Data-blocking cross-correlation peak detection in computerized gas

Oct 1, 1980 - Data-blocking cross-correlation peak detection in computerized gas ... Kristin H. Jarman , Don S. Daly , Kevin K. Anderson , Karen L. Wa...
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Anal. Chem. 1980, 52, 38-43

LITERATURE CITED (1) E. J. Shellard and M. 2.Alam, J . Chromtogr.. 32, 472 (1968);33, 347 (1968);35, 72 (1968). (2) J. D. Phillipson and S. R. Hemingway, J . Chromtogr., 105, 163 (1975). (3) S. Hara and K. Mibe, Chem. Pharm. Bull., 23, 2850 (1975). (4) S. Hara, J . Chromatogr., 137, 41 (1977). (5) G. H. Jolliffe and E. J. Shellard, J . Chromafogr., 81, 150 (1973). (6) S. Gorog, B. Herenyi, and K. Jovanovics, J . Chromafogr., 139, 203

(1977). (7) D. G. I. Kingston and B. T. Li, J . Chromatogr., 104, 431 (1975) (8) L. R. Snyder, Anal. Chem., 46, 1384 (1974). (9) E. Soczewinski, Anal. Chem., 41, 179 (1969).

(10) S. Hara, Y. Fujii, M. Hirasawa, and S.Miyamoto, J . Chromatogr., 149, 143 (1978). (11) S. Sakai, Heterocycles, 4, 131 (1976). (12) J. Haginiwa, S. Sakai, N. Aimi, E. Yamanaka, and N. Shinma. Yakugaku Zasshi, 93, 448 (1973). (13) N. Aimi, E. Yamanaka, N. Shinma, M. Fujii, J. Kurita, S. Sakai. and J. Haginlwa, Chem. Pharm. Bull., 25, 2067 (1977). (14) D. Ishii, K. Asai, K. Hibi, T. Jonokuchi, and M. Nagaya, J . Chromatogr., 144, 157 (1977). (15) C. L. Guillemin, J . Chromatogr., 158, 21 (1978).

RECEIVED for review June 26,1979. Accepted August 23,1979.

Data-Blocking Cross-Correlation Peak Detection in Computerized Gas Chromatography-Mass Spectrometry Wm. F. Bryant,"' M. Trivedi,' B. Hinchman

IV,'

and S. Sofranko'

Pharmaceutical Division, Pennwalt Corporation, P.O. Box 1710, Rochester, New York 14603

P. Mitacek, Jr. Department of Chemistty, St. John Fisher College, Rochester, New York 14618

A new method for the detection of mass peaks in digital data records Is reported. Both a cross-correlation detection function, D,, (subroutine CROSS) and a data-blocking procedure based on the use of a threshold comparator and a digital clock (subroutine CTIME) may be used in processing data for a glven scan. Program LOCPK combines these methods so that each is used as required by the complexity of the dlgltal record. CROSS employs a previously unused property of D , to locate peaks through simple sign checking. The performance of the combined method can be verified using an option which caused CROSS to be used exclusively. Major advantages available through LCCPK include the substantial reduction of the average rate of data transmission, the reduction of computer processing time requirements, and the production of mass spectra comparable in quality to those produced by cross-correlation analysis alone.

A major challenge in the development of algorithms for identification of spectral information in on-line gas chromatography -mass spectrometry (GC-MS) involves the accurate, sensitive, and rapid detection of mass peak profiles. The common approach to peak detection in digital records generally consists of several steps. First, an intensity threshold is specified by either software or hardware methods. A minimum number of digital samples above the threshold is then required to define the beginning of a legitimate peak. Similarly, the end can be located by requiring some minimum number of samples below threshold. When these conditions are met, a mass peak is recognized and further processing is required to determine location and response (1-4). Another method for peak detection has been reported by Bell (5,6). This involves the use of cross-correlation analysis wherein the digital record is examined to locate experimental signals similar in shape to that of a reference (7,8). According to Bell, a suitable reference shape for skewed quadrupole peaks is given by the integer sequence: 1, 3, 4,3, 2, 1. Cross-corDepartment of Analytical Chemistry. 2 D e p a r t m e n t of Computer a n d Statistical Operations. 0003-2700/80/0352-0038$01 .OO/O

relation analysis may be accomplished in practice using Equation 1. m-1

C

Cr =

(fltk)t+r

(1)

t=O

For the indicated integer sequence, this reduces to Equation 2 where C, is the discrete cross-correlation function and g represents the digital ion current values. (2) C r = go + 3g1 + 4g2 + 3g3 + 2g4 + g5 When the experimental and reference signals match closely, C, rises sharply to indicate the presence of a mass peak. Bell was also able to utilize a noise suppression procedure developed by Black (9). The effect of noise on C, can be reduced by subtracting the average of the stored digital samples from each digital value. When six digital values of the ion current are used, as in Bell's method, the average employed in background subtraction, A,, is: 1/6(g0 + gl + g2 + g3 + g4 + g5). Subtracting A , from Equation 1 gives the modified cross-correlation function shown in Equation 3. m--1 DT

=

t =o

( f i t ik)t+T-

(3)

In this form it is used as a detection function and D , is substituted for C,. Equation 3 may be more readily appreciated when viewed in the reduced form. The detection function may be rewritten as shown in Equation 4 if the indicated integer sequence is employed. D , = -go + g1 + 2g2 + g3 - g5 (4) The simplicity of this detection function is apparent; consequently, it is well suited for efficient use in computer processing. Other advantages which have been noted for this method are that cross-correlation analysis provides more accurate mass and abundance values, better immunity from noise, and an increased dynamic range (6). During the development of a real-time data acquisition system involving both selected ion monitoring and repetitive mass scanning capabilities, we found it advantageous to modify Bell's method and to combine it with hardware thresholding of the electrometer signal. The resulting method utilizes the computer program LOCPK. Details of this method are pres-

C 1979 American Chemical Society

ANALYTICAL CHEMISTRY, VOL. 52, NO. 1, JANUARY 1980 ELECTROMETER

39

1” +

c

FILTER

rn hl I

( 1 N T E R F A C E ) N IPU RT+ E$F

I L

REF

++-

.

+ 5

I

-

OU T TTPLU T OUTPUT

I

I ~

D A T A BUS

I

CONTR.

-

1

I I

I TIC

I

INTEGR.

I

I

I

I

I

L I

DATA

BUS:

T O

+

COMPUTER

Figure 1. Schematic diagram of the computer interface: (1) Input: linear voltage ramp proportional to m l z ; (2) Input: signal from MS

ented. T h e performance of LOCPK is discussed.

EXPERIMENTAL Mass Spectrometer. The idstrument employed in this study includes a quadrupole mass filter (Model 4-162-8) and associated control equipment manufactured by Extranuclear Laboratories, Inc. The mass filter was modified by the manufacturer to accept an E1 source and a 16-stagecopper/beryllium multiplier supplied by the R. M. Jordan Co. The vacuum system, including manifold and pumps, is from a Quad-2100 mass spectrometer originally supplied by a division of Electronic Associates, Inc. Samples were introduced via a Hewlett-Packard gas chromatograph (Model 5750) using 180 cm X 2 cm i.d. glass columns packed with 3% OV-225 on 100/120 mesh Chromosorb W. The column oven was maintained at 115 “C, the injection port at 260 “C, and the glass, vinylmethylsilicone membrane separator at 220 “C. The helium carrier gas flow was 8 mL/min. An electron energy of 70 eV was used throughout the study with an ion energy and focus potential of 7 V and 40 V respectively. The quadrupole controller was operated in the constant AM mode. Computer. The mass spectrometer is interfaced to a nondedicated computer manufactured by Digital Scientific Corporation (Model Meta 4/1800). It is a 16-bit word machine having a 64K word memory core and an auxiliary memory of equivalent size. All programs for data processing, display, and storage are efficiently linked so that no more than 9.6K of core is required. The computer, under the supervision of a multiprogramming operating system (IBM MPX-OSl), supports on-line GC-MS experiments as well as the requirements of other users. Data collection occurs on disk by means of a direct memory access channel. Total ion current chromatograms are plotted in real-time on a Tektronix video terminal (Model 4010-1). All other data processing is handled after completion of the GC run. Set-up and control functions are handled either through hardware at the interface or through the equipment normally used to operate the mass spectrometer. Program control-including the initiation and termination of data collection, data reduction, presentation and storage-is under control of the user through the video terminal. Tapped Analog Delay Filter. Following the suggestion of Doerfler and Campbell, a tapped analog delay (TAD) filter was built and incorporated into our system ( I O ) . The TAD filter accepts analog input from the electrometer and provides real-time signal filtering comparable to that obtained from an extensive (31 step) running average digital smoothing routine. The analog

Figure 2. Schematic diagram of the analog voltage comparator built around an LF-111 amplifier (National Semiconductor)

output of the TAD filter is then fed to the interface. Readers interested in this excellent method of data smoothing are encouraged to review the original work of these authors. Interface. A schematic diagram is given in Figure 1. The interface is designed to accept and digitize analog signals from the mass spectrometer, to determine when the ion current signal exceeds a user defined threshold and therefore should be transmitted to the computer, and to provide the digital clock signals for the operation of subroutine CTIME. The interface does not provide for computer control of the mass spectrometer. Indeed, control functions performed by the nondedicated computer are limited to a single routine which determines the mass spectrometer scan rate and sets the bus controller accordingly. An 8-channel input amplifier provides gain ranging capabilities for selected ion monitoring experiments. The A/I> converter is a 12-bit device providing 2.44 mV resolution for a maximum input signal of 10 V. The analog comparator is built from an LF-111 amplifier with the output clamped to provide TTL compatible signals (11, 12). A schematic diagram is given in Figure 2. The interface clock is a 24-bit device which is divided into two, 12-bit sections. One section, B, increases in magnitude throughout the course of the entire data collection run. Section A contains the most significant bits and cycles several times during the course of a normal scan. Operating conditions are generally set such that the mass spectrometer sweeps at a rate of 10 msjamu, the A/D takes 16 samples/amu, and the interface clock increases by 38 clock-times between conversions. Thus the change in the value of the clock between samples (conversions) is sufficient to resolve consecutive samples in the data train. Each sample taken by the interface is transmitted to the computer as a block of four, 16-bit words. Each word contains 4 bits of status information with the remaining 12-bit section reserved for ion intensity, mass voltage, clock (section A), and clock (section B) in words 1-4, respectively. To ensure efficient operation of the data acquisition program on a nondedicated computer, a comparator is used to “pack” the data in the digital train. Samples, which do not contain intensity information above a user defined threshold, are not transmitted.

RESULTS The operation of CROSS was checked through the following experiments. The threshold comparator was disabled so that all data were transmitted to the computer. In this condition, mass spectra of background ions in the air/water region were recorded. The results obtained via CROSS were found to compare favorably with oscillographic recording of the same region. T o determine the effect of noise spikes, computer outputs containing the digital data for individual scans were processed manually using the cross-correlation subroutine. In general the results were satisfactory, but one problem was observed. When noise spikes occurred on the tailing edge of low abundance peaks-Le., those for which the maximum signal intensity was less than 20-30 mv-CROSS would occasionally miss the end of the peak. This was a problem when D,was prevented from becoming negative before the beginning of a subsequent peak. Implementation of real-time data smoothing by means of a TAD filter rectified the problem. Two mass spectra of p-methylanisole are shown in Figure 3. Spectrum 3a was acquired with the threshold comparator

40

ANALYTICAL CHEMISTRY, VOL. 52, NO. 1, JANUARY 1980

Table I. Results of the PBM Identification of Mass Spectra 3a and 3b

k = 90 ~k = 8

spectrum serial no. 3a

34873 34877 34875 34874

(LOCPK) Y

U

U

U

1

b

k = 92 ~k = 6

34876 34873 34874

3b (CROSS)

34876 34877 34875

name p-methylanisole p-methylanisole p-methylanisole p-cresylmethyl ether p-methoxyt oluene p-methylanisole p-cresylmethyl ether p-methoxytoluene p-methylanisole p-methylanisole

confidence value K aK 90+ 8 79*+ 11 69**+ 24 62*+ 4 2 581 92+ 76*+

37 6

75+ 69*s 67+

20 21

28

26

c ENTER

40

60

EO

100

[_

I20

m/

R E A D DATA

Figure 3. Mass spectra of p-methylanisole: (a)spectrum processed via program LOCPK; the bars beneath the abscissa indicate mass peaks identified by subroutine CROSS; (b) spectrum processed via subroutine CROSS;the values for Kand AKwere obtained using the Cornell University PBM System

FROM DISK

adjusted to transmit signals greater than 3-4 mV above the background noise level. Under these conditions mass peaks are identified by either subroutine CROSS or CTME as required by LOCPK. Of the 29 peaks detected within the scan range of 41-229 m u , 17 were found by CTIME alone; 1 2 required further processing by CROSS. Within spectrum 3a, regions for which CROSS was used in peak identification are indicated by the bars beneath the abscissa. The complete digital record for this scan consisted of 382 conversions or 1528 words, since four words are transmitted for each conversion. In contrast, spectrum 3b was recorded without the use of the threshold comparator. Because each conversion was transmitted, the digital record contained 3008 conversions (12 032 words). Nevertheless, visual inspection indicates only small differences between these spectra. Spectrum 3b does contain 10 ions of low relative abundance not found in 3a. The ions a t m / z 120 and m J z 90 have the largest relative abundance of this group-2 and 3%, respectively. The rest fall within the range of 0.5 to 1.0% relative abundance. Several ions found in both spectra do show detectable differences in relative abundance. For example, m / z 121 has an abundance of 52% in 3a but only 47% in 3b. Some differences in relative abundance can also be observed for m / z 52 and m / z 53 when the spectra are compared. The results of the following experiment indicate that, in qualitative experiments, minor differences such as these are not significant. Perhaps these are merely due to the differing dynamic conditions encountered during successive runs with a GC inlet system. T o assess the potential significance of the differences noted above, both spectra 3a and 3b were submitted for computer assisted identification using the Cornell University Probability Based Matching System (13). The results are given in Table I. Both spectra are identified correctly. The most closely matching spectra in each case are all of p-methylanisole. Spectrum 3a, which was processed by LOCPK, and 3b, which was possessed only by CROSS, show excellent agreement with the library spectrum 334873. The close agreement of the confidence factors clearly indicates that the results available through the use of the data-blocking, cross-correlation peak detection method compare favorably with those available through the use of cross-correlation analysis alone. For most,

CTIME

e 1 M , F L A G = I

I

YES

C ROSS

OUT PUT R E SU L T S

Figure 4. Flow

chart for program LOCPK

if not all practical purposes, the results from LOCPK are not significantly different from those given by CROSS.

DISCUSSION Computer Program LOCPK. The program is written in IBM-1800 assembly language. A listing is available by writting to one of us (M.T.). Figure 4 contains the flow chart for LOCPK. The identification of mass peaks in the digital data train involves the following steps. The digitized record for a selected scan is read from disk and subroutine CTIME is called to scan the interface clock values. When necessary, subroutine CROSS is called to process those regions identified by CTIME for cross-correlation analysis. In this format, LOCPK is a simple program providing an efficient method through which mass spectral data are processed using either the data-blocking or the cross-corre-

ANALYTICAL CHEMISTRY, VOL. 52, NO. 1, JANUARY 1980

lation detection algorithm as required by the complexity of the data record. The correct operation of LOCPK can be easily verified by means of hardware control a t the interface; that is, when the threshold comparator is off, the data record for the scan is processed by subroutine CROSS alone. Subroutine CTIME. The operation of CTIME depends on the use of a threshold comparator. Both software and hardware methods of data thresholding are well known (2, 14). McFadden had reviewed both approaches and has indicated areas for caution in their application. Software thresholding could not be easily employed in our situation since the data system operates on a nondedicated computer. When thresholding is done by software methods, all data are transmitted directly to the computer. This would give rise to prohibitively high transmission rates during fast mass scanning. Hardware thresholding provides a reasonable alternative. Several approaches may be used in data thresholding by hardware methods. The underlying strategy is to reduce the volume of data actually transmitted during a scan by eliminating much of the less meaningful signals. This is particularly important in high resolution work where the rates of data sampling may range from 25-100 kHz depending on the scan rate (2). Boetteger has published an excellent account of a data logging system for high resolution mass spectrometry (15). Of course, the application of this approach need not be restricted to high resolution work. Bowen has reported on the design and application of a digital threshold comparator (4,16). In this method, the signal from the mass spectrometer is converted to digital form and the output of the A/D converter compared with an external reference voltage. For the system reported by Bowen, the user can select from among several fixed reference voltages to establish the data acquisition threshold a t 50, 100, 200, 400, 800, 1600, or 3200 mV. For our system, however, these threshold levels were unnecessarily high. An analog method was chosen to provide greater selectivity in thresholding. The analog output of the electrometer is compared to an analog reference voltage which may be continuously varied over the range of 6 1 0 0 mV. The background noise level on the system is normally about 3-4 mV a t an electron multiplier gain of lo6. The analog comparator is therefore set at about 5-8 mV so that the threshold level is just above the level of background noise. Naturally, the comparator need not be of the analog type. A digital comparator designed to operate in the required range would work as well. Subroutine CTIME is used to decipher the information present in the abbreviated digital record. I t is also designed to recognize regions within the record for which more extensive processing is required. In this event, the identified region is processed by CROSS. Four tests are required to locate a mass peak and to detect those regions for which CROSS is required. The flowchart is shown in Figure 5 . Upon entering the subroutine, the clock value, C, is read for the first conversion and both C and the conversion number, n, are stored. As the first conversion in a block of data, n represents the beginning of a mass peak when the necessary conditions are met. As long as additional data are presented in the record, processing passes to Test 2 which identifies discontinuities or “clock-breaks” in the digital record. This is accomplished by comparing the difference in clock values for adjacent conversions, AC, to a limit cy defined in Equation 5 ; b cy

=

(I?,)-

4 ”,?

(5)

k , is an integer constant, 6 is the clock rate (clock-times/s), 4 is the scan range (amu/scan), v is the scan rate (scans/s), and y is the sampling rate (conversions/amu). The ability

41

m

1

I

YES1

I

.-

.-Tz+ i

NO

* L A S T

r

Y

STORE

A

7

~

MASS,INT

n

RETURN

Tests 1-A and 1-B determine Figure 5. Flow chart for subroutine CTIM the end of the data record; Test 2 is used to locate discontinuities in the data record; Test 3 is a threshold test for the rejection of noise spikes; Test 4 determines when subroutine CROSS IS required in processing

of CTIME to resolve adjacent data blocks within the digital record is determined by the settings chosen for 4, u , y, and the value of k , . The clock rate is not a variable as 6 is fixed for the digital clock selected for the interface. In practice a value of 4 is used for k l . This means that adjacent blocks of data separated by a gap greater than four conversions will be recognized. That is, when AC > a , then a discontinuity is located in the digital record. A positive result for Test 2 causes the number of the conversion preceding the discontinuity to be stored in register b. When positive results are obtained for the subsequent tests, 3 and 4,then the conversion number in b is accepted as the end of a mass peak. Under these conditions then, the region of the digital record from a through b, (a,bJ, is accepted as a legitimate peak. Test 3 is a threshold check which prevents transient noise spikes from inadvertently being detected as mass peaks. A noise spike which passes the threshold comparator will be rejected if the total number of conversions, (0-a),is less than threshold p. is defined in terms of the sampling rate such that 0 = y / k 2 . Again, k 2 is an integer constant. When the sampling rate is 16 and k , is equal to 4, then more than four conversions are required for the minimum inass peak definition. Test 4 determines when CROSS is required. If the range of data within the block (b-a)is less than threshold X, then the cross-correlation subroutine is not needed. The data-block contains no more than one mass peak a t integer resolution. The threshold X is defined as k,y; k3 is a constant, 1.25, and y is, of course, the sampling rate. In normal operation y is set for 16 conversions/amu so that threshold X is an integer: 20. Other values can be chosen but, in the interest of processing efficiency, the value chosen should be consistent with the use of integer arithmetic. When X is not exceeded, the

42

ANALYTICAL CHEMISTRY, VOL. 52, NO. 1, JANUARY 1980

$.1222

k---IZl$

-0

b

o

& I 2 3 2

b o

b = n * 3

b

rn I , I N T

n

-

Figure 6. Selected portion of a mass spectrum of p-methylanisole containing the ions at m l r 121, 122, and 123. The digital intensity

values, g,and the corresponding detection function, D,, are presented for each data conversion, n ; a and b represent the beginning and end of each mass peak as located by CROSS response values for conversions a through b are summed, the mass centroid estimated, and these values stored before processing passes to Test 1-B. If the digital record contains additional data, t,hen the result for Test 1-B is negative and the value of n is incremented before CTIME examines the next block of data in the scan be returning to Test 1-A. When X is either exceeded or equaled, however, the data lying in the range la,b] may contain more than one peak so subroutine CROSS is called. Subroutine CROSS. Several modifications have been made in the cross-correlation routine originally reported by Bell. Equation 6 gives the form of the C, function used in this work, and Equation 7 gives the corresponding detection function following background subtraction as suggested by Black. (CT)n

= gn-3

+ 2gn-Z + 3gn-I + 4gn + 3gn+1+ gn+2

(6) (7)

( D r ) n = -8,-3 + gn-1 + 2gn + g n + l - gn+2 Two points should be noted. I t can be seen from the comparison of Equations 6 and 2, or Equations 7 and 4, that the direction of data processing has been altered. Equation 2, and consequently Equation 4, is arranged for processing data from high to low mass. While this is not explicitly stated by Bell, it may be deduced through examination of the integer sequence for the reference signal and by recalling that quadrupole mass peaks are skewed toward the direction of lower mass. Equations 6 and 7 are ordered for processing data in the reverse direction. In this instance, the skewed portion of the peak is encountered first so the reference signal is represented by the integer sequence: 1, 2, 3 , 4 , 3, 1. This is not a necessary condition as far as CROSS is concerned, for, once collected, the digital data can be processed in either direction as long as the correct reference signal is used. It is explicitly stated here, however, to avoid confusing interested readers who may wish to compare the present method with previous work.

Flgure 7. Flow chart

for subroutine CROSS: Test 1 locates the beginning CROSS; Tests 2 and 4-A determine the end of the data block; Test 3 (A, B, and C) locates the beginning of the mass peaks; Test 4 (B and C) locates the end of the mass peaks; Tests 5 and 6 are threshold tests for the rejection of noise of the block of data to be processed by

spikes

The second point of note is that Equations 6 and 7 are written so that the computed value of D is centered at g,. This causes D , to correspond correctly with the associated mass peak rather than being offset by several conversions. That is the case when Equation 4 is used and when the computed value of D, is located a t go. More will be said concerning this point during the discussion of Figure 6. The important properties of the detection function are shown in Figure 6. A region from the digital record of a mass spectrum of p-methylanisole is given. The ability of CROSS to detect mass peaks depends on that property of D , which causes it to become negative before and after each peak. Peak detection can be accomplished through simple sign checking on D,. The practical benefit resulting from this approach is that it is not necessary to use intensity values to locate valleys between adjacent peaks. In previous work, the detection function was used only to determine when a valid peak was present; thereafter, intensity values were compared a t n f 0.5 amu across the entire record to locate the beginning, end, and top of each peak. With CROSS, peak detection involves substantially fewer steps, thus making it more suitable for use on small data systems or on nondedicated computers. Again referring to Figure 6, since the detection function is correctly centered over the mass peaks as represented by the ion current values, peak positions can be determined directly from the detection function. The register a contains the number of the conversion corresponding to the beginning of a mass peak and register b contains the conversion number for the end of that peak. The mass voltage of the median value of n in the range {a,b]provides a convenient estimate for peak location regardless of whether the peak is detected by CROSS or CTIME. Steps usually employed for calculations of centroids are avoided (4,14). The results are quite satisfactory for low resolution work.

ANALYTICAL CHEMISTRY, VOL. 52, NO. 1, JANUARY 1980

The flow chart for CROSS is given in Figure 7. When a block of data within a scan is identified for processing by CROSS, Test 1 locates the first conversion in the block and directs processing into Test 3. Since a positive result for Test 1 has the effect of forcing positive answers for part A and B of Test 3, the only condition that must be satisfied to establish the beginning of a mass peak is for ( D J n f 2to be greater than zero. In other words, part C of Test 3 confirms that a mass peak is beginning or allows the subroutine to continue searching for the beginning of a peak in the initial portion of the data block. Once a positive result is obtained for Test 3-C, the conversion number corresponding to (D,)n+lis stored in register a to denote the point in the data where the peak begins. CROSS then checks for the end of the mass peak through Test 4. The conditions that must be met are simple. Parts B and C of Test 4 look for two successive values for D , that are either zero or negative. When this condition is recognized the conversion number corresponding to (Dr)n+3is stored in register b as the peak end. As stated above, CROSS locates mass peaks through sign checking on the detection function. This is illustrated by the data in Figure 6. Beginning a t the left side of the figure in front of m/z 121 and following the progression of D , in moving toward the right, note that D , becomes negative just prior to the appearance of m / z 121. The general requirement that indicates the start of a mass peak is one of the following sequences of signs for D,: (-, -, +); (0, -, +); (0, 0, +); or (-, 0, +). The first sequence, (-, -, +) is by far the most common. Continuing across mass peak m / z 121, D , again becomes negative a t the end of the peak. For each of the three ions in Figure 6, the range of data corresponding to that ion, as identified by CROSS, is indicated by the arrows beneath the abscissa. Once a potential mass peak has been located by CROSS, two additional tests are used to eliminate noise spikes. Test 5 requires that there be a t least six values for D , in the region (a,b}for which D , > 0. In Test 5 , this is expressed in terms of 0 which is the number of positive values for D, in the peak region, (a,b). In Figure 6, for example, there are ten values of D , > 0 within the region of the molecular ion, m / z 122; 0

43

is greater than 6 and a positive result is obtained for Test 5. A second check, Test 6, requires that there be no more than three values of D, in the range (a,bJfor which D, < 0. In Test 6, w is the number of negative values of D, in the range of a potential peak. For the molecular ion in Figure 6, w is equal to 2. When a potential peak is located by CROSS, it will be accepted as valid only if the conditions for Test 5 and Test 6 are both met. Extensive testing has shown this to be efficient and reliable. The values for 0 and w were ascertained through empirical analysis of actual data using a sampling rate of 16 conversions per amu.

LITERATURE CITED Champman, J. R . "Computers in Mass Spectrometry"; Academic Press: London, 1978; p 30. McFadden, W. H. "Techniques of Combined Gas Chromatography/Mass Spectrometry"; John Wiley and Sons: New York, 1973; Chapter 7. Mellon, F. A. "Mass Spectrometry", Vol. 4, Johnstone, R . A,, Ed.; The Chemical Society, Burlington House: London, 1977; Chapter 3. Gudzinowicz, B. J.; Gudzinowicz, M. J. "Fundamentals of Integrated GC-MS", Part 111; Marcel Dekker: New York, 1978. Bell, N. W. Twenty-First Annual Conference on Mass Spectrometry and Allied Topics, San Francisco, Calif., 1973. Bell, N. W. "Computer Detection of MS Peaks by Real Time Cross Correlation", Technique Paper No. MS-2. Hewiett-Packard: Palo Alto, Calif. Peterson, R. D.; Myers, G. G. "Waveform Analysis in Medicine"; Charles C Thomas: Springfield, Ill., 1976; p 145. Glaser, E. M.; Ruchkin, D. S. "Principles of Neurobiological Signal Analysis"; Academic Press: New York, 1976; Chapter 5. Black, W. W. Nucl. Instrum. Methods 1969, 7 1 , 317-327. Doerfler, D. L.; Campbell, I.M. Anal. Chem. 1976, 50, 1018. Hnatek, E. R. "A User's Handbook of Integrated Circuits"; John Wiley and Sons: New York, 1973; p 308. "Linear Databook"; National Semiconductor: Santa Clara, Calif., 1978; Chapter 5. McLafferly, F.; Hertel, R. H.; Villwock, R. D. Org. Mass Spectrom. 1974, 9 ,690. Chapman, J. R. "Computers in Mass Spectrometry"; Academic Press: London, 1978; Chapter 2. Boettger, H. G. "Biochemical Applications of Mass Spectrometry". Waller, G. R., Ed.; Wiley-Interscience; New York, 1972; p 79. Bowen, H. C.; Chenevix-Trench, T.; Drackley, Si. D.; Faust, R. C.; Saunders, R. A. J . Sci. Instrum. 1967, 4 4 , 343.

RECEIVED for review March 15, 1979. Accepted October 10, 1979.