by a large number of tests in fuel specifications. American Society for Testing and Materials (ASTM) and 594
ANALYTICAL CHEMISTRY, VOL. 49, NO. 4, APRIL 1977
International Air Transport Association (IATA) specifications (1,2) include tests for aromatic content, naphthalene content, smoke point, and luminometer number. Increasingly,however, fuel hydrogen content has been shown by many workers to give better predictions of combustion performance and it has been proposed (e.g. 3 ) that a single determination of hydrogen content could be used to replace the present multiplicity of tests. Both ASTM and IATA are considering this proposal at present and therefore it was considered opportune to examine methods for its determination. To date these methods have been based on complete combustion of a fuel sample with gravimetric determination of the
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Flgure 1. NMR saturation effects for various hydrocarbons relative to
relaxed water (+) *Heptane, vlscosity 0.598cSt; (A)Jet AI fuel, 1.521 cSt; (0) Oleic acid, 26 cSt (86OF); (0) Castor oil, 293 cSt (100 OF); (X) Jet AI fuel, 1.380cSt
water produced (e.g., ASTM method D.1018). A calculation method, based on empirical correlation with other fuel properties, is also available (ASTM method D.3343). An alternative approach which could offer advantages in precision and time and ease of determination is by low resolution proton nuclear magnetic resonance spectrometry (NMR). It is believed that this has not been investigated to date and a preliminary evaluation is reported here.
EXPERIMENTAL A Newport Analyzer, Mark 111, supplied by Newport Oxford Instruments, Newport Pagnell, U.K., has been used in this work. It is a low-resolution, continuous-wave instrument tuned to the magnetic resonance frequency of the proton. A fuel sample placed in the field of the permanent magnet absorbs energy from the RF oscillator proportional to the hydrogen content of the sample. A potentially major problem that was expected was energy absorption saturation caused by the long relaxation times of the low viscosity liquids under study. This would limit the amount of RF energy input that could be used in order to maintain a linear response to hydrogen content and thereby reduce the precision of the measurement by decreasing the signal/noise ratio. The first part of the evaluation therefore was to examine this effect by determining the RF level at which saturation could be detected for typical aviation fuel samples. This was done by recording the NMR absorption (digitally displayed on this instrument) as the RF level was increased for the fuel sample and for a liquid with a very short relaxation time (water with the addition of a small amount of a paramagnetic saltMnClz.4HzO). Following this, instrument conditions were chosen to minimize the effects of saturation, and the hydrogen contents of a number of pure hydrocarbons and aviation turbine fuel samples were determined. The fuel samples tested were obtained from widely distributed crude oil sources and represented the widest possible variations of composition that might be met with current and future fuels. For this part of the evaluation, comparison was made with determinations of hydrogen content using a combustion technique based on a Perkin-Elmer CHN elemental analyzer the accuracy of which was shown to compare favorably with that quoted for the ASTM approved combustion method D.1018.
RESULTS AND DISCUSSION Evaluation of Saturation,Effects. Instrument outputs for two fuel samples (Jet A1 type) and for heptane, oleic acid, and castor oil relative to that for “relaxed” water (water MnC1~4H20,concn 1.5 g/L) are shown graphically in Figure 1. From these results and others not shown here, it is confirmed that the RF level a t which saturation effects can be detected is related to sample viscosity; i.e., as viscosity increases, the relaxation time becomes shorter. It can be seen
+
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134
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140
142
144
146
HYDROGEN CONTENT, % w, DETERMINED BY TRC COMBUSTIONTECHNIQUE
Flgure 2. Comparison of hydrogen content determinations by NMR and combustion techniques
Table I. Hydrogen Contents of Pure Hydrocarbons Hydro-
Hydrogen
True
content % w, determined
hydrogen content, % w
70.3,70.3
...
14.37
42.9,42.9 78.7, 78.8 49.4,49.5 75.0, 75.2
8.77 16.10 10.11 15.35
8.75 16.09
carbon
Instrument response
Cyclohex-
ane To1u ene n-Heptane Mesitylene n-Dodecane
10.06
15.39
from Figure 1that, for aviation fuel samples, the maximum RF level that could be used without incurring saturation effects is about 20 PA. Determination of Hydrogen Content of Pure Hydrocarbons and Aviation Fuel Samples. Following the evaluation of saturation effects, fixed instrument conditions and techniques were adopted for the subsequent determination of hydrogen contents: these were an RF level of 20 MAand an integration period of 128 s. To avoid errors caused by temperature changes or instrument drift, all readings were taken relative to that for a sample of cyclohexane, i.e., the instrument was recalibrated for each sample. Determination of hydrogen content involved weighing a fixed quantity (25 g in this case) of sample into a glass container, measuring the NMR signal with the 128-s integration period, then immediately measuring the signal from a sealed sample of 25 g cyclohexane. Values of hydrogen content determined for some pure hydrocarbons are given in Table I. Clearly, good accuracy can be achieved with the technique. Determinations for a large number of aviation fuel samples by low resolution NMR and by a combustion technique are compared in Figure 2. Again, good agreement is demonstrated. By visual examination of this graph and of fuel properties, the errors appear to be purely random, no bias towards fuels of a particular type or composition being discernible. From the limited number of fuel samples examined in this work, a precision for the NMR method may be estimated as 0.05 which may be compared with 0.11 for the ASTM (D.1018) combustion method and 0.08 for the microcombustion method used here. It was considered that the only other possible interferences to NMR determination of hydrogen content could arise from ANALYTICAL
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595
the magnetic properties of conductivity-promoting additives or iron oxide contamination. These were investigated using the highest contents of additives and contaminants that might be found in jet fuels (1 mg/L ASA-3-an additive containing chromium and calcium compounds-and 50 mg/L black iron oxide). No effect on the values determined for hydrogen content could be detected. Dissolved oxygen content was also shown to have no effect. In conclusion it appears that the use of low resolution proton NMR to determine hydrogen content of aviation turbine fuels is an extremely promising approach. It is simple to use, requires a very short time for determination (about 5 min) and
is capable of giving results to an accuracy better than those of techniques currently employed.
LITERATURE CITED ( I ) American Society for Testing and Materials, Standard specification for aviation turbine fuels, D.1655. (2) International Air Transport Association, Guidance material for aviation turbine fuels. Amended Dec. 1975. Corrected Jan. 1976. (3) C. R. Martel and L. C. Angello, USAF, Technical Report AFAPL-TR-72103.
RECEIVEDfor review October 7,1976. Accepted January 12, 1977.
Intrinsic Dimensionality of Smell James R. McGlll and Bruce R. Kowalskl* Laboratory for Chernornetrics, Department of Chemistry, University of Washington, Seattle, Wash., 98 195
The human sense of smell has long been a toplc of scholarly dlscusslon. Varlous emplrlcal odor classification schemes have been deflned In an attempt to describe the human sensory spectrum. The four most prominent theories are shape sensors, vlbratlonal coupllng, membrane puncture, and acld-base Interactlon. Thls paper attempts to determlne the lntrlnslc dlmenslonalltyof the human sensory space by flrst flttlng multlple emplrlcal odor slmllarltles using physlcal and chemical measurements of the molecules Involved. The axes of the space were then rotated, via the Karhunen-Loeve transform, whlch Indicated that there are only two meaningful axes In the space. By use of both the orlglnal physlcal and chemlcal measurements, and theoretlcal values calculated for the molecules by semlemplrlcalmethods, these axes were found to relate to the molecule’s electron donor ablllty and Its dlrected dlpole.
The human sense of smell has been a source of scholarly discussion since the time of the Greeks. Aristotle (I) (400B.C.) suggested the first empirical classification,dividing odors into sweet, bitter, pungent, sharp, and oily smells. Lucretius (2) (47 B.C.) was the first to try to define a theoretical basis for odors when he speculated that unpleasant smells were produced by hooked, jagged particles, and pleasant smells by smooth, round particles. After Lucretius, scholarly interest in the sense of smell became more empirically inclined, culminating with the work of Zwaardemaker (3) who, in 1895, proposed an empirical classification system which divided smells into nine classes (ethereal, aromatic, fragrant, ambrosial, alliaceous, empyreumatic, caprylic, repulsive, and nauseating), and 30 subdivisions. These 30 are listed in column 1 of Table I. Attempts to define a unifying theory behind sensations of smell were initiated by Hemming ( 4 ) in 1916 when he proposed an “olfactoryprism”. He defined the prism with flowery, fruity, and foul forming the upper triangle and spicy, resinous, and burnt forming the lower. Each member of the former triangle was connected vertically to each member of the latter (i.e., spicy and flowery are vertically connected, etc.). In 1927, Crocker and Henderson ( 5 ) postulated that only four sensors, detecting fragrant, acid, burnt, and caprylic odors, were necessary to explain all smells. They defined the maximum intensity of any odor to be 8 and the minimum to be 0. This classification scheme formed the basis of the early quantitative experiments in odor classification. As research progressed, this four-sensor scheme was found to be too lim596
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ited, and Amoore (6) postulated seven sensors: ethereal, camphoraceous, musky, floral, minty, pungent, and putrid. How these relate to Zwaardemaker’s system is shown in column 2 of Table I. Amoore noticed that in the first five of these categories, models made of compounds from the same category had similar shapes. This led him to revive Lucretius’ idea that the shape of a molecule defines its scent and to postulate shape sensors which fit the molecular forms in a lock-and-key manner. Amoore has since done extensive work using twodimensional projections of atomic models and has had some success fitting scent classifications with them. A separate school of odor theory has developed, based on the observation of Dyson (7),in 1937,that molecules of similar odor seem to have bands in the same region of their Raman spectra (1400-3500 cm-l) and he speculated that this frequency region was where the osmotic membranes of the nose would respond to vibrations. This theory has been extensively studied and modified by Wright (8) who calculated that only vibrations below 500 cm-l are excited at room temperature, and thus focused his attention on the Raman region in the 500 to 50 cm-1 range. He, like Amoore, has had some success fitting experimental data to his theory. A major empirical study of the human odor sensory space was conducted by R. H. Wright and K. M. Michaels (9)which used nine standards for comparative classification (shown in relation to Zwaardemaker’s and Amoore’s schemes in column 3 of Table I). A major attempt at unifying these two theories was conducted by Schiffman (IO). She used Guttman’s (11)method of nonlinear mapping to produce a two-dimensional representation of the nine-dimensional space produced by Wright’s study (9).She observed that molecules of similar smell clustered together, and that there seemed to be some correlation of the structure of the compounds and their smell. Using the structural formulas of the compounds, she counted a number of chemical features, such as the number of double bonds, number of alcoholic, aldehydic, and acidic groups, number of sulfurs and nitrogens, etc., along with other variables, such as molecular weight, and attempted to fit the axes produced by Guttman’s method. She also included Raman spectral information. Using a weighting method which she and co-workers had developed, she was able to generate measures of how important each feature was in explaining the data space. She had some success fitting the axes of the reduced dimensional space and found that a few measures were important (particularly molecular weight).
