1502
Anal. Chem. 1904, 56, 1502-1507 Campbell, M. J.; Sheppard, J. C.; Au, B. F. Geophys. Res. Lett. 1979, 3 , 175. Mihelcic, D.; Ehhalt, D. H.; Kulessa, G. F.; Klomfass, J.; Trainer, M.; Schmidt, A.; Rohrs, H. Pure Appl. Geophys. 1978, 116, 530. Watanabe, T.; Yoshida, M.; Fujiwara, S.;Abe, K.; Onoe, A.; Hirota, M.; Igarashi, S. Anal. Chem. 1982, 54, 2470-2474. Wendel, G. J.; Stedman, D. H.; Cantreli, C. A.; Damrauer, L. D. Anal. Chem. 1983, 55,937-940. Maeda, Y. K.; Aoki, K.; Munemori, M. Anal. Chem. 1980, 52, 307-3 11. Cantrell, C. A.; Stedman, D. H. Geophys. Res. Lett. 1982, 9 , 846-849. Stedman, D. H.;Cantrell, C. A. Second Symposium on the Composition of the Nonurban Troposphere, Williamsburg, VA, May 25-28, 1982. Demore, W. 6.; Watson, R. T.; Golden, D. M.; Hampson, R. F.; Kurylo, M.; Howard, C. J; Molina, J. J.; Ravlshankara, A. R. JPL Pub/. 1982, 24-33, 88-89. Atklnson, R.; Pitts, J. N., Jr.; Winer, A. M. Presented at the American Chemical Society National Meeting, Washington, DC, August 28-September 2, 1983.
(21) Hard, T. M., Portland State Unlverslty, private communication, 1982. (22) Blackburn, T. E.; Stedman, D. H. "Solar Photolysis Frequencies for Ozone to O('D) Atoms"; Regional Conference of the American Chemical Society, Midland Division, Midland, MI, June 1982. Calvert, J. G. NATO Adv. Study Inst. Chem. Poll. Unpoll. Tropo(23) sphere 1981. (24) Logan, J. A.; Prather, M. J.; Wofsy, S.C.; McElroy, M. 6. J . Geophys. Res. 1981, 886, 7210-7254. (25) Chameides, W. L.; Davis, D. D. J . Geophys. Res. 1982, 87, 4863-4677. (26) Gormley, P. G.; Kennedy, M. Proc. R . I r . Acad., Sect. A 1949, 52A, 163- 169.
RECEIVED for review October 6, 1983. Accepted March 19, 1984. We thank the Environmental Protection Agency for support of the laboratory studies under Grant No. R80870601-0* The Center for Atmospheric Research is supported by The National Science Foundation.
Theoretical and Experimental On-Line Analysis of Multistate Melting of Polymers by Differential Scanning Microcalorimetry Lee-Hong Chang, Shi-Jiang Li,' Tom L. Ricca, and Alan G. Marshall*'
Department of Chemistry, T h e Ohio State University, Columbus, Ohio 43210
The temperature and power output voltages of a Microcai MC-1 differential scannlng calorimeter (DSC) have been conditioned, dlgitized, and coded In RS-232 format for reaitime display and subsequent analysis wlth BASIC language programs by an Apple I I Plus microcomputer. From a menu on the display screen, the user may scale the DSC data, flatten the base line, smooth the data wlth a seven-point aigorlthm, and then analyze the resulting curve Into as many as 10 component peaks. CURFIT simulation Is based upon exact solutlon of a thermodynamic two-state equllibrlum meltlng model for each component phase transition. Various exact and approximate methods for extracting the melting mldpolnt, ,T, and molar enthalpy of melting, AH, are compared for four theoretical combinations of T, and AH. For experlmentai DSC data (0.64% cytochrome c, 0.88% ribonuclease A, and 0.30 mM equimolar mixture of the two proteins), the apparatus and methods yield more consistent and accurate T, and AH values than are obtained from the usual direct output of the DSC data from the calorimeter to an analog x-y recorder. Moreover, because the dlgitlzed raw data are stored on a floppy dlsk, a given DSC scan can be reanalyzed according to several different choices of temperature range and/or number of component transitions. Typical simulations require about 10 min of execution time. Full details of all hardware and software are available on request.
With the advent of commercial instruments of high sensitivity and routine operation, differential scanning calorimetry (DSC) has become increasingly popular for characterizing phase transitions in polymers. In this paper, we present two
principal improvements in DSC analysis. First, the melting midpoint, T,, and the molar enthalpy of melting, AH, are obtained by fitting the full DSC peak shape to a thermodynamic two-state phase transition model. Previous estimates of T, and AH have been taken either from the temperature and height of an observed DSC peak maximum (1) or from a Gaussian approximation to the thermodynamic peak shape (2, 3). Second, the DSC output is digitized and stored in a microcomputer, where it can be manipulated (e.g., digitally filtered, base-line corrected, analyzed into component transitions, etc.). The theoretical model is tested by simulating both theoretical and experimental DSC profiles for two or more overlapping phase transitions.
EXPERIMENTAL SECTION Temperature-Dependence of a Two-State Equilibrium. It is useful to begin by assembling the definitions and assumptions underlying any attempt to simulate experimental DSC data. The first assumption is that each component melting process can be treated as a two-state equilibrium, in which A and B are the unmelted and melted species (e.g., native and denatured forms of a polymer).
A=B Keq
= [Bl/ [AI
where
Keg= exp(-AH/RT) exp(AS/R)
State University.
0003-2700/84/0356-1502$01.50/0
(2)
in which Kq is the equilibrium constant, AH and A S are the molar enthalpy and entropy of melting, R is the gas constant, and T is absolute temperature. The fraction melted, 8, can then be defined as (3) 8 = [BI/([Al + [BI) It is readily shown that 0 = Keq/(l + Keq)
Also a member of the Department of Biochemistry, The Ohio
(1)
so that 0 1984 American Chemical Soclety
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ANALYTICAL CHEMISTRY, VOL. 56, NO. 8, JULY 1984
+
1 - 0 = 1/(1 Keq)
Combining eq 2 and 4a yields exp(-AH/Rn exp(AS/ R) 0 = 1 + exp(-AH/RT) exp(AS/R)
(4b)
1503
for the height and width of the DSC peak for a two-state melting transition. The maximum DSC peak height is found by setting the slope of dq,/dT equal to zero
(5)
At the melting midpoint, 0 = ll2,T = T,, Kep= 1,and A S = AHIT,. Equation 5 can thus be rewritten
Solving for 0 0 =
If AH and A S are independent of T, then the temperature dependence of 0 is given by
'/z - (RT/AH)
(14)
The exact temperature at the DSC peak-height maximum can be obtained by substituting eq 14 into eq 6 and solving for T. However, since biological polymers typically melt at 290 K < T, < 350 K, with 10000 cal mol-' < pH < 150000 cal mol-' per component, a typical value of R T / M = (2 cal mol-' K-') (320 K)/(40000 cal mol-l) = 0.016. Thus, to a good approximation (namely, 3.2% for 0 and 0.38 K for T, in this example) 0
Yz at (dqp/dT)max
(15)
T
Tm at (dqp/dT)max
(16)
and
Relation between de/dT and the DSC Experiment. The heat capacity at constant pressure, C,, is given by
To the same level of approximation as eq 15-17, the full width at half-maximum height of such a plot is given by AT E 3.52(RTm2/AH)
in which Hiis the molar enthalpy, n,the number of moles, and C,(i) the molar heat capacity for the ith component, and dq,(i) is the heat required to raise the temperature of the ith component by d T degrees at constant pressure. If the molar enthalpy of melting, AH, is independent of temperature, then for our twocomponent system, A and B, dq,/dT = nAC,(A) + n&,(B) + (d/dT)(n0AHl n [ ( l - O)Cp(A) + OCp(B) + W d e / d T ) I (9)
+
in which n = nA nB, n0 = n~ is the number of moles of A that had melted to become B, n(1- 0 ) = nA is the number of moles of unmelted A remaining, and CJA) and C,(B) are the molar heat capacities of components A and B. Heat capacity of the aqueous buffer solution is compensated by the reference solution in a DSC experiment and may be omitted. In a DSC experiment, the power required to keep the sample temperature the same as the temperature of the reference buffer solution is recorded as the temperature of the system increases linearly with time. The output of the instrument is thus dq,/dt vs. t. However, since dT/dt is assumed to be constant, dq,/dt is readily converted to dq,/dT dqp/dT = (dq,/dt)/(dT/dt)
(10)
The C, terms in eq 9 simply determine the base line of a plot of dq /dT vs. T and will be omitted for the time being. Equations 7 and 9 may then be combined to give
The area under a plot of dq,/dT vs. T is readily evaluated from eq 11. area =
L, dqp T2
=
nmrnelting
(12)
in which Tl > T, to ensure that all enthalpy contributions are recorded within the observed temperature range. Simulation of DSC Melting Curves. Ultimately, we will want to use the right-hand side of eq 11to fit experimental DSC plots of dq,/dT vs. T. In order to obtain initial estimates of T, and AH for such fits, it is useful to derive theoretical expressions
(18)
For example, for a true T, = 320 K and AH = 40 kcal mol-', eq 18 gives AT = 17.9 K, compared to a true AT = 17.8 K from numerical iteration of eq 11. Similarly, the true maximum of dqp/dT vs. T occurs at (T, - 0.38 K) rather than at T,. Sample Preparation. Cytochrome c and ribonuclease A were purchased from Sigma and Boehringer Mannheim and used without further purification. DSC samples were prepared according to the method of Privalov and Khechinashvili ( I ) . Protein concentrationswere determined by UV/vis absorbance (Beckman DU-8 spectrophotometer) by using known extinction coefficients for the two proteins ( I ) . The cytochrome c sample was 0.64% w/v, and the ribonuclease A sample was 0.88% w/v. A third sample containing both proteins was 0.30 pmol mL-' in each. Protein aggregation was minimized by adjusting pH (MI412 microcombination pH probe) to 4.5 at 24 "C in 0.04 M glycine buffer. DSC Data Collection. DSC measurements were conducted according to the manufacturer's recommended procedures (Microcal MC-1 differential scanning microcalorimeter,equipped with Welch Duo-Seal Model 1400 vacuum pump, with liquid cells of 0.7 mL effective volume). Each protein sample was referenced against the same volume of buffer. The reported scan rates were measured directly and were generally 20% larger than the nominal scan-rate reading from the MC-1 control panel. Once an MC-1 scan begins, all remaining operations are controlled by an Apple I1 Plus microcomputer (64K RAM, with an Apple Super Serial card). Although not essential, the use of a Saturn Systems Inc. Accelerator I1 card speeds computations by a factor of 3. The Apple waits until a previously specified lower temperature (say, 30 "C) has been reached, and then begins acquiring data. At specified temperature intervals (say, every 0.1 "C), the thermocouple ( x ) and differential heating output (y) voltages from the MC-1 are conditioned to 0-2 V, digitized by an 11-bit analog-to-digitalconverter, and sent to the RS-232 port of an Apple I1 Plus microcomputer (see Appendix). A BASIC program for the Apple (see below) then scales each voltage-voltage pair to a temperature-cal/min pair and displays the DSC data on a monitor screen as the scan progresses. When the upper temperature limit is reached, the Apple computes the true scan rate, rescales the data as temperature-cal mor1 deg-' pairs, and stores the complete data set on a floppy disk. Computer Software. Because of the limited working memory of the Apple 11Plus, not all of the desired operations can be called from a single program resident in core memory. Therefore, a menu is provided for selection of individual interactive Applesoft BASIC
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ANALYTICAL CHEMISTRY, VOL. 56, NO. 8, JULY 1984
Table I. Melting Midpoint (Tm)and Molar inthalpy of Melting (AH)for a Theoretical Two-State Equilibrium Melting Process, Estimated from Various Treatments of a DSC Plot of dq,/dT vs. T (see Figure 1)
Tm, “C 41 4 1e 80f 8 0g
AH, cal/mol 40 60 40 60
000 000 000 000
T, from T, from actual DSC center of AH from DSC peak center best-fit Gaussian peak areaa 46.62 46.88 79.62 19.15
40 000 60 000 40 000 60 000
46.88 46.94 19.83 19.92
e Equation 1 2 . Equation 19. Equation 20. Corresponds to Figure l a . responds to Figure IC. Corresponds to Figure I d .
AH from DSC peak height and centerb 39 59 39 59
e
AH from DSC peak width and centerC
974 988 976 975
39 60 39 60
918 139 894 021
Corresponds to Figure l b .
Cor-
--
language programs for data acquisition (DSCACQ), curve simulation (DSCCURFIT), and plotting (DSCPLOT). During system start-up, the Accelerator I1 card is activated and shape tables of alphanumeric characters and symbols are loaded in memory addresses 36 94638400, for later use in labeling of graphs. High memory is then set below 36 946. A menu is then installed to direct traffic among the various programs. Program listings of the three programs are available on request. DSCACQ captures digitized MC-1 signals from the analog-todigital converter and saves the data for later manipulation. DSCCURFIT performs curve simulation and deconvolution of the acquired data. For example, a set of 500 data pairs can be deconvoluted into up to 10 component peaks, fitted to eq ll. DSCPLOT plots curves (in up to seven colors, if desired) in a format defined by the user. It can also superimpose experimental, simulated individual component, and/or a sum of simulated-component curves and perform screen dump to an Integral Data Systems Prism printer/plotter. Typical parameter printouts and graphs may be found in Results and Discussion. All supporting subroutines are based on published algorithms. Marquardt’s CURFIT algorithm ( 4 ) has been adapted to fit experimental DSC data to eq 11,including deconvolution of the data into as many as 10 component peaks. Savitzky-Golay seven-point data smoothing is based on a cubic-fitting function (5). For base-line tilting, a line is drawn between the averages of the five left-most and five right-most C, values in the selected temperature range. Finally, Simpson’s rule with a quadratic fitting function (6) is used for numerical integration of the DSC curve.
RESULTS AND DISCUSSION Extraction of T, and AH from DSC Data: Theoretical Models. The principal parameters to be extracted from DSC analysis are T, (half-melted temperature) and AH (enthalpy of melting) for each component DSC peak. Representative theoretical plots of dq,/dT vs. T for an equilibrium two-state melting model (eq 1 and 11) are shown in Figure 1 for four combinations of T, and AH, along with the best-fit Gaussian approximation ( 2 , 3 )to each curve. Note that the symmetric Gaussian peak deviates noticeably from the more accurate asymmetrical line shape of eq 11. A quantitative comparison of the curves in Figure 1 may be found in Table I. The left-most entries in Table I are the “true” T, and AH that would be obtained by fitting a theoretical two-state melting DSC curve to eq 11. To a good approximation (see Figure 1 and Table I), T, is given by the temperature at the observed maximum (or the best-fit Gaussian maximum) of a plot of dq,/dT vs. T. However, there are at least four ways to estimate AH: (a) curve fitting of the entire DSC curve to eq 11;(b) integration of the full DSC curve; (c) combination of observed DSC peak height and center using eq 19 (2); and (d) combination of observed DSC peak width and center using eq 20 (corrected from the approximation in ref 7 ) . For a single two-state phase transition, a and b are exact and c and d are excellent approximations (see Table I). Experimentally, close agreement (say, to within &5% between A H values obtained by direct integration of the DSC curve (eq 12) and by curve fitting to eq 11)constitutes strong evidence for a single two-state phase
a
I
b I
d
1 I
Figure 1. Theoretical DSC curves (dq,ldTvs. T ) for a single twestate equilibrium melting process: dotted curves, exact formula (eq 11); solid curves, Gaussian best fit to eq 11. (a) T , = 320 K, AH = 40 000 cal mol-’ K-’. (b) T, = 320 K, AH = 60 000 cal mol-‘ K-’. (c) T, = 353 K, A H = 40000 MI mol-’ K-‘. (d) T , = 353 K, AH = 60 000 cal mot’ K-I. Maxima for the two curves (shown by vertical lines) are listed in Table I.
transition. Similar arguments have previously been advanced for the use of approximations to eq 11 ( I ) . mmelting
AHmelting
= area/n
(12)
3.52RTm2/AT
Extraction of T, and AH from DSC Data: Experimental DSC Curves. Figures 2a-4a show experimental DSC curves for dilute ( e l % wt/vol) aqueous solutions of cytochrome c, ribonuclease A, and an equimolar mixture of the two proteins. These two proteins were chosen because they have previously been shown to melt reversibly, with large AHmelting, in what appears to be a single stage ( I ) , and because they are not expected to interact when mixed together at these concentrations. The high sensitivity of the MC-1 instrument is apparent from the good signal-to-noise ratio obtained for the raw data from such polymers. This high sensitivity is accomplished at the expense of sample size: each scan requires about 0.7 mL of sample, compared to about 0.04 mL for most other commercial DSC instruments. Compared to similar curves (not shown) obtained from direct analog output to an x-y recorder, the base line of the digitized DSC data is flatter, In analog detection, the x-y recorder time constant is large in order to reduce noise, and the base line and peak shapes can be distorted during the DSC scan. In contrast, no analog filtering is required when the DSC data are routed directly to the microcomputer, because the
ANALYTICAL CHEMISTRY, VOL. 56, NO. 8, JULY 1984
1505
rl
35 40
59
69 79 80 TEMPERATURE 'C
90
70 30
lB0
50 60 70 TEMPERATURE
40
11
9M
80 (
OC)
(
OC)
180
14F
I
55
I
I
I
I
I
70 75 80 85 TEMPERATURE ( O C )
90
I
65
60
6 45-
95
Flgure 2. DSC curves for cytochrome c: (a) digitized raw data, with uncalibrated y axis: scan rate, 60 OC h-' nominal, 71.6 'C h-' actual; y axis sensitivity, maximum; (b) dotted cuwe, data have been scaled and smoothed and the base-line flattened; solid cuwe, best-fit to two-state melting process (eq 1l), with fit parameters listed in Table 11.
56
55
60 65 76 TEMPERkTURE
75
80
85
90
Flgure 4. DSC curves for equimolar mixture of cytochrome c and ribonuclease A. Format is the same as for Figure 2, except for scan rate of 60 OC h-' nominal, 71.5 OC h-' actual. The experimental curve has been simulated by the sum of two best-fit components (computed from eq 11).
Table 11. Melting Midpoint (T,) and Molar Enthalpy of Melting (AH) Obtained from Theoretical Best Fits of Eq 11to Experimental DSC Curves for Dilute Aqueous Protein Solutions
AH: kcal cytochrome c ribonuclease A equimolar mixture of both proteins a
13h
ii-
b
w
-I
D E
\ -I
7-
a
c)
Y
"
a u
3-
-11 45
I
50
I
I
I
55 60 65 TEMPERkTURE ( O C )
I
70
1
75
Flgure 3. DSC curves for ribonuclease A. Format is the same as for
Figure 2, except for scan rate of 60 OC h-' nominal, 72.0 OC h-I actual.
data can be smoothed digitally after acquisition. The elimination of base line distortion is a major advantage of digitized data acquisition.
From DSC area.
AH,^ kcal
T,, "C
mol-'
mol"
75.3 62.2 60.3 and 76.3
99.3 116.2 199.6
92.7 111.9 107.4 and 91.0
From best fit to eq 11.
Since DSC signal-to-noiseratio is directly related to the rate at which the temperature is scanned, it is desirable to work at the maximum possible scan rate. However, if the scan rate is too fast, equilibrium is not reached during the scan, and a distorted DSC curve will be obtained. In the present experiments, the DSC curves for the same sample run at two different scan rates were indistinguishable. Therefore, the data from the higher scan rates are reported in Figures 2-4. The base line of an experimental DSC plot almost always exhibits a non-zero slope. Apart from small differences in specific heat capacity between sample and reference, or between unmelted and melted polymer, any difference in absolute mass of the sample and reference will require a differential power required to raise the temperature of the two cells by the same amount. It is therefore necessary to tilt the base line of experimental DSC curves, using reference temperatures near the low and high temperature limits of the scan. In addition, data smoothing is appropriate when (as in these cases) the thermal phase transitions are relatively broad (10-20 "C). The dotted curves in Figures 2b-4b show the effect of base-line tilting and seven-point Savitzky-Golay smoothing on the raw data of Figures 2a-4a.
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ANALYTICAL CHEMISTRY, VOL. 56, NO. 8, JULY 1984
VI
J4
CD40ll 74LSOO
J 5 CD4002 U 6 74L510
U7 C D 4 0 5 1
3 nz. 7iQ XTAL
- 8“
7905
-5
5Y ~
__ -
~
_ _ _
.
.“
I
_-
-1
Figure 5. Circuit description of the DSC/microcomputer interface.
The reduced DSC data of Figures 2b-4b were then subjected to CURFIT analysis based on eq 11. The results are shown as the solid curves in Figures 2b-4b, and the best-fit parameters are listed in Table 11. AH obtained from the integrated area under the DSC curve is compared to AH from a best fit of the DSC curve to eq 11, as a test of the two-state melting model (see below). The fitting algorithm typically takes about 2 min per iteration and reaches a final best fit (variance constant to within about 1 part in 109 after four to six iterations. For cytochrome c or ribonuclease A alone, the “truen AH obtained from the DSC area is 4-7 % larger than that obtained by fitting the data to a theoretical two-state model. This small but real difference is in the same direction for both proteins and can be ascribed to a combination of the following: presence of multiple DSC peaks (due to multistage melting); invalidity of eq 11 (due to cooperative melting, scan rate too fast to permit establishment of equilibrium at each temperature, variation of AHmeltbwith temperature); and a difference in heat capacity between unmelted and melted forms (change in base-line slope on passing through the DSC peak). Such problems have been discussed elsewhere (8, 9). More important, there is as excellent an agreement between the T , and AH values obtained for the two-protein mixture as for the individual proteins alone. Since T, and AH for both proteins are highly pH dependent (I), the observed discrepancies are most likely due to small differences in pH between the individual protein samples and the mixture. In summary, the combination of an Apple I1 Plus microcomputer with an Apple Super Serial card (ca. $200) and about $100 worth of additional hardware provides for simple, automated acquisition and analysis of DSC curves. The same methods can be applied with minor modifications to other calorimeters or microcomputers. The results provide linear base lines, with provision for base-line flattening, data smoothing, and simulation of DSC curves containing up to
10 independent melting transitions.
ACKNOWLEDGMENT We thank J. F. Blazyk for helpful comments and suggestions. APPENDIX: DSC/MICROCOMPUTER INTERFACE A circuit diagram for the DSC/microcomputer interface is shown in Figure 5. The relatively slowly varying voltage signals, x h and yb, are conditioned to vary between 0 and 1.999 V by U7 and related components. At each clock pulse selected by the sampling rate selector, one value of xi, is digitized in about 50 ms and transmitted in about 70 ms to the computer in the form of four ASCII codes. One value of yin is then processed in about the same length of time. Consecutive processing of xin and yin is appropriate because the rate of change of xi, and yin is slow compared to the time required to process each signal. Operation of the interface will now be discussed. Closing of SW1 stops analog-to-digital conversion and transmission of data to the computer. When SW1 is opened, the trailing edge of a clock pulse at pin 11of U4 causes U13a to set, U13b to reset, and U3b to set. U3a remains reset. CLKEN is active and enables the clock built around U2. ADCLK assumes a frequency of 307.2 kHz (for fast conversion at chip U8), and SELECT is low; U7 thus routes x,, to input 3 of the analog-to-digitalconverter U8. After analog-to-digital conversion, pin 11of U3a briefly goes high and the frequency of ADCLK is reduced to 1200 Hz to provide for sufficiently slow strobing of the “three and one-half” digits of the x i , value. The first digit is the so-called ”half-digit” (which can be only 0 or 1)and its sign, encoded globally as a 4-bit nibble by the chip U8. This nibble is automatically associated with another special nibble and strobed into the UART U9 and is converted via serial voltage pulses at pin 25 of U9. These pulses are in
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Anal. Chem. 1984. 56. 1507-1514
turn converted into current-loop pulses for reliable distant transmission by U5, transistor 2N3906, and optoisolator 4N33. The remaining BCD digits of xinare then processed. STEP goes high, so that SELECT goes high and U3 is reset. U7 then selects yin,and its three and one-half digits are processed as for xin. Except for the last BCD digit of yin, each nibble coming from pin 20 to 23 of U8 is attached to a special nibble of 0011 on the most significant side of the 8-bit byte input of UART U9. Each whole-digit byte thus becomes a hex code 30-39 (which corresponds to an ASCII of “O”-‘9”). It also makes each half-digit byte into a hex code from 3A to 3F (ASCII, u.n-u?n . . ). The specifications of chip U8 provide details for reconstruction of xin and yinat the computer. Pin 6 of U14 goes low only for the last whole digit of yin, changing the above-mentioned special nibble into 0010. The acquisition program thereby monitors this digit according to lines 1090-1100 so that acquisition always begins with xin. Lines 1190-1200 restore the special nibble for this digit to 0011 for further processing. Following analog-to-digital conversion of yin,STEP goes high, making END low and CLKEN high. Conversion and transmission then halt until arrival of the next pulse from the sampling rate generator at pin 11 of U4.
The parameters of UART to be specified by the computer RS-232 interface are as follows: 1200 baud; 8 data bits; 1stop bit; no parity. +V is connected to +5 V of the RS-232 interface, and pin 3 and 7 of the DB25 connector of the interface are connected to the transistor leads of 4N33 as shown. Registry No. Cytochrome c, 9007-43-6; ribonuclease A, 9001-99-4.
LITERATURE CITED Privalov, P. L.; Khechinashvili, N. N. J . Mol. Biol. 1974, 8 6 , 665-684. Privalov, P. L.; Filimonov, V. V.; Venkstern, I. V.; Vayev, A. A. J . Mol. Biol. 1975, 9 7 , 279-288. Schott, F. J.; Grubert, M.; Wangler, W.;Ackermann, Th. Biophys. Chem. 1981, 14, 25-30. Bevington, P. R. ”Data Reduction and Error Analysis for the Physical Sciences”; McGraw-Hill: New York, 1969; pp 235-242. Savitzky, A.; Golay, M. J. E. Anal. Chem. 1964, 3 6 , 1627-1639. Bevington, P. R. “Data Reduction and Error Analysis for the Physical Sciences”; McGraw-Hill: New York, 1969; pp 265-271. Privalov, P. L.; Khechinashvili, N. N.; Atanasov, B. P. Biopo~mers 1971, 10, 1865-1890. Jackson, W. M.; Brandts, J. F. Biochemistry W70, 9 , 2294-2301. Krishnan, K. S.; Brandts, J. F. Methods Enzymol. 1978, 4 9 , 3-14.
RECEIVED for review December 14,1983. Accepted March 22, 1984. This work was supported by a grant to A.G.M. from the U.S.A. Public Health Service (NIH 1R01 GM-29274-03).
Postcolumn Addition of Buffer for Thermospray Liquid ChromatographylMass Spectrometry Identification of Pesticides Robert D. Voyksner,* Joan T. Bursey, and Edo D. Pellizzari Analytical and Chemical Sciences, Research Triangle Institute, P.O. Box 12194, Research Triangle Park, North Carolina 27709
Coaxlai and right-angle tees were evaluated as methods of postcoiumn buffer addition for thermospray LC/MS analysis. The coaxial tee, which showed dlghtiy better total ion current stability, was optimized to produce the best sensitivity. This tee was used together with a gradient LC separation to obtain thermospray LC/MS spectra for 15 carbamate and urea pesticides. The detection limits for these pesticides are also reported.
Carbamate pesticides have high usage in the United States by virtue of their high effectiveness and low mammalian toxicity ( I , 2). The ability to separate and identify these pesticides is important because of their increasing presence in the environment, along with their degradation and metabolic products. Analytical procedures for determination of these pesticides are rather limited. The pesticides are thermally labile which prevents direct analysis by gas chromatography. Spectrometric methods lack specificity or sensitivity (3-5). Although high-performance liquid chromatography (HPLC) is ideally suited for carbamate separation, mass spectrometry is appropriate for their detection. Liquid chromatography/mass spectrometry (LC/MS) has developed several approaches to overcome the problems as-
sociated with coupling the effluent of the LC to the source of a MS, including moving belt (6),direct liquid introduction (9, thermospray (€9,atmospheric pressure ionization (9),and semipermeable membrane (10). Although the moving-belt and direct liquid introduction (DLI) interfaces have been used in the analysis of carbamates (11-16), these techniques have been hampered by either lack of sensitivity or thermal degradation of the sample. The DLI interface usually requires a 1/100 split, and the moving belt requires the sample to be thermally desorbed from a surface and sometimes requires a split depending on the solvent system used. On the other hand, thermospray LC/MS does not require splitting the LC effluent or thermal desorption. Thermospray (TSP) is also an ionization technique, the exact nature of which is still being investigated (17, 18). In qualitative appearance, the spectra resemble field desorption and ammonia chemical ionization spectra (17). The ionization process requires that a volatile buffer be present in the LC effluent. The most commonly used buffer has been ammonium acetate; however, others have been reported (18). Most LC separations are developed before consideration of the use of mass spectrometry as a detector. This situation poses a problem for TSP LC/MS analysis since a separation scheme which has already been developed cannot be used unless ammonium acetate or an equivalent buffer is present for ion formation. If a buffer is added to accommodate the
0003-2700/84/0356-1507$01.50/00 1984 American Chemical Society
