- Email: [email protected]
Signal processing techniques in analytical instruments
163
trends in analytical chemistry, vol. 1, no. 7,1982
2’ Keirs, R. J., Britt, R. D. Jr. and Wentworth, W. E. (1957) Anal. Chem. 29, 202 3 Parker, C. A. and Hatchard, C. G. (1962) Analyst 87, 664 4 Miller, J. N. (1981) TrendsAnal. Chem. 1, 31 5 Shulman, E. M. and Walling, C. (1972) Science 178, 53 6 Vo Dinh, T., Walden, G. L. and Winefordner, J. D. (1977) Anal. Chem., 49, 1126 7 Cline Love, L. J., Skrilec, M. and Habarta, J. B. (1980) Ana!. Chem., 52, 754 8 McCarthy, W. J. and Winefordner, J. D. (1967) in Fluorescence, Theory, Instrumentation and Practice, (Guilbault, G. G. (ed.)), Ch. 10, p. 371, Marcel Dekker, New York 9 Goutilier, G. D. and Winefordner, J. D. (1979) Anal. Chem. 51, 1384 10 Wilson, R. M. and Miller, T. L. (1975) Anal. Chem. 47, 256 11 Goeringer, D. E. and Pardue, H. L. (1979) Anal. Chem. 51, 1054 12 Johnson, D. W., Callis, J. B. and Christian, G. D. (1977) Anal. Chem. 49, 747A 13 Warner, I. M., Callis, J. B., Christian, G. D. and Davidson, E. R. (1977) Anal. Chem. 49, 564 14 Fogarty, M. P. and Warner, I. M. (1981) Anal. Chem. 53, 259
Signal
processing
15 Ho, C.-N., Christian, G. D. and Davidson, E. R. (1978) Anal. Chem. 50, 1108 16 Ho, C.-N., Christian, G. D. and Davidson, E. R. (1980) Anal. Chem. 52, 1071 17 Warner, I. M., Fogarty, M. P. and Shelly, D. C. (1979) Anal. Chim. Acta, 109, 361 Isiah M. Warner received his B.S. degree in Chemistry from Southern University in Baton Rouge, Louisiana in 1968. He then worked as a Research Chemist at Battelle Northwest, Richland, Washington from June, I!%8 to September, 1973. In October, 1973, he entered the graduate program at the University of Washington where he worked under the research guidance of Professor Gary Christian and received his Ph.D. in Analytical Chemistry in 1977. Isiah Warner has been an Assistant Professor of Chemistry at Texas A &? M University College Station, TX77843, U.S.A., since June, 1977. Chu-Ngi Ho received his B.S. degree from Denison University in Granville, Ohio in 1975. In August 1980, he obtained his Ph.D. in Analytical Chemistry under the supervision of Professor Gary Christian at the UniversiQ of Washington. He is presentb a Post-Doctoral Research Associate with Dr Isiah M. Warner at Texas A @ M University.
techniques instruments
in analytical
Signal processing is a unifying principle useful in understanding the operation of analytical instrumentation. Through it new modes of operation may be found for existing analytical methods and entirely new methods may be discovered. John B. Phillips Carbondale, IL, U.S.A. Signal processing, broadly speaking, is any operation which refines information contained in a signal. By this definition much ofwhat analytical chemists do is signal processing. An analytical determination begins with a sample and ends with some desired information about the sample. During the process the chemist manipulates the sample and signals derived from it to select the desired information and discriminate against all other information. A signal is any physical parameter whose value has meaning; that is, a signal carries information. The deflection of a meter on a spectrophotometer is a signal. So is the current which drives the meter, the light which generates the current in a photocell, and the concentration of substance in a cuvette which determines the light intensity. Every manipulation of a signal such as the selection of a particular wavelength of light by a monochromator is, in the broadest sense, signal processing. This approach to understanding analytical instru-
mentation was not much used in the past because the straightforward signal processing involved could generally be understood without a unifying concept. However, new instruments currently being developed and some which have already been introduced include a great deal more sophisticated signal processing. Much of this sophistication is due to the advances made in electronics and to the computers which are now being used in instrument automation, but in some cases advanced signal processing concepts are also beginning to affect the chemistry of the instrument. The distinction between the processing of electronic and computer signals and the chemical reaction signal is becoming more and more blurred. For example, most nuclear magnetic resonance spectrometers, especially for isotopes other than ‘H, now include a computer for signal averaging and Fourier transform calculations. Digital signal processing in the computer improves data quality. It also makes possible a variety of new chemistries such as cross polarization and spin echo techniques which produce additional kinds of information. Here the signal processing has changed the chemistry ofthe instrument in subtle but important
164
ways. It is no longer possible to understand the chemistry without considering signal processing in the instrument as a whole.
Signal processing in chromatography Chromatography is an excellent example of an analytical methodology which has gradually made more extensive use of signal processing techniques. Originally, chromatography was strictly a chemical separation method. A liquid chromatographic column would be used for a preliminary separation, but the analytical emphasis was on the subsequent measurement step. In gas chromatography (GC), however, a physically separate measurement device was very inconvenient. New kinds of detectors were developed and evolved in response to the needs of the column. Detector and column technologies stimulated each other’s evolution to such an extent that now the term ‘gas chromatography’ essentially refers to the combination of the two. More recently, liquid chromatography has followed the same path with the development of HPLC. Thin layer and paper chromatography are also developing in this direction’. Therefore as chromatography has evolved into an instrumental analytical method, the emphasis has shifted from chemical separation to the production of analytically useful chromatograms. A chromatogram is a signal. It is the most general representation of the information produced by a chromatographic instrument. A strip-chart recording of a chromatogram is the traditional final output of a chromatograph. A chemist may extract some information from a chromatogram by inspection, but to make maximum use of this signal he must apply some further signal processing. External devices such as paper and pencil, pocket calculator, or even a time-shared computer system have been used for chromatographic signal processing. The weak link in these techniques is the transmission of the information in the form of a chromatogram from the instrument to the external device. The ‘computing integrator’ currently being marketed by several companies started out as an external device for chromatographic signal processing but it is fast becoming a standard part of the instrument. As soon as this occurs a co-evolution process similar to that which took place between column and detector will begin. In a few years the term ‘chromatography will refer to an instrument composed of a column, detector, and computer. The raw chromatogram will then become an intermediate signal which is only occasionally examined during method development or instrument maintenance.
Qualitative and quantitative signals Different signal processing techniques are required for the extraction of qualitative as compared to quantitative information. The majority of chromatographic determinations are quantitative. The identities of the compounds to be determined are usually already known and standards
trends in analytical chemistry, vol. 1, no. 7,1982
are available. No further information can be obtained from the positions of the peaks in the chromatogram. The signal processor isolates the relevant information from the signal by measuring peak areas or heights. This information is then combined with calibration information taken from the same chromatogram or a reference chromatogram. Chromatograms contain little qualitative information about individual chemical compounds. Only the position of a single peak and sometimes the peak intensity, if a selective detector is being used, are relevant. For compound identification chromatography is inferior to spectroscopy but, in the analysis of complex mixtures, the larger number of components results gives rise to more peaks and a much larger amount of qualitative information. Spectroscopic methods generally cannot compete with chromatography when applied to complex mixtures because they generate signals which contain a great deal of qualitative information about the individual components. This additional information is largely irrelevant for mixture identification and must be discriminated against by additional complex signal processing.
Automation The new advances in electronics and computer science are rapidly being applied to the automation of analytical instruments. Automation can enhance efficiency and productivity by eliminating manual operations and reducing waste. This justifies expenditure on automated instrumentation by any laboratory with a sufficient number of analytical determinations to perform. Automation also improves reliability, precision, and accuracy by eliminating variability in instrument operation. Automation of the traditional signal processing methods in chromatography is now essentially complete2. The term ‘automation’ implies that the instruments operate in basically the same way and are applied in the same way as older non-automated instruments. However, once a powerful signal processing capability becomes associated with an instrument, new operation modes and applications are likely to develop as the instrument and signal processor evolve together. A signal processing computer has been used in association with gas chromatography/mass spectrometry (GWMS) for a long time and important new techniques have been developed for this method”. Indeed, signal processing software now forms a major part of these GUMS instruments.
A signal processing revolution Computers intimately associated with instruments are the key to the development of analytical signal processing. Table I lists some of their capabilities likely to revolutionize analytical instrumentation. Computational power is a basic requirement of instruments such as Fourier transform infrared spectrometers and provides new modes of operation based on sophisticated signal transformation techniques+.
165
trends in analytical chemistry, vol. 1, no. 7,198.?
from one representational Transforming signals domain to another often allows formerly inaccessible information to become readily available. A large on-line data storage capability is potentially valuable in most instruments devoted to qualitative analysis as a rapid and accurate comparison with reference materials is required. Indeed, a large computer library of reference spectra is now used, almost exclusively, for methods such as mass spectrometry, and will be extended to cover other methods as the computer becomes a standard instrument component. Most analytical instruments are much slower than their associated computer. The computer is therefore able to record an analytical signal while simultaneously performing other signal processing functions. Traditional analog measurement devices such as panel meters or strip-chart recorders often limit the reliability, precision, and accuracy of analytical instruments. In general, an electronic signal should be converted to digital form as early as possible. Instrument command and control can also be more precise, accurate and reliable if a computer is incorporated in the instrument. A computer does not become bored with repetitive tasks and is, therefore, likely to be more reliable than a human operator. If the instrument is user programmable, then the definition of repetitive task can be broadened to include any sequence of signal processing operations for which decision criteria can be specified in advance. Few analytical instruments in current use even approach the theoretical possibilities offered by advanced signal processing techniques. Automation is well advanced in some instances and new methods fundamentally depend on computerized signal processing are beginning to appear. However, the association between computer and analytical instrument is still too young for much co-evolution to have occurred. So far chromatography has lagged behind, for despite computer linkage, chemists are only now beginning to devise new methods which use it. The most pressing need in chromatographic instrumentation is to increase the rate by which information is produced. In principle this could be accomplished by better signal processing to extract more information from chromatograms or by the production of better signals containing more information. These two approaches are being pursued separately in the development of better software for chromatogram processing and in the development of better chromatographic columns and detectors. The signal processing revoluTABLE I. Computer processing (1) (2) (3) (4) (5) (6)
capabilities
computational power large data storage volume fast data acquisition precise instrument control precise digital measurement repetition
important
for instrument
A
A
Ctii?OMTO6RRtl
Fig. 1. Multiplex chromatography. The computer generates a random signul to modulate the sample stream concentrations. The chromatogram may be recovered by deconvolution of the random modulation signal from the detector output signal
tion will have arrived by the time these two approaches are simultaneously applied in an interdependent fashion. Indeed, some possibilities for their use are already apparent. Multiplex5 or cross-correlation chromatography treats the column as a communication channel through which a chemical concentration signal may be transmitted. As shown in Fig. 1, a sample stream flows through the column continuously while a computer generated signal modulates the sample concentrations. The detector output signal is not a chromatogram, but since it contains the same information, the chromatogram may be computed by means of a signal processing technique. This method has the potential to produce a continuous analysis with detection limits comparable to or better than the best chromatographic methods currently available. In this method signal processing ideas are applied to those processes occurring within the column as well as those within the computer, Mode sequencing in liquid chromatography” makes use of multiple short HPLC columns to achieve spectacular improvements in selectivity and reductions in analysis time. As shown in Fig. 2, a number of
signal
U
U
Fig. 2. Mode sequence liquid chromatography. One particular component is steered through a sequence of different #res of columns bv precise!v timed valve switching
166
trends in analytical chemistry, vol. I, no. 7,198.?
different column types are connected by valves in an array structure. At the appropriate times a computer switches the valves to steer the desired component through the array to the detector. It is extremely unlikely that any other substance would have the same retention on all the different column types in the array. The combination of a set of precise timing signals with a corresponding array of columns is the key to this method. Similar revolutionary ideas can be found in the literature of most analytical methods. Not all of these will be practical, but many will and signal processing in develand related concepts718 will be instrumental oping and understanding them.
References 1 Fenimore, D. C. and Davis, C. M. (1981) Anal. Chem. 53,253A
Inelastic
electron
Reese, C. E. ( 1980) J. Chromatogr. Sci. 18, 249 Gates, S. C., Smisko, M. J., Ashendel, D. L., Young, N. D., Holland, J. F. and Sweeley, C. C. (1978) Anal. Chem. 50, 433 Griffiths, P. R. (Ed.) (1978) Transform Techniques in Chemistry Plenum Press, New York Phillips, J. B. (1980) Anal. Chem. 52, 468A Freeman, D. H. (1981) Anal. Chem. 53, 2 Eckschlager, K. and Stepanek, V. (1979) Znjrmation Theory as Applied to Chemical Analysis,John Wiley and Sons Ltd., New York Beauchamp, K. and Yuen, C. (1979) Digital Methods for Signal Analysis, George Allen and Unwin, London
John B. Phillips received his B.A. degree from the University of California, Irvine in 1970 and a Ph.D. in Analytical Chemistry from the University of Arizona in 1977. He is currently Assistant Professor in the Department of Chemistry and Biochemistry at Southern Illinois Universily, Carbondale, IL 62901, U.S.A. His research interests include chemical instrumentation, chromatographic processes, and applications of laboratory computers.
tunneling
spectroscopy
Inelastic electron tunneling spectroscopy (IETS) is a relatively new form of vibrational spectroscopy which is able to address problems previously unsolved by either IR or Raman. It is particularly useful for surface analysis. Hawey S. Gold and Lisa J. Hilliard University of Delaware, U.S.A.
The vibrational triumvirate Jaklevic and Lambe discovered in 1967, spectroscopy (IETS) Josephson junctions at the Ford conventional Josephson iunction insulator/metal) yields a linear applied bias voltage. However,
IR
RAMAN The Vibrational
0 165.9936/82/oooO-0/$02.7.5
inelastic tunneling whilst working on Motor Companyl. A (of the form metal/ ‘plot of current-vwhen an insulator
Triumvirate.
IETS
contaminated with organic molecules was used a change in the slope of the graph was observed at each voltage corresponding to the energy required to excite a vibrational mode of the molecule. Second derivative techniques made it possible to observe peaks in the plots at these locations. IETS is now the third form of vibrational spectroscopy available to the scientific community - the others are infrared (IR) and Raman. In contrast to IR and Raman, IETS is a non-optical technique. It involves the tunneling of electrons (in the quantum mechanical sense) from one metal to another through a barrier (an insulating oxide layer) containing sample molecules. Energy from the electrons is transferred inelastically to the vibrational modes of the sample molecule. There are several advantages and disadvantages associated with each of the vibrational spectroscopies; these are summarized in Table I. However, a few points regarding IETS should be emphasized. First, there are no quantum mechanical selection rules to restrict IET, with the result that all vibrational modes are active. An IET spectrum thus consists of IR-active modes, Raman-active modes, and optically forbidden modes, Second, the limit of detection for IETS is extremely low: as little as 5 X 10-s monolayer (or approximately 2 X 1010 molecules) of a substance can be detected on the barrier surface. This compares favorably with the most sensitive spectroscopic tech-. niques and is orders of magnitude more sensitive than either IR or Raman. 0 I962 ElJcvicr S&milk Publishing Company
trends in analytical chemistry, vol. 1, no. 7,1982
2’ Keirs, R. J., Britt, R. D. Jr. and Wentworth, W. E. (1957) Anal. Chem. 29, 202 3 Parker, C. A. and Hatchard, C. G. (1962) Analyst 87, 664 4 Miller, J. N. (1981) TrendsAnal. Chem. 1, 31 5 Shulman, E. M. and Walling, C. (1972) Science 178, 53 6 Vo Dinh, T., Walden, G. L. and Winefordner, J. D. (1977) Anal. Chem., 49, 1126 7 Cline Love, L. J., Skrilec, M. and Habarta, J. B. (1980) Ana!. Chem., 52, 754 8 McCarthy, W. J. and Winefordner, J. D. (1967) in Fluorescence, Theory, Instrumentation and Practice, (Guilbault, G. G. (ed.)), Ch. 10, p. 371, Marcel Dekker, New York 9 Goutilier, G. D. and Winefordner, J. D. (1979) Anal. Chem. 51, 1384 10 Wilson, R. M. and Miller, T. L. (1975) Anal. Chem. 47, 256 11 Goeringer, D. E. and Pardue, H. L. (1979) Anal. Chem. 51, 1054 12 Johnson, D. W., Callis, J. B. and Christian, G. D. (1977) Anal. Chem. 49, 747A 13 Warner, I. M., Callis, J. B., Christian, G. D. and Davidson, E. R. (1977) Anal. Chem. 49, 564 14 Fogarty, M. P. and Warner, I. M. (1981) Anal. Chem. 53, 259
Signal
processing
15 Ho, C.-N., Christian, G. D. and Davidson, E. R. (1978) Anal. Chem. 50, 1108 16 Ho, C.-N., Christian, G. D. and Davidson, E. R. (1980) Anal. Chem. 52, 1071 17 Warner, I. M., Fogarty, M. P. and Shelly, D. C. (1979) Anal. Chim. Acta, 109, 361 Isiah M. Warner received his B.S. degree in Chemistry from Southern University in Baton Rouge, Louisiana in 1968. He then worked as a Research Chemist at Battelle Northwest, Richland, Washington from June, I!%8 to September, 1973. In October, 1973, he entered the graduate program at the University of Washington where he worked under the research guidance of Professor Gary Christian and received his Ph.D. in Analytical Chemistry in 1977. Isiah Warner has been an Assistant Professor of Chemistry at Texas A &? M University College Station, TX77843, U.S.A., since June, 1977. Chu-Ngi Ho received his B.S. degree from Denison University in Granville, Ohio in 1975. In August 1980, he obtained his Ph.D. in Analytical Chemistry under the supervision of Professor Gary Christian at the UniversiQ of Washington. He is presentb a Post-Doctoral Research Associate with Dr Isiah M. Warner at Texas A @ M University.
techniques instruments
in analytical
Signal processing is a unifying principle useful in understanding the operation of analytical instrumentation. Through it new modes of operation may be found for existing analytical methods and entirely new methods may be discovered. John B. Phillips Carbondale, IL, U.S.A. Signal processing, broadly speaking, is any operation which refines information contained in a signal. By this definition much ofwhat analytical chemists do is signal processing. An analytical determination begins with a sample and ends with some desired information about the sample. During the process the chemist manipulates the sample and signals derived from it to select the desired information and discriminate against all other information. A signal is any physical parameter whose value has meaning; that is, a signal carries information. The deflection of a meter on a spectrophotometer is a signal. So is the current which drives the meter, the light which generates the current in a photocell, and the concentration of substance in a cuvette which determines the light intensity. Every manipulation of a signal such as the selection of a particular wavelength of light by a monochromator is, in the broadest sense, signal processing. This approach to understanding analytical instru-
mentation was not much used in the past because the straightforward signal processing involved could generally be understood without a unifying concept. However, new instruments currently being developed and some which have already been introduced include a great deal more sophisticated signal processing. Much of this sophistication is due to the advances made in electronics and to the computers which are now being used in instrument automation, but in some cases advanced signal processing concepts are also beginning to affect the chemistry of the instrument. The distinction between the processing of electronic and computer signals and the chemical reaction signal is becoming more and more blurred. For example, most nuclear magnetic resonance spectrometers, especially for isotopes other than ‘H, now include a computer for signal averaging and Fourier transform calculations. Digital signal processing in the computer improves data quality. It also makes possible a variety of new chemistries such as cross polarization and spin echo techniques which produce additional kinds of information. Here the signal processing has changed the chemistry ofthe instrument in subtle but important
164
ways. It is no longer possible to understand the chemistry without considering signal processing in the instrument as a whole.
Signal processing in chromatography Chromatography is an excellent example of an analytical methodology which has gradually made more extensive use of signal processing techniques. Originally, chromatography was strictly a chemical separation method. A liquid chromatographic column would be used for a preliminary separation, but the analytical emphasis was on the subsequent measurement step. In gas chromatography (GC), however, a physically separate measurement device was very inconvenient. New kinds of detectors were developed and evolved in response to the needs of the column. Detector and column technologies stimulated each other’s evolution to such an extent that now the term ‘gas chromatography’ essentially refers to the combination of the two. More recently, liquid chromatography has followed the same path with the development of HPLC. Thin layer and paper chromatography are also developing in this direction’. Therefore as chromatography has evolved into an instrumental analytical method, the emphasis has shifted from chemical separation to the production of analytically useful chromatograms. A chromatogram is a signal. It is the most general representation of the information produced by a chromatographic instrument. A strip-chart recording of a chromatogram is the traditional final output of a chromatograph. A chemist may extract some information from a chromatogram by inspection, but to make maximum use of this signal he must apply some further signal processing. External devices such as paper and pencil, pocket calculator, or even a time-shared computer system have been used for chromatographic signal processing. The weak link in these techniques is the transmission of the information in the form of a chromatogram from the instrument to the external device. The ‘computing integrator’ currently being marketed by several companies started out as an external device for chromatographic signal processing but it is fast becoming a standard part of the instrument. As soon as this occurs a co-evolution process similar to that which took place between column and detector will begin. In a few years the term ‘chromatography will refer to an instrument composed of a column, detector, and computer. The raw chromatogram will then become an intermediate signal which is only occasionally examined during method development or instrument maintenance.
Qualitative and quantitative signals Different signal processing techniques are required for the extraction of qualitative as compared to quantitative information. The majority of chromatographic determinations are quantitative. The identities of the compounds to be determined are usually already known and standards
trends in analytical chemistry, vol. 1, no. 7,1982
are available. No further information can be obtained from the positions of the peaks in the chromatogram. The signal processor isolates the relevant information from the signal by measuring peak areas or heights. This information is then combined with calibration information taken from the same chromatogram or a reference chromatogram. Chromatograms contain little qualitative information about individual chemical compounds. Only the position of a single peak and sometimes the peak intensity, if a selective detector is being used, are relevant. For compound identification chromatography is inferior to spectroscopy but, in the analysis of complex mixtures, the larger number of components results gives rise to more peaks and a much larger amount of qualitative information. Spectroscopic methods generally cannot compete with chromatography when applied to complex mixtures because they generate signals which contain a great deal of qualitative information about the individual components. This additional information is largely irrelevant for mixture identification and must be discriminated against by additional complex signal processing.
Automation The new advances in electronics and computer science are rapidly being applied to the automation of analytical instruments. Automation can enhance efficiency and productivity by eliminating manual operations and reducing waste. This justifies expenditure on automated instrumentation by any laboratory with a sufficient number of analytical determinations to perform. Automation also improves reliability, precision, and accuracy by eliminating variability in instrument operation. Automation of the traditional signal processing methods in chromatography is now essentially complete2. The term ‘automation’ implies that the instruments operate in basically the same way and are applied in the same way as older non-automated instruments. However, once a powerful signal processing capability becomes associated with an instrument, new operation modes and applications are likely to develop as the instrument and signal processor evolve together. A signal processing computer has been used in association with gas chromatography/mass spectrometry (GWMS) for a long time and important new techniques have been developed for this method”. Indeed, signal processing software now forms a major part of these GUMS instruments.
A signal processing revolution Computers intimately associated with instruments are the key to the development of analytical signal processing. Table I lists some of their capabilities likely to revolutionize analytical instrumentation. Computational power is a basic requirement of instruments such as Fourier transform infrared spectrometers and provides new modes of operation based on sophisticated signal transformation techniques+.
165
trends in analytical chemistry, vol. 1, no. 7,198.?
from one representational Transforming signals domain to another often allows formerly inaccessible information to become readily available. A large on-line data storage capability is potentially valuable in most instruments devoted to qualitative analysis as a rapid and accurate comparison with reference materials is required. Indeed, a large computer library of reference spectra is now used, almost exclusively, for methods such as mass spectrometry, and will be extended to cover other methods as the computer becomes a standard instrument component. Most analytical instruments are much slower than their associated computer. The computer is therefore able to record an analytical signal while simultaneously performing other signal processing functions. Traditional analog measurement devices such as panel meters or strip-chart recorders often limit the reliability, precision, and accuracy of analytical instruments. In general, an electronic signal should be converted to digital form as early as possible. Instrument command and control can also be more precise, accurate and reliable if a computer is incorporated in the instrument. A computer does not become bored with repetitive tasks and is, therefore, likely to be more reliable than a human operator. If the instrument is user programmable, then the definition of repetitive task can be broadened to include any sequence of signal processing operations for which decision criteria can be specified in advance. Few analytical instruments in current use even approach the theoretical possibilities offered by advanced signal processing techniques. Automation is well advanced in some instances and new methods fundamentally depend on computerized signal processing are beginning to appear. However, the association between computer and analytical instrument is still too young for much co-evolution to have occurred. So far chromatography has lagged behind, for despite computer linkage, chemists are only now beginning to devise new methods which use it. The most pressing need in chromatographic instrumentation is to increase the rate by which information is produced. In principle this could be accomplished by better signal processing to extract more information from chromatograms or by the production of better signals containing more information. These two approaches are being pursued separately in the development of better software for chromatogram processing and in the development of better chromatographic columns and detectors. The signal processing revoluTABLE I. Computer processing (1) (2) (3) (4) (5) (6)
capabilities
computational power large data storage volume fast data acquisition precise instrument control precise digital measurement repetition
important
for instrument
A
A
Ctii?OMTO6RRtl
Fig. 1. Multiplex chromatography. The computer generates a random signul to modulate the sample stream concentrations. The chromatogram may be recovered by deconvolution of the random modulation signal from the detector output signal
tion will have arrived by the time these two approaches are simultaneously applied in an interdependent fashion. Indeed, some possibilities for their use are already apparent. Multiplex5 or cross-correlation chromatography treats the column as a communication channel through which a chemical concentration signal may be transmitted. As shown in Fig. 1, a sample stream flows through the column continuously while a computer generated signal modulates the sample concentrations. The detector output signal is not a chromatogram, but since it contains the same information, the chromatogram may be computed by means of a signal processing technique. This method has the potential to produce a continuous analysis with detection limits comparable to or better than the best chromatographic methods currently available. In this method signal processing ideas are applied to those processes occurring within the column as well as those within the computer, Mode sequencing in liquid chromatography” makes use of multiple short HPLC columns to achieve spectacular improvements in selectivity and reductions in analysis time. As shown in Fig. 2, a number of
signal
U
U
Fig. 2. Mode sequence liquid chromatography. One particular component is steered through a sequence of different #res of columns bv precise!v timed valve switching
166
trends in analytical chemistry, vol. I, no. 7,198.?
different column types are connected by valves in an array structure. At the appropriate times a computer switches the valves to steer the desired component through the array to the detector. It is extremely unlikely that any other substance would have the same retention on all the different column types in the array. The combination of a set of precise timing signals with a corresponding array of columns is the key to this method. Similar revolutionary ideas can be found in the literature of most analytical methods. Not all of these will be practical, but many will and signal processing in develand related concepts718 will be instrumental oping and understanding them.
References 1 Fenimore, D. C. and Davis, C. M. (1981) Anal. Chem. 53,253A
Inelastic
electron
Reese, C. E. ( 1980) J. Chromatogr. Sci. 18, 249 Gates, S. C., Smisko, M. J., Ashendel, D. L., Young, N. D., Holland, J. F. and Sweeley, C. C. (1978) Anal. Chem. 50, 433 Griffiths, P. R. (Ed.) (1978) Transform Techniques in Chemistry Plenum Press, New York Phillips, J. B. (1980) Anal. Chem. 52, 468A Freeman, D. H. (1981) Anal. Chem. 53, 2 Eckschlager, K. and Stepanek, V. (1979) Znjrmation Theory as Applied to Chemical Analysis,John Wiley and Sons Ltd., New York Beauchamp, K. and Yuen, C. (1979) Digital Methods for Signal Analysis, George Allen and Unwin, London
John B. Phillips received his B.A. degree from the University of California, Irvine in 1970 and a Ph.D. in Analytical Chemistry from the University of Arizona in 1977. He is currently Assistant Professor in the Department of Chemistry and Biochemistry at Southern Illinois Universily, Carbondale, IL 62901, U.S.A. His research interests include chemical instrumentation, chromatographic processes, and applications of laboratory computers.
tunneling
spectroscopy
Inelastic electron tunneling spectroscopy (IETS) is a relatively new form of vibrational spectroscopy which is able to address problems previously unsolved by either IR or Raman. It is particularly useful for surface analysis. Hawey S. Gold and Lisa J. Hilliard University of Delaware, U.S.A.
The vibrational triumvirate Jaklevic and Lambe discovered in 1967, spectroscopy (IETS) Josephson junctions at the Ford conventional Josephson iunction insulator/metal) yields a linear applied bias voltage. However,
IR
RAMAN The Vibrational
0 165.9936/82/oooO-0/$02.7.5
inelastic tunneling whilst working on Motor Companyl. A (of the form metal/ ‘plot of current-vwhen an insulator
Triumvirate.
IETS
contaminated with organic molecules was used a change in the slope of the graph was observed at each voltage corresponding to the energy required to excite a vibrational mode of the molecule. Second derivative techniques made it possible to observe peaks in the plots at these locations. IETS is now the third form of vibrational spectroscopy available to the scientific community - the others are infrared (IR) and Raman. In contrast to IR and Raman, IETS is a non-optical technique. It involves the tunneling of electrons (in the quantum mechanical sense) from one metal to another through a barrier (an insulating oxide layer) containing sample molecules. Energy from the electrons is transferred inelastically to the vibrational modes of the sample molecule. There are several advantages and disadvantages associated with each of the vibrational spectroscopies; these are summarized in Table I. However, a few points regarding IETS should be emphasized. First, there are no quantum mechanical selection rules to restrict IET, with the result that all vibrational modes are active. An IET spectrum thus consists of IR-active modes, Raman-active modes, and optically forbidden modes, Second, the limit of detection for IETS is extremely low: as little as 5 X 10-s monolayer (or approximately 2 X 1010 molecules) of a substance can be detected on the barrier surface. This compares favorably with the most sensitive spectroscopic tech-. niques and is orders of magnitude more sensitive than either IR or Raman. 0 I962 ElJcvicr S&milk Publishing Company