are evenly distributed through the hydrocarbon Z series. The latter demonstrates the importance of and the need for removal of the polar compounds to obtain a good analysis of the aromatic fraction. RECEIVED for review December 9, 1971. Accepted February 14, 1972. Presented at the Division of Petroleum Chemistry, 162nd National Meeting, American Chemical Society, Washington, D.C., Sept. 1971. This investigation was performed
as a part of the work of American Petroleum Institute Research Project 60 on the Characterization of the Heavy Ends of Petroleum, carried out by the Bureau of Mines at Laramie, Wyo. Work was done under cooperative agreements between the Bureau of Mines, U S . Department of the Interior; the American Petroleum Institute; and the University of Wyoming. Reference to specific commercial materials or models of equipment in this report is made for information only and does not imply endorsement by the Bureau of Mines.
Nuclear Magnetic Resonance Spectrometry of Petroleum Fractions Carbon-13 and Proton Nuclear Magnetic Resonance Characterizations in Terms of Average Molecule Parameters D. R. Clutter,l Leonidas Petrakis,Z R. L. Stenger, Jr., and R. K. Jensen Gulf Research & Deuefopment Company, Pittsburgh, Pa. 15230 A novel development in compositional characterization techniques of petroleum fractions has been made based upon carbon-13 and proton nuclear magnetic resonance spectrometry. The techniques developed have two very attractive features: First, they provide a direct and accurate value of “aromaticity” or aromatic carbon as a fraction of the total carbon. Second, they provide a series of parameters or indices of an “average molecule” based entirely upon the nuclear magnetic resonance spectrum, and thus they afford an excellent characterization of complex, multicomponent petroleum fractions. The previously developed treatments of the data are reexamined and a new, improved procedure is described that provides “fingerprinting” information. It is demonstrated that high quality NMR data can be used to calibrate the 1H NMR, and thus make it possible to obtain the required information from the IH spectra. Relatively inexpensive modifications to a conventional Varian HA-COIL spectrometer that allow us to do CW carbon-13 NMR with proton noise decoupling i n the internal lock mode as well as operate with an external proton lock without decoupling are described. The techniques are illustrated in terms of some FCC charge stocks, but their applicability is wider, and they can be extended to a great variety of petroleum fractions.
DETAILEDCOMPOSITIONAL CHARACTERIZATION of petroleum fractions is extremely important, but has proved both quite difficult and time consuming. For this reason, among the various analytical schemes that have been devised, procedures have also been proposed which attempt to describe a particular petroleum fraction in terms of a hypothetical average molecule (1-4). Proton nuclear magnetic resonance spectrometry can be used to provide a detailed characterization Present address, Carr Laboratory, Department of Chemistry, Mount Holyoke College, South Hadley, Mass. 01075. To whom communications should be addressed. ~~
(1) R. B. Williams, “Symposium on Composition of Petroleum Oils, Determination and Evaluation,” ASTM Spec. Tech. Pub/., 224, 168-94 (1958). (2) S. A. Knight, Chern. Znd., 1967, 1920. (3) J. K. Brown and W . R. Ladner, Fuel (London), 39, 87 (1967). (4) V. J. Bartuska, T. T. Nakashima, and G. E. Maciel, Reo. Sei. Instritrn., 41, 1458 (1970) and references therein.
Table I. Average Parameters Calculable for Petroleum Fractions n = average number of carbon atoms per alkyl substituent. f = average carbon-hydrogenweight ratio of the alkyl groups. %AS = per cent substitution of alkyl groups on non-bridge aromatic ring carbons. #CA = average number of aromatic ring carbon atoms per average molecule. #Cl = average number of non-bridge aromatic ring carbon atoms per average molecule. RA = average number of aromatic rings per average molecule. Rs = average number of alkyl substituents per average molecule. RN = average number of naphthenic rings per average molecule. fa = molar ratio of aromatic carbon to total carbon in sample. BI = branchiness index. MW = average molecular weight. %CS = fraction saturate carbon. ~ C =Nfraction naphthenic carbon. r = number of naphthene rings per substituent %Cl = fraction non-bridge aromatic ring carbons. Average Molecular Formula
of aromatic fractions provided the proper correlation between hydrogen and skeletal carbons is used. Through the use of the integrated intensities of the various types of protons in the sample, the parameters associated with an average molecule can be ascertained. Carbon-1 3 nuclear magnetic resonance on the other hand is capable of directly observing the skeletal carbons, and thus by utilizing the integrated intensities of the various carbon types a good picture of the average molecule can be visualized. Table I lists the average parameters and a brief description of each which can be determined for petroleum fractions. Various approaches can be taken to determine these parameters with some methods requiring additional information such as elemental analysis and an average molecular weight of the sample. These averages parameters are the weighted average for certain properties of the sample and upon putting these average parameters together, an average molecule can be constructed for a given sample. In most instances the values determined are non-integral. ANALYTICAL CHEMISTRY, VOL. 44, NO. 8, JULY 1972
1395
OlHCR ALKYL HYDROOLN
c
r
n
AROMATIC H I D M E N A
I
1
I
I.
,
I
I . . . . .
I
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8.0
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I
I
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0
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M E T H Y L IODIDE STANDARD
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A L I P H A T I C CARBON
A R O M A T I C CARBON Ai
Ae
,
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40
.
,
.
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.
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.
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,
,
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1
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240.9
Figure 1. (a) Proton magnetic resonance spectrum of an aromatic fraction of an FCC charge stock ( b ) Carbon-13 magnetic resonance spectrum of an aromatic fraction of an FCC charge stock The recent improvements in instrumental techniques to obtain high quality carbon-1 3 spectra have thrust carbon-1 3 NMR into a position where it promises to play a central role as a structure-determining tool, A relatively simple modification of a Varian HA-601L spectrometer allows good carbon13 NMR spectra to be obtained in a reasonably brief time. The great potential of carbon-13 NMR to petroleum analysis will be discussed and some preliminary data will be presented.
METHODS USED TO CALCULATE AVERAGE PARAMETERS OF PETROLEUM FRACTIONS Several magnetic resonance methods (1-3) have been used to determine average parameters of petroleum fractions. The following is a brief description of each existing method as well as two procedures developed in this laboratory. The latter represent the more straightforward approaches and take advantage of separation techniques to provide standardization and support of assumptions. 1H NMR-Method 1. Method 1 is basically the method described by Brown and Ladner (3). This method uses the 1396
ANALYTICAL CHEMISTRY, VOL. 44, NO. 8, JULY 1972
proton magnetic resonance spectrum and C and H elemental analysis data to determine an aromaticity of the sample. The normalized integrated intensities of the aromatic, CYalkyl, and other hydrogens whose resonance positions are illustrated in Figure l are determined and used in Equation l to calculate the aromaticity.
L
where C/H is the atomic ratio of carbon/hydrogen from an elemental analysis, x and y are the average number of hydrogens per a-alkyl and the remaining alkyl, respectively. Ha* and (H,* HP*) represent the normalized integrated intensities of the a-alkyl and other alkyl hydrogens, respectively. The problem which arises using this method is the estimation of the parameters x and y . Brown and Ladner (3) performed studies to estimate these parameters using coal-like materials and concluded that 1.5 < x, y < 2.5. The usual value for x and y is 2.0. The aromaticity values determined
+
wo 0.70
0.60
0.50
-
480
-
440 -
-
460
-
380
420 400
360
e 2
-
-
w 320
-
300
-
280
-
’ zao 240 220 200
o
010
020
030
040 1.111
050
om
om
080
090
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AT 1.20
Figure 2. Variation of f,(l) for changes in carbon-hydrogen atomic ratio of alkyl groups in this manner are listed in Table V under Method 1. Studies have been performed here to ascertain the sensitivity of f,(l) upon variation of x and y . In order to simplify the problem and also due to the fact that we are interested in average parameters, x was set equal to y . Figure 2 shows the result of changing x = y in steps of 0.1 from 1.8 to 2.2. The four lines correspond to the four steps; 1.8 to 1.9, 1.9 to 2.0, etc. This plot shows that the change in fa(l) is a function of both fa(l) and x . The sensitivity of f,(l) is approximately 0.03 unit in the region of most aromatic fractions of FCC charge stocks. This indicates an absolute deviation of approximately 0.03 for a change of 0.1 in the value of x = y . No other average parameters are calculated by this method. As a result, the information concerning a sample is minimal when Method 1 is used to determine average parameters. IH NMR-Method 2. This method as originally presented by R. B. Williams ( I ) involves a detailed treatment of an aromatic fraction of an oil sample. Information which is required to obtain average parameters by this method is the integrated intensities of the proton spectrum, carbon and hydrogen elemental analysis, average molecular weight, and a “branchiness index” (see below). There are two assumptions that must be made to perform this analysis. First, the carbonhydrogen ratio of the alkyl groups can be accurately estimated. This involves the determination of a “branchiness index.” Second, the carbon-hydrogen ratio of the a-alkyl groups is equal to that of the other alkyl groups. The equations used to calculate the various parameters by this method are listed in Table 11. Equation 2 involves the second assumption stated above and Equation 3 involves the first assumption. The “branchiness index,” BI, that is used in Equation 4 and indirectly in all the other equations except Equation 2 is defined as the peak height ratio of the gamma to beta protons ( I ) . The argument is that as the amount of naphthenic material in the sample increases, this branchiness index will increase proportionally. This argument is questionable from an experimental point of view in that several of the terminal methyl groups in naphthenic material have resonance positions in the region of methylene groups. This question should be resolvable by detailed analysis of narrow cuts by carbon-13 magnetic resonance. The molecular weight used in Equations 9 and 11 is determined by two methods, VPO and mass spectrometry. Figure 3 shows the correlation between the VPO and mass
180 180
Y’
,’
-
-
/‘
,d
Table 11. Equations Used in Method 2 Calculations n = (Ha* Hg* Hr*)/Ha* (2) f = 12n/(21? 1 - 2r) (3) (0.250[BI 4.121 - 1) (tz - 1) r = (4) 2
+
+ +
+
spectrometry molecular weights for a series of FCC charge stocks. Theoretically, the points in the graph should fall on the dotted line, but as the molecular weight increases, the two methods disagree probably due to the fact that the VPO molecular weight is a number average rather than a weight average molecular weight. Thus, depending upon the molecular weight range and the method of determining the molecular weight, variations in #C, and any other parameter which depends upon the molecular weight will have certain errors associated with its value. Two clarifying remarks may be needed here. First, in the definitions of the average number of carbon atoms per substituent (n)and the average number of alkyl groups per molecule (Rs),it is assumed that a system such as tetralin is considered to have two alkyl groups of two carbons each. Second, no allowances are made in the preceding formulations for a system with more than one aromatic nucleus per molecule, separated by at least a 2-carbon alkyl chain. Thus, if a large percentage of the molecules in the sample were diANALYTICAL CHEMISTRY, VOL. 44, NO. 8, JULY 1972
e
1397
Table 111. Equations Used in Carbon-13 Method fa('") = (A1 AZ)/(Al A2 '43) c, = fa('3C)C C1s = A3C/n C1u 2A2C Cj" = 12AH c1 = CIS c 1 u %AS = CislOO/Ci f = A3C/(Ha* Hg* Hy*)H r = (n 0.5) - (6n/f) RN = Rsr
+ +
+
+
+
+
+
Table IV. Equations Used in Method 3 Calculation HA'" mono = 6 - #CY-alkyl carbons HA'" HA= 8 - #a-alkyl carbons di = 1 - mono #mono = 6mono #di = 10 di #bridge = 2 di #C.k = #mono #di #Cl = #CA - #bridge number alkyl carbons Total #C = #C, f43) = #CA/total #C %AS = lCq#a-alkyl carbons)/#Cl
(
+
+
+
#Cl.
=
(1 -
S)
#C1
av molecular formula = C(totali c ) H(t,t,l av molecular weight = 12.01 (total #C) 1.008 (total #H) 12.01 (total #C - #CA) = 1.008 (total #H - #Clu) 100(total #C - #CA) S" = total #C l00#Cl
+
.HI
ZC1= totalc ZcN
RN =
=
100 #naphthenic carbons total #C
#naphthenic carbons 3.5
phenyls, some of the average parameters would be in error. For instance, f would be too low, #CA and #Cl too high, and RA also too high. Williams ( I ) presents some empirical expressions t o account for this situation, but he states that for systems with molecular weights less than 400, the error introduced by not considering the above types of molecules is minimal. Carbon-13 Method. Through the combination of carbon13 and proton magnetic resonance, Knight ( 2 ) developed a scheme t o determine the average parameters of aromatic fractions of petroleum in a manner quite similar t o Method 2. Essentially, the same average parameters are determined, but information from the carbon-13 spectrum is used whenever possible since this spectrum reflects the characteristics of the carbon skeleton directly. In order t o ascertain the average molecular parameters by the carbon-13 method, the integrated intensities of the char1398
ANALYTICAL CHEMISTRY, VOL. 44, NO. 8, JULY 1972
acteristic resonances in both the carbon-13 and proton magnetic resonance spectra, elemental analysis, and the average molecular weight are required. The assumption involved in this technique pertains only to the interpretation of the proton spectrum; namely, that the carbon t o hydrogen ratio of the a-alkyl and other groups is the same (second assumption in Method 2). From the carbon-13 magnetic resonance spectrum of a petroleum fraction shown in Figure 1, the aromaticity of the sample can be determined directly from the integrated intensities. There are three characteristic regions discernible with relative areas A I , A B ,and A 3 as is shown in this figure. The region, A1, characterizes ring junction carbon, substitated ring carbon, and one-half of the unsubstituted ring carbon. The next region, A*, indicates the other one-half of the unsubstituted ring carbon, and region A 3 contains the resonances of the carbon in saturated groups. The equations used in this method are those listed in Table I11 along with Equations 2, 9, 11, 12, and 14 from Table 11. The average number of carbon atoms per saturated substituent (n) is calculated by Equation 2. Equations 18 and 19 are alternative ways t o calculate C1". Normally, Equation 19 is recommended for this calculation since there is a minimum of overlap in this resonance region. In this method, r is not estimated from the proton branchiness index as in Method 2 but is calculated by Equation 23 from n andf. Thus, these average parameters are based upon the direct observation of the carbon skeleton via the carbon-13 magnetic resonance in as many calculations as are possible. In addition to being able to directly measure the aromaticity, this method should represent a reliable means of estimating the number of naphthene rings per average molecule. 1H NMR-Method 3. This method of characterizing a n aromatic fraction of a petroleum sample through a detailed analysis of its proton magnetic resonance spectrum was developed in this laboratory. Given a proton magnetic resonance spectrum, all of the average parameters calculated by Method 2 as well as the fraction of monoaromatic and diaromatic (fused) ring systems, the average molecular formula, and average molecular weight can be determined. N o additional information is necessary to perform these calculations for the average parameters. In order to extract these average parameters from the proton magnetic resonance spectrum, certain assumptions concerning the sample are required. The first assumption which limits the size of ring systems considered is that the sample contains only mono- and diaromatic (fused) ring systems. The validity of this assumption is supported by separation data in which less than 5 by weight of ring systems greater than diaromatics in a n aromatic fraction of a number of petroleum samples is reported (5). The second assumption is concerned with the spectral interpretation and required that the unsubstituted non-bridge aromatic ring carbon protons are sufficiently separated in the proton magnetic resonance spectrum such that the ratio of mono- to diaromatic protons can be determined. This assumption is supported by a survey of APT selected N M R spectra of mono- and diaromatic systems as well as by data of monoaromatic systems in this laboratory. The third assumption is concerned with the number of substituents in the mono- and diaromatic components. (5) D. M. Jewell, R. G. Ruberto, and B. E. Davis, "A Systematic Approach to the Study of Aromatic Hydrocarbons in Heavy Distillates and Residues," accepted for presentation at the 163rd
National Meeting, American Chemical Society, Petroleum Division, Boston, Mass., 1972.
There are two alternative assumptions that can be made : the number of substituents is the same in both components; the percentage of substitution is the same in both components. By observation of a number of mono- and diaromatic cuts, the first assumption appears to be the more reasonable. We have observed the percentage substitution of monoaromatics to be greater than 50% while that for the diaromatics is less than 50%. The equations used in this method are those listed in Table IV along with Equations 2, 12, and 14 from Table 11. The first parameter calculated is the fraction monoaromatic rings in the sample by Equation 25, where HA^ and HA^ represent the intensity of the mono- and diaromatic protons, respectively. HaD is that portion of the aromatic integrated intensity below 7.05 ppm and HA^ is that portion of the aromatic integrated intensity above 7.05 ppm. The factor (6 #a-alkyl carbons)/(8 - #a-alkyl carbons) is required to yield the proper ratio since the number of non-bridge aromatic ring carbons is not the same in mono- and diaromatic ring systems, and the percentage substitution is not the same. Once #C, is known, then the number of alkyl carbons can be calculated since the relationship between intensity units and number of carbon atoms is now defined. In the calculation of monoaromatics, an iterative process using Equations 25 to 31 is used since #&-alkyl carbons is not known initially. The value of mono normally converges in approximately two iterations. From Equation 35, #ClUrepresents the number of aromatic protons observed in the spectrum, thus the total number of hydrogens in the average molecule, total #H, can be calculated from the relationship between aromatic intensity units and number of aromatic hydrogen atoms. The amount of naphthenic carbon is determined in the following manner. Naphthene rings fused to aromatic systems yield proton NMR spectra with an absorption between 1.65 and 1.9 6 which is assigned the @-naphthenic protons on the unsubstituted carbons. The protons on substituted @-naphthenic carbons yield a resonance slightly upfield from this region in most cases. Thus, to determine the average number of naphthenic carbons, one-half of the region from 1.65 to 1.9 6 corresponds to the number of unsubstituted @-naphthenic carbons and assuming that an equal number of substituted 0-naphthenic carbons are present, the total average number of naphthenic carbons is easily determined. Then the per cent naphthenic carbon ( %CS) is just given by Equation 41. The average number of naphthenic rings (RK) is calculated by Equation 42, where 3.5 assumes an equal amount of five- and six-membered naphthenic rings. Although this is strictly an estimate of the per cent naphthene carbon, the value should reflect major changes in composition from sample to sample. A Graphical lH NMR Method. This method is just an extension of Method 1 to a graphical procedure. The aromaticity value determined in Equation 1 is a function of both the integrated intensities and the C / H ratio from elemental analysis. Figure 4 shows the relationship between f,(l) and (Ha* Hp* Hy*)/2 constructed from a number of analyses of petroleum fractions in this laboratory. As can be seen, a rather definite trend is observed indicating that it is possible to graphically obtain the aromaticity of a petroleum fraction without knowledge of the C/H ratio. This method is obviously limited and assumes that the C/H ratio is the same for H,* Hy*)/2 regardless of the composiany given (Ha* tion of the sample. Comparison of Methods. Method 1 and the graphical extension are of one type of analysis whereas Method 2, Method
+
+
+
+
0.9
F
0.8
-
0.7
-
0.6
-
fa 0.5
-
0.4
-
0.3
-
0.2
’
0.1 ’
0
0.1
0.2 Hag +
0.3
H Z + HIC
0.4
0.5
2
Figure 4. Correlation of aromaticity and normalized intensity of alkyl protons of petroieum fractions 3, and carbon-13 are of another. Therefore, for comparison purposes, Method 1 and the graphical method are grouped together as are Method 2, Method 3, and carbon-13. As stated previously, the graphical ‘H method is a graphical extension of Method 1. Thus, the results provided by these two methods should be equivalent if the C / H ratio varies in a pre‘dictable manner. As a result, the graphical method yields a value of the aromaticity as soon as the proton spectrum can be recorded, whereas Method 1 requires the elemental analysis. Therefore, for a rapid indication of the aromaticity, the graphical method is the method to be used. If average parameters other than aromaticity are desired, then Methods 2, 3, and carbon-13 must be considered. Method 2 and carbon-1 3, as have been presented, parallel each other somewhat in determining the average parameters, whereas Method 3 is a result of a different approach. Upon comparing Method 2 and carbon-1 3, one sees that a “branchiness index” is not estimated in the carbon-1 3 method which is a questionable assumption in Method 2. Therefore, provided that parameters extracted from the proton and carbon13 magnetic resonance spectra are accurate, the carbon-1 3 method should be superior to Method 2 in indicating average parameters of the sample. The effect of the variation in molecular weight and elemental analysis upon the average parameters determined by Method 2 has been determined. The findings from the average molecular weight changes (i.e., whether VPO or mass spectral average molecular weights are used) indicate that as the average molecular weight decreases #CA,#Cl, RA,Rs, and RN all decrease. The amount of change is directly proportional to the ratio of the two average molecular weights compared. ANALYTICAL CHEMISTRY, VOL. 44, NO. 8, JULY 1972
1399
Figure 5. GR&DC 13C CW NMR system with internal 13CSzlock I SUPER STAB I L I ZE
C-1024 OR P D P 81s
PAR LOCK-IN AMP
1 TO MAGNET
a
Table V. Aromaticities Determined for FCC Charge Stocks by Nuclear Magnetic Resonance Sample F002 F004 F014 F016 Methoda 0.34 'H No. 1 0.34 0.29 0.43 'H No. 2 0.39 0.36 0.33 0.48 'H No. 3 0.38 0.30 0.35 0.41 '3C 0.37 0.31 0.35 0.38 0.37 Graphical 0.29 0.34 0.38 For description see text.
Variations in fa(l) and fa(2) with changes in carbon and hydrogen elemental analysis were observed. The variation in weight per cent hydrogen from a series of determinations was about 1%. There is an approximate decrease of 0.06 unit in the aromaticity for a positive increase of 1 % in the weight per cent hydrogen. Other average parameters which decrease with the decrease in weight per cent hydrogen are #CAand RA, and an increase in #Cl, Rs, and R N is observed. Thus, very careful and accurate elemental analyses are required for both Method 2 and carbon-13 to provide accurate average parameters of the sample. In the case of Method 3, no experimental errors other than the quality and measurability of the spectrum are involved. The errors introduced from the spectral measurements of the proton spectrum reflect a variation of approximately +0.01 in the aromaticity and an error of h0.03 in the aromaticity from the carbon-1 3 spectrum. N o further absolute comparisons are possible for the different methods since there is no technique at this time which yields the exact composition of a petroleum fraction. In order t o further ascertain the quality of results from each method, the actual results of each method must be compared with each other and with the spectral features of the proton and carbon-I3 magnetic resonance spectra. From this type of comparison, the technique which best reflects the differences or changes in the composition of a petroleum fraction can be ascertained. A later section is concerned with such a comparison. EXPERIMENTAL
A Varian HA-60 internal lock nuclear magnetic resonance spectrometer operating at 60 MHz was used to obtain the 1400
ANALYTICAL CHEMISTRY, VOL. 44,
NO. 8, JULY 1972
*
RECORDER
OIC
FFi +-MOD
URR-WWN
PULSE
v-4311
GENERAL RADIO
RF- 6
0
proton magnetic resonance spectra. A Varian V-4333 probe which used 5-mm sample tubes was also used. The sample size was approximately 50-100 mg diluted with about 0.3 ml of deuterochloroform with 2.5 % tetramethylsilane (TMS) as an internal reference lock. All samples were recorded with sweep widths of 500 Hz downfield from TMS. The integrated intensities of regions A , a,p, and y shown in Figure 1 were determined by a Varian V-3521A integrator-decoupler. The integral as recorded is shown in Figure 1. The accuracy of the integrator was checked on four consecutive days and had a deviation of 1 of full scale. The carbon-13 magnetic resonance spectra were recorded on an instrument designed and constructed in this laboratory. Figure 5 shows a block diagram of this modified Varian system. The modification is based upon the derivation of the carbon-13 observation frequency (15.08 MHz) and the audio locking frequency from a GR-1164 AR7C frequency synthesizer (4). The carbon-13 frequency is amplified in the V-4311 15.08 MHz unit and fed to the regular double-tuned transmitter coil of the V-4336 probe. The audio beat frequency is divided and fed into the V-4354A lock box and is used as the locking sideband to maintain a constant field/ frequency via the Varian V-3506 magnet flux stabilizer unit in the same manner as in 1H NMR frequency sweep operation. The carbon-13 NMR analytical signal is obtained in the usual crossed-coil configuration, fed to the 15.08 MHz V-4311 receiver section, RF-detected, and introduced into an audio phase detector that is referenced to the analytical channel modulation frequency. Sweeping through the carbon- 13 spectrum is achieved by sweeping the RF centerband via a ramp voltage. Thus, in this mode, the analytical modulation frequency remains constant and the control modulation frequency changes at the same rate as the radio frequency but in the opposite direction. The result and advantage of this scheme is that the instrument is operated as the frequency sweep spectrometer but with the characteristics of a field sweep system. Thus, phase changes due to modulation index variation are reduced to a minimum allowing accurate integrals of the resultant spectrum to be obtained. Base-line stability is a severe problem that has hampered obtaining good carbon-13 spectra over a wide frequency range for m w y years. Overcoming this problem is important especially where one must obtain the entire spectrum in one sweep. Figure 6 illustrates the dramatic improvement in base-line stability and roll-elimination that can be effected in this manner. Figure 6a shows the normal frequency sweep spectrum of tetrachloroethylene illustrating the severe baseline roll which is a result of phase variation in the audio modulation frequency. Figure 6b shows the radio frequency
~
~
Average Parameters Calculated from Proton and Carbon-13 Spectra of Aromatic Fractions of FCC Charge Stocks F014 F002 F004 F016 Sample Method Method Method Method Method Method Method Method Parameters" 2 3 1 3 c 2 3 '3C 2 3 1 3 c 2 3 1 3 c 318.3 252.0 318.3 359.2 319.5 319.5 272.2 296.4 296.4 285.3 312.6 MW 312.6 3.35 3.19 3.35 4.72 4.97 4.97 3.62 3.64 3.92 4.20 3.64 n 4.21 5.48 6.48 5.55 6.19 5.49 5.72 5.49 5.73 5.56 5.49 5.50 f 5.63 56.61 50.28 51.33 54.61 56.37 58.30 51.75 50.65 50.77 50.75 52.63 %AS 51.50 11.33 7.55 9.06 8.36 7.82 7.17 7.60 7.98 7.33 8.57 7.28 kCA 6.98 6.78 8.07 5.27 6.91 5.51 7.43 6.80 7.29 6.52 7.14 6.64 Kl 6.59 1.39 1.50 1.45 1.83 2.95 2.55 1.40 1.35 1.41 1.71 1.32 RA 1.19 3.48 3.91 3.74 4.41 2.97 3.21 3.44 3.77 3.31 3.63 3.49 Rs 3.39 0.68 3.29 0.47 2.10 0.71 1.23 0.77 0.56 0.67 0.39 0.62 RiX 0.76 0.41 0.38 0.30 0.48 0.36 0.31 0.38 0.37 0.35 0.39 0.35 f a 0.33 18.6 23.9 ... 26.3 ... 23.8 20.1 ... 22.0 21 .o ... #CT 23.0 30.9 ... 27.8 ... 43.2 34.0 30.9 ... ... 32.4 33.0 #HT 36.2 Monoaro61 ... 55 ... ... 60 ... ... ... ... 68 ... matics See Table I. Table VI.
sweep spectrum of p-dioxane over the same region illustrating the greatly improved base line. The modified Varian V-4336 probe which was used accommodates 12-mm sample tubes. Approximately 2 ml of sample is required to obtain a carbon-13 spectrum of a petroleum fraction for the type of analysis described in this correspondence. A 5-mm tube containing enriched 13CS2and I3CH3Iwas concentrically placed in the 12-mm tube for adjusting the instrument to optimum conditions and for reference, respectively. Sweep widths of 3000 Hz were employed and 150 scans were time averaged on a PDP SjS computer. The spectrum after accumulation in the PDP SjS was base-line corrected, digitally smoothed to remove high frequency noise, and then integrated to obtain the integrated intensities of regions Ai, A z , and A3 shown in Figure 1. Again an integral is shown in this figure for the sample. RESULTS AND DISCUSSION
All of the methods described previously have been applied to the problem of characterizing the aromatic fraction of FCC charge stocks. Table V shows the aromaticities of four such samples determined by the five methods discussed earlier. Note that the carbon-13 method is the only one which involves no assumptions and is the method of directly counting the aromatic and aliphatic carbons, wheres all other methods calculate the aromaticity (carbon content) by indirect means. Table V indicates that Method 3, carbon-13, and the graphical method yield essentially the same aromaticity values within experimental error for each of these four samples. Methods 1 and 2 appear to give values beyond the experimental error in certain instances, thus indicating that more reliable results are obtainable from Method 3, carbon-13, and the graphical method. Of the latter methods, the graphical method yields an answer quicker since in the carbon-1 3 method data accumulation requires approximately eight hours of time and Method 3 requires a complete analysis of the spectrum. Therefore, the graphical method is the best choice for a rapid and reliable determination of the aromaticity. If average parameters of the aromatic fraction of the petroleum fraction are desired, then a choice between Method 2, Method 3, and carbon-13 must be made since Method 1 and the graphical method yield no additional average parameters. Table VI lists a number of average parameters calculated by the former three methods for the same four samples. The molecular weights listed for Method 2 and carbon-13 are those determined by mass spectral carbon number distribu-
1 1
t
I
I
I
I
200.0 180.0 160.0 140.0 120.0 100.0 8cse PPM
I
L
80.0
60.0
40.0
1
20.0
9
19.6
40.0
60.0
80.0
100.0 120.0 ~ C S ,I
140.0 160.0
180.0 200.0
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Figure 6. (a) 200-ppm Sweep of tetrachloroethylene using frequency sweep (6) 200-ppm Sweep of p-dioxane using RF sweep tions, whereas the molecular weights under Method 3 are calculated in the analysis by Method 3. Close examination of Table VI reveals that in many instances all three methods yield essentially the same value for the average parameters although different methods are used. Some of the parameters which agree well are n, ZAS, and fa, although fa is somwhat larger for F004 and F016. The other parameters which are shown tend to have discrepancies between the different methods. The question which arises now is which one of the methods gives the most accurate description of the sample. First let us turn to the three parameters #CA,#Cl, and RA. R Ais directly related to #CA and #C, in Method 2 and carbon-13. In samples F004 and F016, the value of RA for Method 2 is inconsistent with #CA. For instance, F004 and F014 are shown to have an average number of 2.55 and 2.95 rings, respectively, and only 8.36 and 11.33 total carbons in the aromatic ring system. Thus, these two parameters are not consistent with each other, because R A predicts a much larger #CAthan is actually determined. Likewise, there is a discrepancy in the carbon-13 method for these two parameters although not as serious as Method 2. Also in sample F004, #Cl is less than 6.0 for Method 2 and carbonANALYTICAL CHEMISTRY, VOL. 44, NO. 8, JULY 1972
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ANALYTICAL CHEMISTRY, VOL. 44, NO. 8,JULY 1972
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Figure 9. (a) Proton magnetic resonance spectrum of a normal paraffin mixture obtained from a petroleum crude (b) Carbon-13 NMR spectrum of a normal paraffin mixture obtained from a petroleum crude 13. An analysis of Equations 5, 6, 8, 9, and 11 indicates that #CA,#Cl, and R.4 are directly dependent upon f,H, and mol wt in a multiplicative manner in Method 2. Thus, iff has not been estimated properly or the hydrogen weight per cent (H) is in error or an incorrect molecular weight has been used, a true description of the aromatic composition of the sample is not given. None of these inconsistencies is observed in the Method 3 analysis although its other parameters agree with Method 2 and carbon-13. In order to remove these inconsistencies, the average molecule weight should be less, especially in the carbon-1 3 method, since upon considering Equations 16,17,18,9,11,and 12, #CA,#CI, and RA are dependent upon only the average molecular weight in addition to the integrated intensities from the carbon-13 spectrum. If, for. example, #CA and #Cl are adjusted by the factor average molecular weight Method 3/average molecular weight carbon13, then the inconsistency in the carbon-1 3 method is removed and the values of #CA and #Cl agree very closely with those of Method 3. In the case of Method 2, not only is the average molecular weight involved but the weight per cent hydrogen and average carbon-hydrogen ratio of alkyl groups (f)are involved. If the same factor of average molecular weights is applied, the inconsistency is not removed because #Cl for both F004 and F016 is less than six. In order to increase the value of #Ci, the product must be larger in Equation 8. This is reasonable since fa(2) is larger than fa(13C)and if f H were larger, then C Swould be larger according to Equation 6 and
thus C.4 or f,(2) would be reduced so that RX would be consistent with #CA. In order to separate the product f H , R s andfdetermined in the carbon-13 method must be examined. RX by this method appears to be much larger than Method 2 or 3. The proton spectrum of F004 and F016 does not indicate such a high content of naphthenic material. Since f i n the carbon-13 method is directly proportional to the ratio of the integrated intensities of the aliphatic regions of the carbon-13 and proton spectra and the carbon-hydrogen ratio as is shown in Equation 22, then by increasing the hydrogen weight per cent slightly f and Rp; would be reduced in the carbon-13 method. This indicates that in the product f H in Method 2, H is the component which should increase and not f i n order to remove the inconsistency between #CA,#CI,and RA. From this comparison and investigation of the sources of inconsistencies observed within the various methods of calculating the average parameters, the end result is that all of these methods give approximately the same average parameters provided accurate elemental analysis and average molecular weights are available for input data in Method 2 and the carbon-1 3 method. The most economical and straightforward method is Method 3 since only a proton spectrum is required to obtain the average parameters. These methods of calculating average molecular parameters of a petroleum fraction have all been developed for application to an aromatic fraction of samples. The extension of ANALYTICAL CHEMISTRY, VOL. 44, NO. 8, JULY 1972
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Figure 10. (a) Proton magnetic resonance spectrum of a non-normal paraffin mixture isolated from a petroleum crude (b) Carbon-13 NMR spectrum of a non-normal paraffin mixture isolated from a petroleum crude these methods to a sample containing both the saturate and aromatic fractions does not yield reliable information except for the aromaticity. If additional assumptions are made and the ratio of aromatic and saturate fractions is known, then somewhat reliable parameters can be determined; however, in order to determine the amount of saturates and aromatics present, separation of the two must be performed and thus the aromatic fraction can be analyzed in detail. Work is in progress to devise a means of characterizing a petroleum fraction which contains both the saturate and aromatic fraction. The wide range of carbon-13 chemical shifts as shown in Figure 7 will be of advantage here. Figure 8 compares the carbon-13 spectrum of an FCC charge stock with its proton spectrum. The peak at 216.1 ppm in the carbon-13 spectrum is due to the 13CH31reference. It is important to record both the proton and the carbon-13 spectra since the aromatic and the olefinic carbon chemical shifts overlap, but it is easy to spot olefinic protons in the lH NMR spectrum. Normally as in Figure 8 the olefin content of an FCC charge stock is minimal. 1404
ANALYTICAL CHEMISTRY, VOL. 44, NO. 8, JULY 1972
Analysis of a saturate fraction is perhaps more important since saturates often make up the bulk of many petroleum fractions. Figure 9 shows the 'H NMR and the carbon-13 NMR spectra of a mixture of Clj-C20 n-paraffins. In the carbon-13 NMR spectrum, one observes four distinct methylene carbons. Not only is the greater magnitude of the carbon-1 3 chemical shifts an advantage in structural determinations, but the I3G1Hcoupling constants can be further used to make unequivocal assignments of particular types of carbon atoms. The carbon chemical shifts of normal alkanes are known (6) and thus average carbon numbers can be determined from the integrated carbon-13 NMR spectrum of a mixture of n-paraffins. From Figure 9, the average molecular formula for this mixture is found to be This has been confirmed by GLC. Figure 10 provides additional dramatic illustration of the fact that much more information concerning (6) D. M. Grant and E. G. Paul, J . Amer. Chem. SOC.,86,2984-90 (1964).
provide a meaningful description of the particular cut in terms of the “average molecule.” The use of carbon-1 3 NMR will extend this method even possibly providing a “group-type” analysis of both the aromatic and, more importantly, the saturate cuts of a petroleum crude, in the manner of mass spectrometric group-type methods.
the composition of mixtures of isoparaffins and cycloparaffins which have been separated from a petroleum crude can be obtained from the carbon-13 spectra than from the lH spectra. Due to a lack of carbon chemical shifts available for these types of compounds, the resonances of the carbon-1 3 spectrum have not been fully assigned although certain resonances can be assigned to terminal methyl groups and methylene groups upon comparing the carbon chemical shifts of Figures 9 and 10.
ACKNOWLEDGMENT
CONCLUSION
Grateful acknowledgment is made of efforts of W. E. Magison who recorded the ‘H magnetic resonance spectra and J. E. Mogush for writing the computer programs.
The Method 3 analysis presented here is a new superior method of analyzing the IH NMR spectra of aromatic cuts of petroleum crudes. The average parameters obtained
RECEIVED for review November 5, 1971. Accepted March 7, 1972.
The K-Nearest Neighbor Classification Rule (Pattern Recognition) Applied to Nuclear Magnetic Resonance Spectral Interpretation B. R. Kowalski and C. F. Bender Lawrence Liwrmore Laboratory, Unioersity of California, Licermore, Calif. 94550 The first application of pattern recognition to NMR data demonstrated a direct route from spectrum to molecular structural information, thereby eliminating the interpretation of chemical shifts and coupling constants. Spectra were converted to pattern vectors using the autocorrelation function to remove the translational spectral shifts produced by shielding and solvent effects. A Computerized Learning Machine, which has also been applied to mass, infrared, and gamma-ray spectra, used a training set of spectra of known molecular structures to determine a decision rule which was used to classify unknown spectra according to molecular structure. In this paper the K-Nearest Neighbor Classification Rule is used to analyze NMR pattern vectors. The method has a firm statistical foundation and does not suffer from a non-uniqueness problem. Results are presented and the advantages of this method over the Feedback Learning Machine method are discussed.
THEFIRST APPLICATION of Pattern Recognition to NMR data ( I ) demonstrated a direct route from spectrum to molecular structural information, thus eliminating detailed studies of chemical shifts and coupling constants. The pattern recognition method used for the study was a linear learning machine employing least-squares and a threshold logic unit (TLU). Applications of learning machines to other types of spectrometric data have used learning machines with TLU’s and negative feedback (2-5). Spectra are treated as points in an n-dimensional space where n is the number of intensity measurements made when the spectrum is digitized. The mea(1) B. R. Kowalski and C. A. Reilly, J. Phys. Chern., 75, 1402 (1971). (2) P. C. Jurs, B. R. Kowalski, and T. L. Isenhour, ANAL.CHEM., 41, 21 (1969). (3) B. R. Kowalski, P. C . Jurs, T. L. Isenhour, and C . N. Reilley, ibid.,p 1945. (4) L. E. Wangen and T. L. Isenhour, ibid., 42, 737 (1970). ( 5 ) T. L. Isenhour and P. C . Jurs, ihid., 43 (lo), 20A (1971).
surements serve as the n coordinates that position each point (spectrum) in the n-space. Some of the points are “tagged” with known classifications and collectively comprise a training set. In the two-class problem, the learning machine determines a hyperplane that divides the n-space so that points from different classes are separated. Unknown points can then be classified according to which side of the plane they are found. The TLU (6) essentially indicates which side of the hyperplane a point lies. Most of the spectrometric work uses the negative feedback approach for finding the hyperplane, and therefore this paper addresses the problems associated with the feedback learning machine. Many of the points covered hold true for the least-squares solution as well. NMR spectra preprocessed with the autocorrelation function (1) serve as the data base for this study. While the main goal of this paper is to advance the effectiveness of using pattern recognition methods to analyze NMR and other types of spectra, another objective is to examine some of the important drawbacks of using the learning machine for data analysis. A viable alternative, the K-Nearest Neighbor Classification Rule, will be introduced and some of its extensive theory presented. Investigation of the Feedback Learning Method. In the following, it is assumed that a suitable training set of known spectra is available and that the goal is t o classify unknown spectra according to molecular structure parameters. For instance, the goal might be to divide a training set of NMR spectra into two groups; those containing a certain functional group (e.g., CHa CH2 CH,) and those that do not. It is also assumed that the spectra have been digitized and that all necessary transformations have been applied to each spectrum in order to generate a list of features that can be used for classification. (In some cases no transformation is necessary, (6) N. J. Nilsson, “Learning Machines,” McGraw-Hill, New York, N.Y., 1965.
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