Process analytical chemistry - ACS Publications - American Chemical

Anal. Chem. 1903, 65, 199R-216R

Process Analytical Chemistry Kenneth R. Beebe: Wayne W. Blaser’,.Pt Robert A. Bredeweg, Jean Paul Chauvel, Jr.? Richard S. Harrier,? Mark LaPack,t Anne Leugers: Daniel P. Martin: Larry G. Wright: and E. Deniz Yalvact Analytical Sciences Laboratory, Dow Chemical USA, Midland, Michigan 48640, and Analytical and Engineering Sciences Laboratory, Dow Chemical USA, Freeport, Texas 77541 Review Contents General Topics Chromatography Optical Spectroscopy Fiber Optics Mass Spectrometry Chemometrics Flow Injection Analysis Process Analytical Needs

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This is the first comprehensive application review in the area of process analytical chemistry (PAC). As such, it was necessary to impose limitations on the areas covered to facilitate a thorough examination of the literature in the field. Because the technology is changing so rapidly, the review focusesprimarily on articles published between 1987and 1992. In some cases, however, there are relevant reports published earlier which still represent the best technology for niche applications; these have been included where appropriate. Although many diverse techniques have been utilized to measure analytical parameters in manufacturing, the literature search was limited to those dealing with spectroscopy, separations, and mathematical treatment of analytical data. Specifically, the techniques reviewed included chromatography, optical spectroscopy, fiber optics, mass spectrometry, chemometrics, artificial neural networks, and flow injection analysis. We further limited our search to articles dealing specifically with process applications: on-line continuous analytical measurements, short-term on-line studies for process evaluation or optimization, and environmental monitoring in a process area. There are a number of technologies commonly used for making process measurements that are not addressed in this article. Some of these include physical measurements such as temperature, flow, and pressure and the more common analytical measurement equi ment such as pH meters, oxygen analyzers, electrochemical etectors, total hydrocarbon analyzers, and lower flammable limit (LFL) explosimeters. Although commonly used, relatively little has been recently published. An obvious omission in the topics contained within this review is the general area of “sensors”. Although there have been a m iad of articles published on sensors, the bulk of them have K e n laboratory evaluations. Since relatively few articles were found describing these types of devices for making lonk-term, reliable analytical measurements in a process environment, the topic was not addressed. Advances in technolo for process instrumentation generally lag several years Ehind laboratory instrumentation. T ically the concepts are researched and proven in the lagratory and then must be developed to meet the process requirements such as safety and reliability. In addition, since many on-lineprocess analytical measurements are proprietary in nature, the literature in this area is somewhat limited to those of a eneric nature or to feasibility studies performed in a researca laboratory. By the time these articles are cleared for publication, the published technolo lags that which has been reported for the comparable an ytical measurements being made in the laboratory environment. A number of general application and review pa ers written by manufacturers of process instruments have feengiven. Many of these articles are rather sketchy in technical details, demonstrating concepts rather than providing technical detail and/or

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measurement data. Many of these reviews should be read with the understanding of vendor bias. As an example, a general paper by Weiss (El)on process mass spectrometers makes reference to such vendor claims. These reviews have been grouped on the basis of applications and cited in Table I with the other published work discussed in this review.

GENERAL TOPICS A number of articles were written concerning the general concepts of process analytical chemistry. These papers represent the viewpoints of several groups involved with the development and implementation of process analytical chemist : academia, industry, and instrument manufacturers. Fallis et al. (AI) defined terms used in the process analytical chemistry area and discussed current and future focus areas being pursued by academia which could have a significant impact on process technology. Blaser et al. (A2) discussed important issues to be considered in the successful implementation of an on-line analytical system. Tyson and Willis (A3) discussed the work groups involved in the definition and implementation of an on-line instrument and the importance of teamwork and good communication to ensure long-term project success. Certain recently reported industrial applications of PAC were summarized by Riebe et al. (A4). An example was given for defining the critical parameters in a manufacturing process to implement the PAC approach. Hara (A5)used inductively coupled plasma atomic emission spectroscopy (ICP-AES) and X-ray fluorescence (XRF) to illustrate the process by which instruments that were developed for research applications can be successfully commercialized. Similarly, the important considerations in attemptingto convert a mass spectrometer originallydesigned for laboratory analyses for use in on-line environmental or process monitoring were detailed by Fjeldsted (A6). Campbell (A7) contends that the majority of instrument companies focus on applications and product development but not on basic instrument research and development. He has described examples of technology which he feels could be developed more fully by instrument companies for the process analytical market: ion mobility and flame infrared emission.

CHROMATOGRAPHY Introduction. One of the more widely used techniques for process analysis applications is process as chromatography (PGC). A recent book by Annino andkillalobos (Bl) reviewed the fundamentals and applications of PGC. A review article by Annino (B2)focused on the differences between a process gas chromatograph and its laboratory counterpart. These differences emphasize the need for reliability, low maintenance, and safe operation in hazardous areas and the need to interface the analyzer with the process control computers. Although liquid chromatography (LC) is a commonly used laboratory technique, it has not met some of the reliability requirements for on-line analyzers. LC requires more maintenance, which is not always available in process areas, than does PGC. A review of the evolution to a process LC (PLC) and current instruments was presented by Clevett (B3). A comparison of PGC vs PLC, laboratory LC vs PLC, and the options available was presented by Synovec et al. (B4). Instrumentation. According to Earle et al. (B5),the most significant recent improvements in commercial PGCs have been the use of capillary columns, the ability to temperature program the oven, and improved communication networks. An automated large-volume on-column injection technique 0 1993 American Chemical Society

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PROCESS ANALYTICAL CHEMISTRY Kenneth R. Beebe is a Project Leader in the Instrument Development Group of the Analytical Sciences Laboratory, Dow Chemical USA, Midland, MI. He received a B.S. in chemistry in 1981, and a B.S. in statisticsand a Ph.D. in analytical chemistry in 1987 from the University of Washington, Seattle, WA. His doctoral studies were in the area of chemometrics within the Center for Process Analytical Chemistry (CPAC). After graduation, he performed postdoctoral research at the National Institute of Standards and Technology in the areas of experimental design and errors in variables regression. Since joining Dow, Ken's research interests have been in applying chemometrics techniques to on-line instrumentation. He is a member of the Chemometrics Society.

Jean Paul Chauvel, Jr. is a Research Leader in the Analytical and Engineering Sciences Laboratory, Dow Chemical USA, Freeport, TX. He received a Ph.D. in chemical physics from the University of California, Davis, in 1984. He joined Dow in 1985 and has worked on process analytical projects since that time. His primary interests include the application of optical process analyzers to process applications with difficult chemistries. He is a member of the Society for Applied Spectroscopy and the American Chemical Society.

Wayne W. Blaser is a Research Manager in the Instrument Development Group of the Analytical Sciences Laboratory, Dow Chemical USA, Midland, MI. He received his B.S. degree in chemistry from the University of Wisconsin, Madison, WI. He joined Dow in 1965. His expertise and research interests have primarily been in the field of chromatographic separations and the application of on-line process analytical instrumentation. He is responsible for the analyzer resource center within Dow.

the Analytical Sciences Laboratory, Dow Chemical USA, Midland, MI. He received a B.S. from Lebanon Valley College in Annville, PA, and a Ph.D. in analytical chemistry from Purdue University in 1980. He has developed custom on-line and insitu instrumentation for process monitoring and control. His current research emphasizes fiber optic probes and process interfaces for remote measurement of absorption and scattering phenomena and the use of embedded computer systems in process analyzers for real-time data acquisition and communication. He is a member of the American Chemical Society, Sigma XI, and the Instrument Society of America.

RobertA. Bredewegis a Senior Associate Sdrentist with the Special Analysis Group of the Analytical Sciences Laboratory, Dow Chemical USA, Midland, MI. He received his B.A. (1963) at Hope College and his M.A. (1965) at Southern Illinois University. He joined Dow in 1965. His current interest is in developing on-line applications of gas chromatography, liquid chromatography, and flow injectionanalysis for understanding and optimizing chemical processes. He is a member of the American Chemical Society, the Instrument Society of America, and Sigma XI. He received a Special Recoanition Award from the Northeastern Sect& of the Instrument Society of America in 1986.

Mark LaPack is a Project Leader In the InSitu Group of the Analytical Sciences Laboratories, Dow Chemical USA, Midland, MI. He received his B.S. degree from Purdue University in 1983 and his Ph.D. from Michigan State University in 1992. He joined Dow in 1983. His research interests are in the application of membrane separations to characterization of chemical processes by mass spectroscopy. He is a member of the American Chemical Society, the American Society for Mass Spectrometry, the Materials Research Society, and Sigma XI. He received the Midland Chapter Sigma X I award in 1992.

for improvingdetection limits was developed by Morabito et al. (B6)and McCabe et al. (B7). A prevaporization chamber was described by Grob and Munari (B8). Prevaporization and removal of the solvent prior to the column was described by Gerstel (B9).A valveless circuit technique for switching flow direction in two columnsconnectedin series was reported by Mueller (BIO).Stroboscopic computerized sampling of nonstationary gas streams was described by Kalurand et al. (BI I). A unique on-column thermal desorption modulation system for sample preconcentration and introduction was described by Lui et al. (BIZ). Annino (BI3)reviewed the use of fluidics for sampling valves, detectors, etc., in PGC instrumentation. Before PLC can contribute significantlyto process analysis, improvements must be made in reliability and in the level of maintenance required. One way to reduce maintenance is to use micropacked LC columnswhich have a mobile-phaseflow rate of 1-10 pL/min. At 5 pL/min, a liter of mobile phase would last more than 4 months, while a t conventional flow rates of 2 mL/min, a liter lasts a little more than 8 h. Making mobile phase is time consuming and recalibration is usually required on each new batch prepared, making the maintenance unacceptable. The sample often has to be diluted prior to injection, making the sampling system more complex. Cortes et al. (B14)demonstrated that a micropacked LC system operated for 8 months had acceptable column performance and data reproducibility similar to that of conventional laboratory LC. Guillemin (BI5-BI8) described the use of a probe LC, where the injection, sample conditioning, and column are located in the reactor and the detector and electronics are just outside the reactor. The column was not temperature controlled, resulting in retention time variations.

This was corrected for by using the deferred standard technique, which is an independent injection of a standard or standards used as markers for computer correction of the sample component retention times. Marsman et al. (BI9) confirmed that when the deferred standard technique was used in GC, corrections could be made for changes in atmospheric pressure, sample injection errors, and incorrect instrument settings as well as prediction of maintenance and reduced calibration costs. A super speed size-exclusion chromatographic system usin short columns and conventional flow rates was describecfby Renn and Synovec (B20). Synovec (B21) and Renn and Synovec (B22) also described the use of position sensitive detectors for both refractive index and absorption detection. Murugaiah and Synovec (B23) describe the use of a refractive index gradient detector to measure the radial concentration gradient of a hydrodynamically generated concentration profile. The response is correlated to the diffusion coefficient or the analyte and, hence, to the molecular weight. Applications. A review article by Crandall et al. (B24) discussed the application of PGC to simulated distillations. Martin (B25) also described the use of PGC for the determination of boiling points. In boiling point applications calibration is normally performed using a series of compounds like n-paraffins. Dataobtained are initial boiling point (0.5% boiled off), 10% intervals of amount boiled off, and final boiling point (99.5% boiled off). Smith (B26)used a process supercritical fluid chromatograph for the determination of boiling points up to 600 "C for vacuum gas oil using supercritical carbon dioxide. Maintenance problems with carbon dioxide leakage were reported. Hall (B27)used PGC for the monitoring and control of absorption and stripping

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Anne Leugemis a Research Leader in the Instrumental Methods Group of the Analytical Sciences Laboratory, Dow Chemical USA, Midland, MI. Anne received a B.S. in chemistry from Xavier University in Cincinnati, OH, and a Ph.D. in physical chemistry from the University of Cincinnati in 1981. She performed postdoctoral research in laser spectroscopy at Syracuse University and the University of Arizona. Anne’s research interests include the application of Raman and fiber optic spectroscopy to the chemical and morphological characterization of materials.

Instrument Development Group of the Analytical Sciences Laboratory, Dow Chemical USA, Midland, MI. He received his B.A. degree from Berea College, Berea, KY, in 1981 and his Ph.D. in analytical chemistry from Purdue University, West Lafayette, IN, in 1986. Current research interests are in the development and utilization of mass spectrometry and chromatography for fast continuous on-line environmental and process monitoring applications. He is a member of the American Chemical Society, the Society for Applied Spectroscopy, the American Society for Mass Spectrometry, and Sigma XI.

Dank1 P. Martln is a Project Leader in the Instrument Development Group of the Analytical Sciences Laboratory, Dow Chemical USA, Midland, MI. He received his B.S. in chemistry from Central Michigan University in 1980. Since joining Dow in 1980 his primary interests have been the development of chromatographic and speo troscopic systems for in-situ and on-line applications.

a towers. The use of PGC for the determination of octane number using n-alkanes as reference peaks was described by Durand et al. (B28).PGC has the advantage over spectroscopic techniques of determining actual component composition, an estimate of molecular weight, and specific gravity. Kenter et al. (B29) evaluated the uncertainty of the PGC determination of the calorific value of natural gas. Chen et al. (B30) reported the use of PGC for controlling the H/N ratio during the production of ammonia. Annino and Villalobos (R31) reviewed the use of PGC for some environmental applications, includinga comparisonof direct aqueous injection vs the use of a stripper for the determination of organic compounds in water, the analysis of reformulated gasoline for Reid vapor pressure and oxygenates, and the monitoring of ambient air for worker safety. A number of papers described the determination of or anic compounds in water. Villalobos (B32) compared &ect injection and sparging; Urban (B33), Maitoza et al. (B34), and Combs et al. (B35, B36) described sparging systems. Schnable et al. (B37) developed a sparging system modified for small sample volumes. Baykut et al. (B38) developed a spray extraction system. Systems using sparging frequently have maintenance problems due to foaming and plugging. A thin-layer headspace system developed by Kozlowski et al. (B39, B40) reduces the problems with foaming. Thomas et al. (B41) and Turner (B42) also have reported on headspace systems. The use of membrane separators was described by Melcher and Morabito for liquid/liquid separations followed by GC or LC (B43, B44). Liquid/gas separations with membranes followed by GC is described by Pratt and Pawliszyn (B45) and Guseva (B46). Membrane separators have the advantage of rejecting solids and soluble salts, which reduces the problems with plugging and eliminates most of the water, but they do have equilibrium time limitations for some classes of analytes. In known process environments, PGC has been used extensively for ambient air leak detection. The advantage is its specificity; the disadvantage is the time it takes to do an analysis. If a large number of sample points are to be monitored the cycle time is often long; therefore, many of these applications are now being done by spectroscopic techniques. Development of fast micro-GC systems or the use of software to handle merged peaks may allow rapid enough analysis by PGC in the future. Mouradian et al. (B47) developed a fast GC with a cold trap inlet and variable-speed electrometer. Detection limits of 1-50 ppb and peak widths of 70 ms were achieved. Slater et al. (B48)developed a PGC system for the determination of methane, carbon dioxide, carbon monoxide, and hydrogen in an anaerobic wastewater

E. Denlz Yalvac is a Project Leader in the Analytical Sciences Laboratory, Dow Chemical USA, Midland, MI. She received a B.S. degree in chemical engineering from Hacettepe University, Ankara, Turkey, in 1976 and M.S. degrees in chemical engineering and chemktry from the University of Michigan, Ann Arbor, MI, in 1981. She joined Dow in 1982. Her specialty is automation of wet chemical analyses and implementation of analytical techniques in process analysis. Her current research interests are the development of electrochemical and spectrophotometric chemical sensors. She is a member of Sigma XI, Applied SpectroscopySociety, and the EditorialBoardof Process Control and Quality.

treatment process. Pau et al. (B49) described a conventional system for monitoring benzene and vinyl chloride in ambient air. They utilized a 200-mL bulb prior to the sampling valve to “average” the analyte concentrations and to eliminate spikes. Bronder et al. (B50)and Hanai et al. (B51)used a PGC for the continuous monitoring of aromatic hydrocarbons in air. Kuo (B52) reported the use of PGC for the determination of sulfur dioxidein air. Claytonet al. (B53)described the use of PGC for the continuous determination of nitrous oxide and sulfur dioxide in coal-fired utility emissions. Lindgren et al. (B54) used PGC for monitoring hydrogen sulfide and carbonyl sulfide in emissions from coal combustion. Nolen et al. (B55) described a mobile laboratory used to monitor emissions from hazardouswaste incinerators. Kern and Kirshen (B56),Sides and Cates (B57),Aoki et al. (B58), Baechmann and Polzer (B59), and Tsuchida et al. (B60) described the use of cryogenic trapping or the use of solid sorbents followed by flash vaporization for the determination of ultratrace levels of components. Braithwaite et al. (B61) reported on the use of a portable GC with several different detectors for the monitoring of ambient air in coal mines for hydrocarbons and oxygenates. Mehrotra and Kumar (B62) described the use of PGC to monitor methane in flue gas leaving a fluidized bed reactor used in the reduction of iron ore. Mueller (B63) used multidimensional PGC to monitor complex vapor mixtures. A custom-built PLC system used successfully for several years to monitor the production of biosynthetichuman insulin was described by Cooley and Stevenson (B64). The system recirculated the mobile phase to reduce maintenance. The 97 5% uptime was attributed to location of the analyzers in the control room, daily check on performance by trained personnel, long-term maintenance by the group that developed the instrument, and dedication to the instrument by the operating personnel due to the importance of the data. Melcher et al. (B65) and Melcher and Bouyoucos (B66) described a custom-built membrane/LC system that was used for the determination of phenolic compounds in water. The system used a membrane separator to clean up the sample and concentrate the phenolic compounds. The system was located in a laboratory and required weekly maintenance. Fagan and Haddad (B67) used an LC system with postcolumn derivatization for the determination of cyanide in ore leach liquors. Van de Merbel et al. (B68)developed an on-line LC system for monitoring laboratory-batch fermentations for lactose, glucose, and fructose. Maintenance on the inertial membrane filter used for sample cleanup was optimized to ANALYTICAL CHEMISTRY, VOL. 65, NO.

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perform satisfactorily for a 20-h run. Monitoring of bioreactors b LC for lactose, gl cerol, acetate, and succinate was reportel by Favre et al. (269). Sauter (B70) described an on-line LC for monitoring a Conalab automated reactor. A dual-syringe batch dilution system was used to dilute the sample prior to injection. Thompsen and Smith (E71) developed an on-line ion chromatography system using a hightem eraturebatch sampling system tomonitor the production of aiipic acid. Fathi (B72)reported on the use of an on-line size-exclusion chromatograph made from laboratory components installed in a purged box. The system was used to monitor a polymer pilot plant facility. A four-port valve was used to pulse small portions of sample into the solvent. A portion of the diluted stream was then injected into the chromatograph. Lynch (B73) gave an overview of the sampling requirements, equipment, data handling, and maintenance experiences of several on-line ion chromatography systems. Ebdon et al. (B74) described an ion chromatography system equipped with an ion exchange preconcentration column to determine trace metal ions in a brine stream. Bond (B75) reviewed the methods used for continuous determination of metals in industrial effluents. Similarily, Bond et al. (B76)reported on a procedure using LC with electrochemical detection. Miscellaneous. Pevoto and Converse (B77) reported on the use of statistical quality control to determine the frequency to calibrate an analyzer. The authors suggest that periodic calibration of an analyzer may lead to overadjustment. Renn and Synovec (B78)described the use of a solute-independent calibration method for universal calibration. The technique required that the standards and samples be injected sequentially and simultaneously into two different chromatographs. Synovec et al. (E791 and Bahowick and Synovec (B80) described a technique for data analysis using a point by point ratio of sequential chromatograms after baseline subtraction to recognize interferents, quantitate, and correct for retention time variation, peak shape change, and mild detector nonlinearity. Villalobos (B81)compared method development for PGC to laboratory chromatography emphasizing sample type, sampling system, instrument location, injection system, multicolumn and column switching, and detectors. OPTICAL SPECTROSCOPY Reviews. Many types of on-line and in-situ analyses use an optical measurement to obtain chemical information about processes. Filter-based optical instruments have been used extensively in process analysis. Increasingly, however, the more complex scanned grating and Fourier transform infrared (FTIR) instruments are making inroads into the process control area for applications where increased resolution and selectivity are demanded. A plications using fiber optic interfaces or probes are groupe together and discussed under the Fiber Optics section of this review. Nyquist et al. (C1) and Putzig et al. ((72) have reviewed the applications of IR, near-IR, and Raman to laboratory measurements and laboratory-based in-situ studies utilizing these techniques. These applications are excluded from this review, which is focused primarily on process applications. Applications that deal with remote monitoring b optical techniques for environmental studies are also excludred from this review as these applications have been reviewed elsewhere by Devara (C3),Steinbrecht et al. (C4),Sasano (C5),and Gosz et al. (C6). Fluorescence and X-ray fluorescence applications as applied to process monitoring are also reviewed herein. General discussions on the use of on-line IR analyzers for the analysis of process streams have been iven by Wilks (0, McIvor (C8), Converse (C9), and #illis (1210). A discussion on the use of FTIR analyzers for the analysis of process streams was given by Morrison and Solomon (C11) and by Doyle (C12). McDermott (C13)and Bickel (C14)have discussed the use of on-line near-IR analyzers for process monitoring. Rostaing and co-workers (C15) presented a eneral discussion of the principles and applications of onme IR and near-IR analyzers in the control of pharmaceutical processes. An overview of the use of ultraviolet (UV)analyzers for process control was given by Mooney (C16). Kalnicky and Ramanujam (CI7) discussed the use of XRF spectroscopy to on-line applications in polymer blending, monitoring of steel-pickling bath composition, catalyst preparation, and

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determination of elements in petrochemical manufacturing. Mineral processing applications using XRF have been reviewed b Hietala and Kalnicky (C18),Lundan (C19),and Dulski ( z 2 0 ) . Several papers focused on the potential of optical spectroscopy for on-line process control and monitoring a plications. McIntosh (C21) discussed the potential of &IR combined with attenuated total reflectance (ATR) spectroscopy in batch monitoring applications. The potential of flame infrared emission (FIRE) spectroscopy for on-line analysis has been discussed by Spitler and Chen (C22). Bruce and Dhaliwal ((223)have discussed the various approaches for moisture analysis and sampling cell designs needed for different concentrations of water using on-line IR and nearIR. The use of transient IR spectroscopy in the on-line analysis of solid materials has been described by Jones and McClelland (C24). The 700-1100-nm near-IR region for use in process applications has been discussed by Schrieve and co-workers (C25). Thompson (C26) discussed the use of statistics in calibrating and validating on-line near-IR analyzers. Chauvel and May (C27) described the technical and practical considerations for the application of FTIR to online chemical analysis in a process environment. Factors discussed include instrument stability, resolution, accuracy, precision,linearity, signal-to-noiseratio, and sample handling. Process applications discussed included ambient air leak detection monitoring, analysis of trace impurities in liquid chlorine, and feasibility studies to evaluate the utility of filterbased IR and near-IR instruments for on-line applications. Applications. Infrared, Near-Infrared, and Fluorescence. Farquharson and Chauvel ((228) utilized FTIR to monitor the reaction and reaction products of phosgene with steam and ammonia to aid in the design of a pilot-scale scrubbing tower. Wilks (C29) reported on the development of a cylindrical internal reflection cell that allowed for the measurement of IR spectra on aqueous process streams. Erickson et al. (C30) evaluated the use of IR emission for analysis of liquid samples for composition and thickness. Emission spectra were compared with transmission spectra. A reaction monitoring system developed to monitor chemical reactions using FTIR was reported by Rein (C31). Niemela (C32) reported the development of an industrial process analyzer that incorporated the use of a four-channel P b salt detector to replace the traditional tilting filter wheel construction. A new solid-state acoustooptic tunable filter (AOTF) analyzer operatin in the IR for simultaneous analysis of CO, COz,SOz,NO, and BO2was reported by Nelson (C33). The analysis of caustic streams in the presence of ionic and nonionic contaminants by near-IR methods was compared with flow injection analysis and titration methods in a paper by Watson and Baughman (C34). Kunikawa et al. ((735) reported on the use of near-IR spectroscopy to monitor the continuous sulfonation of or anic hydroxy compounds. In a study reported by Izcue and Krafft (C36),IR spectroscopy was used to monitor relative concentrations of reactants and products in the manufacture of lubricating greases. Friedrich et al. (C37)used FTIR spectroscopy with a gas cell to measure the distribution of methylchlorosilanes in a flow reactor formed from the copper-catalyzed reaction of chloromethane and silicone. The use of continuous on-line filter photometers in the IR and UV region in a maleic anh dride process production plant was described by Cardis anfBrewer ((238). The instruments were ap lied to the measurement of butane in a butane/air mixer a n f t o the measurement of butane and maleic anhydride concentrations in the reactor off-gas. A patent application was described by Shih et al. (C39) for the determination of phosphate layer thickness and composition of a phosphate-coated surface usin IR reflectance spectroscopy. A visible/near-IR spectral cfatabase for plutonium solutions was developed by Day et al. (C40)to monitor process solutions at the Los Alamos Plutonium Facility. The analysis of water content in many products and raw materials is very important in many industries. Recent measurements usin IR detection schemes are discussed by Brown (C41), Van den Hauten (C42), and Hanebeck et al. (C43). Pivonka (C44)applied FTIR to the analysis of trace amounts of moisture in HC1, a measurement needed to characterize the performance of HCl gas purifiers for use in semiconductor applications. The on-line configuration per-


mits direct quantitation of HC1gas dryer efficiency,capacity, and flow rate specifications. A method and application for the determination of semiconductor-processingchemicalsby near-IR spectroscopywas disclosed in a patent application by Koashi and co-workers (C45).Strang and co-workers (C46)evaluated FTIR for the detection of various gases and vapors generated at semiconductor manufacturing sites. In a related pa er, the authors (C47) evaluated the detection limits of an FTfR spectrometer e uipped with an indium antimonide/mercury cadmium te%uride sandwich detector and 20-m path-length gas cell for the analysis of a group of semiconductor gases. Shi (C48) described the use of an IR spectrometer modified for the elimination of back ound interference. The modified instrument was applizto monitoringethylenein the production of ethylene oxide by high-temperature oxidation of ethylene in the presence of a silver catalyst. Applications for the determination of methane, carbon monoxide, and carbon dioxide in the presence of water vapor were resented. Also presented were applications for the an&ses of carbon monoxide in carbon dioxide mixtures and of carbon dioxide in methane and sulfur dioxide. McDermott (C49) has discussed the use of near-IR in the food industry. The on-line measurement of CO2 in beer production by IR measurementswas discussed by Wilks (C50). A discussion of near-IR for monitorin the refractive index of glucose solutions, original wort and afcohol content in beer, humidity, fat and protein content in milk powder, and fat concentrationsin soft cheese was given by Grevesmuehl(C51). Continuous monitoring of beet su ar with an on-line near-IR spectrometer was discussed by darchetti (C52).Berg and Kolar (C53)investigated the on-line use of near-IR spectroscopy for the determination of water, fat, protein, and hydroxyproline in beef and pork samples. Sadeghi-Jorabchi et al. ((254)discussed the analysis of the hydro enation of vegetable oil in margarine manufacturing using If3 spectroscopy with ATR. Chasseur (C55)described the use of near-IR reflectance to assay cimetidine (Tagamet) anules on-line. Selected wavelengths were used to avoid efgcts of color and granule size. Walling and Dabney (1.256)described the use of near-IR reflectance to determine the amount of water, detergent, solids, and glycerol in sham 00. Davenel et al. (C57)compared filter-based near-IR anfFT-near-IR instruments for the analysis of wine fermentations. The process and apparatus for the control of aerobic fermentation using cytochrome IR absorption was described in a patent a plication by Hess (C58).Sode and co-workers (C59)descriged the use of on-line fluorescence to monitor marine cyanobacterialcultivation by tracking the intracellular hycocyanin content. Fluorescence data were compared to emacytometer data to show linearity between the two techniques. On-line IR spectroscopy was used by McPeters (C60)to measure composition of polymer blends and copolymers exiting an extruder. Stengler and Weis (C61)desi ned and applied a high-pressure, high-temperature flow cefl for the on-line IR analysis of molten polymers. The authors determined the presence and amount of additives, controlled the polymerization process, and analyzed the end groups. A process and apparatus for controlling the manufacture of P o pers using IR spectroscopy was described by Laurent an co-workers (C62).These authors also described a process and the use of an IR spectrometer for the manufacture of poly(oxyalky1enes) (C63).The principles of IR technology in the on-line measurement and control of coextrusion components/layersto improveproduct quality were discussed by Marchland and Sipos (C64).Weis and Volgmann (C65) have applied a filter-based IR instrument for the on-line analysis of additive concentrations in a pol olefin production process. Transmission measurements on t i e flowingpolymer melt using a filter centered at 1740 cm-' and a reference line at 2230 cm-' gave accuracies reported to be 0.05% by weight absolute. Pate1 (C66)ap lied an IR analyzer to monitor an amide slip agent a d d e f to a polymer. The slip agent concentration, detected at levels as low as lo00 p m, was varied during extrusion of molten polyethylene. IR Ztection methods are also widely ap lied to the determination of film thickness in polymers. 8ecent applications include the determination of polymer film thickness by Zhang (C67), the

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measurement of coating thickness by Fukui (C68), and the measurement of thin organic filmson metallic sheets by Sturm

(C69).

The tem erature of a natural gas flame and the temperature in a heatetair jet were measured by Shannon et al. with IR spectroscopy using an C02 absorption band (C70).An online measurement system to detect the dew point and CO gas concentration simultaneously in a high-temperature furnace using IR absorptionwas described by Iuchi and Hoshino (C71). Zabielski and co-workers (1272) reported the results of a project to control the fuel/air ratio on industrial burners using IR emission spectroscopy of natural gas flames. A technique was developed by Maeda et al. (1273)for the determination of gas components such as CO, COZ,and H2O a t yrometallurgical temperatures greater than lo00 "C. F h R was applied to stack gas monitoring in a Ti02 production facility by Cronin (C74).Past monitoring of stack gases in the process utilized IR and UV filter-based instruments for the analysis of COz, CO, SO2, HC1, and COS. FTIR was applied to the procedure to improve the accuracy and reliability of the analysis a t low concentrationsof CO. A 1-m-diameter,Tefloncoated, stainless steel sphere was constructed as a tool for conductin IR studies of the atmospheric chemistry of toxic chemicals%yStone (C75).The chamber was equipped with an in-situ, multipass o tical system allowing a path length of 106 m to be used in tEe analysis. A patent for an apparatus and method for near-IR reflectance analysis of successive samples was disclosed by Johnsen for the measurement of composition of viscous or solid materials (C76).Herrala and Niemela (C77)developed a miniature FTIR spectrometer for industrial on-line applications. New techniques and accessories for IR analysis of liquids and solids in on-line and off-line sampling were discussed by Tregid o (C78).The factors affecting performance of rugged muftiwavelength near-IR and IR analyzers for industrial rocess measurements were discussed by Hyvarinen an8Niemela ((279).The development of a continuous on-line automatic near-IR analyzer was disclosed in a patent by Lape e et al. (C80). Doyle and Jennings (C81) discussed the devegpment of a deep-immersion probe that can be interfaced to an FTIR spectrometer to produce attenuated total reflectance spectra. Thompson ((282) discussed the use of statistics in calibrating and validating nearIR on-line analyzers. The history and future of process analyzer maintenance was discussed by Wright (C83).McCurley (C84)and Xu (C85)have reported on troubleshooting, predictive maintenance, calibration, and temperature control for process IR analyzers. Raman. The application of on-line Raman s ectrosco y to the cryogenic isotope separation system was fescribed y O'Hira et al. (C86).A flow-through cell was used to sample three columns in the process. Quantitative analysis of H2, HD, HT, and D2 in the distillation columns gave comparable sensitivity to a GC method. Compared to the GC method, the system had a faster analysis time (1 min compared with 40 min for the GC method) and did not consume gases or enerate waste gases. Eckbreth and Stufflebeam (C87) !iscussed the use of coherent anti-Stokes Raman scattering (CARS) as an analytical approach tononintrusive temperature and species measurements in combustion and plasma processes. Ricard et al. (C88)and Lueckerath et al. (C89)have described application of CARS to monitor deposition processes in semiconductor manufacturing. Concentration fluctuations of two nonreactive liquids in a stirred tank reactor were monitored by Kraus and Schneider using CARS (C90). Getty et al. (C91)examined the utility of resonance Raman spectrosco y to detect low concentrations of benzene and trichloroetRylene in methane diffusion flames. Flame temperature was also measured with the technique. Smith et al. (C92) discussed a Raman system for on-line multiplecomponent gas analysis. The system, configured with eight discrete detectors, was used to simultaneous1 monitor 0 2 , C02, NO,, SOz, NH3, total hydrocarbons, andlN2. UV-Visible. Small and Hassel (C93) described the use of a commerciallyavailable diode array analyzer for the analysis of gas or li uid streams. Several papers by Saltzman et al. (C94-C96)\ave reported on efforts to measure and control the sulfur recovery process. Measurements of SO2 and HzS concentrations in the tail gas are made using filter-based photometric devices or linear diode array spectrometers

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operating in the UV-visible range to control rocess efficienc Mooney (C97) described the use of a iouble-beam U? spectrometer to obtain a differential measurement for the analysis of phenols in water and H2S and total S in natural gas. Bertolin (C98) discussed the use of UV, visible, and near-IR spectroscopy to monitor a glass production process. Quality measurements and estimation of concentrations of important elements in the glass can be made using the instruments in conjunction with spectral processing. X-ray Fluorescence. On-line XRF has been a plied to the continuous analysisof elements in the mining and)chemical industries. Modern steel production utilizes XRF for continuous on-line elemental composition. Matsumoto and coworkers (C99) have applied XRF to the production of Ni-Zn electroplated steel sheets. XRF was used to control the concentrations of Ni2+ and Zn2+ions in a plating bath and the coating weight and nickel content of the coating alloy to ensure product quality. Similarly, Jones (C100) developed an XRF spectrometer to measure Sn and Fe in plating baths. The spectrometer was reported to have an operating range of 20-50 g/L Sn and 5-15 g/L Fe with a precision of f0.5 g/L. Yamamoto and co-workers ( C I O I ) also utilized on-line XRF in combination with an X-ray diffraction (XRD) method to analyze a double-layer electroplated steel strip. The plated alloy weight of each layer and the Fe content of the doublelayer electroplated steel strip were determined. Verman and Sidorov (C102)have discussed the re roducibilityof the XRF analysis in ore flotation slurries fore!t elements Mo, Cu, and Fe. The use of XRF for on-line monitoring of Fe, Ca, Si, P, Mg, and A1 and IR absorption for the monitoring of C in a steel manufacturing process was described by Subrahmanyan and co-workers (C103). Holt and Tily (C104)described the development of an on-line XRF control system to monitor off gases generated by the pyrometallurgical processes in the refining of copper. Watson (C105) described a commercially available XRF spectrometer developed for hostile environments. Pilz and co-workers (C106) reported the use of on-line XRF for the analysis of heavy elements in nuclear fuel reprocessing solutions. U, Np, and Pu were detected from ppm levels up to saturation levels of about 400 g/L. Weiss (C107)evaluated a commercial XRF spectrometer installed in a magnesite processing plant to monitor CaO and Fe203 as well as pulp density of four different products. High data throughput with the instrument allowed for a quicker response to changes in the flotation process and was reported to result in more consistent quality and improved process efficiency. A commercial XRD/XRF analyzer was evaluated by Ahonen and co-workers(C108)for on-site control of an apatite concentrator and a talc concentrator. The on-line system results compared with laboratory analysis data showed deviations of approximately 10%. Hietala and co-workers (C109) described a commercial XRF analyzer developed for the determination of sulfur and lead in asoline, calcium in polymers, and nickel in metal treatment %aths. Software was developed by Leland et al. (C110) using fundamental parameter programs to reduce the number of standards required and time needed for on-line standardization of an XRF analyzer. The software is applied to the determination of lead and bromine in leaded gasoline and to the determination of P, S, Ca, and Zn in lubricating oils.

FIBER OPTICS Introduction. While the use of optical fiber for process analytical measurements generally involves optical spectroscopy, this section has been treated separately due to its enormous potential for process monitoring and control applications. Well-designed probes, installed directly and unobtrusively into process streams, generate physical as well as chemical information about the process in real time. Ultimately a fiber optic sensor system may achieve the status of process transducer, with reliability specifications and maintenance intervals equivalent to conventionaltemperature and pressure devices. In-line chemical composition measurements, if made with sufficient precision and frequency, may become the primary feedback input to the process control algorithm. Review. Most fiber optic sensor research to date has utilized the intrinsic properties of fibers for detection or has 204R


modified the fiber by some means to create chemical specificit . Wolfbeis (01)has recently documented much of this broaitechnology base in detail ~ 1 7 5references). 0 Early attempts to convert several physical parameter sensors to fiber o tic versions for process use yielded some successes (02).gecent reviews covered selected chemical sensors (031, monomode interferometric physicalsensors (04,fluorometric analyzers (05),multivariate calibrations (061, and continuous clinical monitoring (07). While these applications exploited the chief advantages of o tical fiber use in process areas, i.e., nonconducting, electricaPinterference immunity, high bandwidth, light weight, etc., the long-term stabilityof the sensin region in contact with the process has usually been the weaf link. Limited lifetime, uncompensated signal drift, re ent consumption, and process contamination are typical f%re modes. Although many sensor reports claim potential for on-line chemical applications, only those with documented installations, specific attributes, or unusual process potential have been included below. Applications. In the past five years, Raman spectroscopy has received increasing attention as an analytical tool for on-line and in-situ analyses. This is due in part to the excellent throughput of optical fibers in the visible and near-infrared regions where small, portable, air-cooled lasers may be used for excitation and to the availability of highly efficient detectors such as silicon charge-coupled devices (CCD). Raman spectra can now be acquired in seconds using CCD detectors, as compared with the many minutes required with a scanned grating and a photomultiplier tube detector. Moreover, Raman spectra are composed of vibrational fundamentals and the spectra are usually quite simple, obviatingthe need for sophisticated mathematical treatments. Although there has been much activity in this field, no published reports of permanent on-line installations of this technology were found. There have been several reports of instrumentation developments, in-situ studies, and feasibility studies to evaluate the technology for permanent installations. Examples of such reports are given by Vess and Angel (08), Carraba et al. (D9), Leugers et al. (DIO),Roberts et al. ( D l l ) , McCreery (012),and Schoen et al. (013). Infrared applications utilize transmission through an optical waveguide, absorption by the sample, and transmission back to the detection system. In the near-infrared the end point of a transesterification reaction was determined by monitorin the decrease in poly(ethy1eneglycol) absorbance via a parti3 least squares (PLS) model (014).Mackison et al. (015)used a Fourier transform near-IR to monitor alcohols a t 1-2 pm in an in-line process interface over 2 km of silica fiber. Farquharson et al. (016)coupled optical fiber to a FT-nearIR spectrometer to monitor polymeric properties on-line at an extruder exit port. Kemsley et al. (017interfaced ) another FTIR spectrometer to both silicaand zirconium fluoride fibers to monitor sugar and alcohol in fruit juice concentrates. Infrared fiber optic sensors for the remote detection of hydrocarbons operating in the 3.3-3.6-pm region were developed by Matson and Griffin (018). A high-pressure flowthrough cell and a remote evanescent wave liquid cell were developed and used in the 3000-6000-cm-*region with heavy metal fluoride optical fiber (D19).High-temperature measurements of combustion gases in a blast furnace were made with a FTIR using a water-cooled fiber optic probe (020). Melling et al. (021) mounted a randomized bundle of chalcogenide glass fibers transmitting in the mid-IR on the collimated external beam port of various laboratory grade FTIR spectrometers to make remote measurements in research-scale reactors. Gas correlation spectroscopy, with reference cell modulation via pressure or Stark effect means, was implemented remotely with optical fibers (022). A diode array spectrometer and fiber optic interface was used to analyze uranium and plutonium ions in the presence of interfering species in the 300-1000-nm range (023). O'Rourke (024)discussed the advantages and problems of applying chemometrics to the determination of these systems. Peck et al. (025) monitored a methanogenic fermentation reactor with a fiber optic fluorescence probe. Ethanol was monitored noninvasively through the glass wall of a fermentation reactor using a diode array detector in the 700-1000nm range (026).A fermentation process was monitored using a fluorophore-based pH indicator at two wavelengths (027). Zhu and Hieftje (028)utilized a packed bed of chloramine-T


in a flow-through cell to selectively oxidize bromide to bromine. A fiber optic sensor with flowing rea ent and irreversible chemical reaction indicator monitorecf groundwater contamination ( 0 2 9 ) . Process capable fiber optic refractometers have been used to infer chemical composition from changes in refractive index utilizing a Fabry-Perot interferometer ( 0 3 0 , 0 3 1 ) or focal position ( 0 3 2 ) . A highpressure cell designed to allow optical measurements in the near-critical pressure region which is independent of refractive index of the fluid media was described ( 0 3 3 ) . Harner ( 0 3 4 ) designed a sealed fiber optic probe which compensates for differing thermal expansion coefficientsand a general purpose process interface for in-line installation. Driver et al. ( 0 3 5 ) reported on some environmental effects on optical fiber used for remote sensing.

MASS SPECTROMETRY Introduction. The field of process mass spectrometry (MS) is dynamic and continues to develop to meet challenging process demands. Most ap lications cited herein were carried out using electron im act ( I) conditions with either magnetic, y d r u p o l e , or tan em analyzers unless otherwise noted. hemical ionization (CI) and atmospheric pressure ionization (API) are increasingly making inroads into process applications. For the techniques where a reagent gas is required, sample matrix conditions are of the utmost concern. The potential problems and drawbacks of these techniques when applied to unstable matrices have been described (E2-E5). Increasingly,sample introduction/ionization techniques, such as continuous-flowfast atom bombardment (FAB), ion spray, thermospray, and electrospray are being applied to continuous monitoring applications in the laboratory where reduced fragmentation and ionization of thermally labile analytes is needed (E6-E9). Long-term performance still demands close scrutiny before moving to permanent on-line installations since these techniques are still under development in the laboratory and have yet to be proven in long-term, continuous monitoring applications. Applications. Environmental. Mass spectrometry has a si nificant presence in process environmental monitoring app!ications. A major thrust in the field has been in the development of small, portable mass spectrometers for shortterm quantitative and qualitative continuous monitoring applications at manufacturing and waste sites. The configuration for these small systems is continually changing, with modifications made to their sampling systems to meet the diverse range of problems in which they are applied. A number of environmental applications for on-line mass spectrometry utilize membrane extractors to provide a sample to the analyzer that is enriched in analyte. The fundamental principles of membrane extraction and various designs of these samplin systems have been described (EIGE14).Gas chromatograpiy (GC), discussed previously, is often utilized in combination with MS in environmental applications in order to bring enhanced specificity and selectivity to the anal sis of complex sample streams. Short-column GUMS has Been utilized by McClennen et al. (E15) and Arnold et al. (E16) to provide on-line monitoring of the combustion roducts in a rotary kiln incinerator. Polycyclic aromatic [ydrocarbons and substituted benzenes were separated and detected at parts-per-billion (ppb) levels in this application. A field-portable instrument with nanogram detection limits has been evaluated by Robbat ( E l 7,and Xyrafas et al. (E18) for analysis of 35 volatile organic compounds and applied to the analysis of drinking water and groundwater. Parts-permillion (ppm) detection limits were reported by Grant and Kahn (El 9 ) for monitoring severalenvironmentally important organic compounds in wastewater and wastewater treatment plant effluents. Campbell et al. (E20) have reported that chlorobenzenes and chlorophenols have been monitored in the vent of a sewage slud e incineration process by on-line mass spectrometry with caemical ionization. Unstable gasphase ions in flames have been studied on-line by Axford and Hayhurst ( E 2 0 Ions were extracted from flames and introduced into a mass spectrometer via a metal sampling nozzle with an applied voltage. The effech of experimental parameters on the analysis were discussed. A membrane sampling system and a direct leak valve for an ion trap have been reported by Hemberger and co-workers

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(E22)for the monitoring of combustion products and for the monitorin the subsurface vapor transport of volatile or anic compoun s at chemical waste areas. More recently, hemberger et al. (E23) and Cisper et al. (E24) reported the development of a field-portable gas chromatograph ion trap mass spectrometer with different samplin modules for direct injection, direct air sampling, and tube iesorption. Applications for purge-and-trap analyses of volatile organic compounds (VOCs) in water and soil, for the determination of VOC removal efficiency of a pilot water purification system, and for military applications were discussed. Detection limits in the parts-per-trillion (ppt) range were reported for trichloroethylene in water, with most analyses requiring approximately 20 minutes. Thompson et al. (E25) and Wise et. al. (E26) have reported the development of an air sampling interface for real-time continuous monitoring for a portable ion trap mass spectrometer. Sampling modules were developed for air monitorin , purging of liquids, and thermal desorption. Detection Emits reported in these studies for benzene, trichloroethylene, and tetrachloroethylene were 16, 11,and 14 ppb, respectively. Detection limits for nonvolatile components such as naphthalene, methyl salicylate, and diisopropyl methyl phosphonate were 10, 50,and 500 ppb, respectively. Betz ( E 2 7 , E B )has described the use of a mobile mass spectrometer to quantify 0 2 , N2, CO2, and CH4 and to identify volatile compounds in the soil at landfills. A commercial mobile mass spectrometer equipped with membrane and GC sampling systems has been developed by Matz and Forbes (E29)for the on-site identification of trace componenta in the environment. The instrument was evaluated by Kowalski et al. (E30,E31) for on-site characterization of polychlorinated biphenyl and polycyclic aromatic hydrocarbon contamination in soil samples at Superfund sites. Onsite data were com ared to those of a confirmatory laboratory. A short-column G&on trap MS was evaluated by McClennen et al. (E321 for repetitive analysis of thermally desorbed contaminants from soil. Low-ppb detection limits have been demonstrated for analyses requiring less than 1 min. Meuzelaar and co-workers (E33-E35) have also developed a battery-powered GC/MS system for on-site monitoring of environmental samples. The quadrupole system is reported to weigh less than 35 kg and is equipped with a custom-built direct atmospheric vapor sampling inlet in combination with a short-column transfer line for sample introduction. Preliminary detection limits of approximately 1 ppm were reported using selected ion monitoring. Wyatt and Koslin (E361report that a small magnetic sector mass spectrometer has been utilized on a nuclear submarine to continually monitor air quality and provide continuous feedback to on-board personnel. Sinha and Gutnikov (E37) described a miniaturized magnetic focal plane mass spectrometer that covers a mass range from 25to 500amu equipped with a gas chromatograph with microbore columns developed for short-term field studies. Utilizing array detection for the simultaneous detection of all ions, this system was reported to have high sensitivity (7.5X lW4g of benzene) and a linear dynamic range greater than 1000. New materials of construction for the magnet and yoke have been evaluated by Sinha and Tomassian (E38)to reduce the total weight of the system. Real-time measurements of thermospheric composition by mass spectrometry have been reviewed by Spencer and Carigan (E39). The use of mass spectrometry on board a rocket or satellite is discussed. Tandem mass spectrometry or mass spectrometry/mass spectrometry (MS/MS) is also increasingly making inroads into the continuous monitoring arena. For many environmental applications, API is the ionization method of choice due to its high sensitivity and selectivity when matrix conditions in the ionization source are stable (E2-E4). Kenny and co-workers (E40) re orted the use of API-MS/MS in a jet aircraft to collect amtient air data at altitudes between 2400 and 10 000 ft in the study of conditions affectin global climate change and to profile the plume from a trash-{urnin power plant. An API triple-quadru ole instrument was used by Ketkar and co-workers (E41)to letect ultratrace levels of chemical warfare agents Sarin (GB) and 0-ethyl S-[2(diisopropylamino)ethyl]methylphosphonothiolate (VX) in air. Using single parent-to-daughter ion monitoring, the system had detection limits of 7.2 and 6 ppt for GB and VX, respectively, with an analysis time of 15 s. Two parent-to-

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daughter ion transitions were shown to increase specificity in the analysis while still providing detection limits for GB and VX of 14.1 and 100 ppt, respectively. A mobile lowressure chemical ionization tandem mass spectrometer has een applied by Kurlick (E42)to the measurement of volatile organic chemicals in indoor ambient air at eight single family homes located near an Ohio Superfund waste site. These results were found to be inconclusive due to the presence of a number of targeted compounds in normal household gases. Ketkar et al. (E43) report the evaluation of GC/CI-Fourier transform MS to determine interferences found in toxic stack gases. Advantages that tandem mass spectrometry can offer to the anal sis of the effluent in incinerator stacks were discussed, aythough unstable background interferences were shown to be a consistent source of problems in these analyses. Sunner and co-workers (E441 report that methane-air combustion products have been successfully monitored by AF'I-MS/MS. The products detected included polycyclic aromatic hydrocarbons and singly oxygenated polycyclic aromatic hydrocarbons. Ketkar and co-workers (E5, E45, E46) have described the merits of monitoring incinerator stack effluents by API-MS. An API tandem mass spectrometer system was demonstrated with ppt level detection capabilities for volatile compounds in air. In a simulated stack environment model, competitive ion-molecule reactions were demonstrated to reduce analyte sensitivity, making quantitation difficult for dimethyl methyl phosphonate when diisopropyl methyl phosphonate was present as an interference. This group has shown the API technique to have difficulty in quantitating GB when interferences possessing proton affinities higher than the targeted analyte were present in the analysis of a liquid agent incinerator. Similarly, the sensitivity of API-MS to an analyte, in the presence of another analyte with a higher proton affinity, was used to model the ion-molecule chemistry occurring in the ionization source. These researchers also reported enhanced detection of trace quantities of analytes when the ionization source was operated with a high density plasma. Careful control of ion-molecule chemistry in the API ion source can be utilized to add selectivity to the measurement. Benzene charge exchange in a corona discharge atmospheric ion source has been reported by Ketkar et al. (E47) to be extremely sensitive for detecting low proton affinity compounds in air. Detection limits of 12.7 ppt were reported for 2-chloroethyl ethyl sulfide in ambient air. Eisele et al. (E48) reported the real-time detection of atmospheric species a t the sub-ppt level using an atmospheric pressure chemical ionization mass spectrometer (APCI/MS) equipped with a flow reactor to increase analysis specificity. The ion chemistry in the chemical ionization flow reactor is reported to be well controlled, allowing the production of single reactant species to react with the sample molecules. Examples are given showingthe detection of dimethyl sulfide, sulfur dioxide, and caryophyllene with detection limits of 0.5, 0.2, and 0.5 ppt. Further work with the APCI/MS instrument has been reported by the group (E49)showing,the detection of dimethyl sulfoxide mixing ratios in ambient air at approximately 0.5 ppt with 60-s integration times. A method using negative APCI/MS has been developed by Karellas et al. (E50) for the identification and quantitation of HCl at sub-ppb levels in complex ambient air matrices containin a variety of chlorinated species. Slivon and coworkers (151,E52) have reported the use of a helium-purged flow membrane cell for the real-time monitoring ppb levels of regulated volatile organic compounds in municipal drinking water. Helium was used to transport organic compounds to the ion source through the interior of a tube membrane which is immersed in the aqueous samples. A quantitative membrane sampling technique has been developed by LaPack et al. (E53) for the analysis of organic compounds in multiple liquid and gas streams and applied to the analysis of a biological wastewater treatment process. Mass balance determinations were performed by quantitatively measuring the organic contaminants in the influent wastewater stream, in the effluent water stream, and in the effluent air stream, demonstratin the biode radability of a variety of organic compounds. both shorexased and boat-mounted applications are described by Harland et al. (E54) for monitoring volatile organic compounds in natural waters by mass spectrometry. Hambitzer and co-workers (E551 describe a

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differential electrochemical mass spectrometric (DEMS) technique for monitoring volatile organicchemicals in aqueous streams. The on-line characterization of aerosols has been described by Dworzanski and co-workers (E56)and anumber of analytical techniques, including mass spectrometry, have been reviewed by Niessner (E57) for this application. Biofermentation. The role of mass spectrometry for the continuous off-gas and broth analyses of fermentation rocesses have been reviewed by Heinzle (E58),Berecz anc/)coworkers (E59), and Nishi (E60). On-line fermentation chemicalanalysis permits the determination of metabolic rates of biological processes and the optimization and control of such processes. Commercially available quadrupole mass spectrometers (E61)and magnetic sector mass spectrometers (E62,E63) configured for continuous on-line monitoring of fermentation processeshave been described. User-developed mass spectrometer monitoring systems have also been developed and configuredfor process monitoring of fermentation off-gases and broths, many of which are cited below. Camelbeeck et al. (E64) reported the use of a capillary inlet with a magnetic sector mass spectrometer to analyze headspace gas from air-sparged aqueous solutions of methanol and ethanol. In a somewhat related paper (E65),the group reported that two important factors influencing the on-line analysis of alcohols were the response time of the analyzer and the adsorptive capacity of the sampling tube that transports the analytes to the analyzer. Nam et al. (E66) reported the on-line monitoring of oxygen uptake rate and carbon dioxide evolution rate used to monitor the material balance in a Candida utilis fermentation process. Nishi and Tateishi (E67) have reported the use of multiport sampling in fermentation applications where carbon dioxide, argon, nitrogen, methane, ammonia, and ethanol vapor concentrations were monitored for Bacillus caldolyticus and Saccharomyces cerevisiae fermentation processes. Hayward and co-workers (E68, E69) describe a membrane flow injection sampling system used to continuously extract the major products from fermentation broths and to introduce these products into a mass spectrometer. The production of 2,3butanediol by the microorganisms Klebsiella oxytoca and Clostridium acetobutylicum was monitored. Methane, isobutane, and water have been evaluated as CI reagent gases. These studies were further used to model a fermentation process (E70).Similarly, a Bacillus polymyxa fermentation process has been monitored by the grou (E71). Heinzle and co-workers (E72) have described a n 1 modeled problems associated with error propagation in metabolic rate measurements using mass spectrometry. Cox (E73)and Willaert et al. (E74) described on-line monitoring of carbon dioxide and ethanol during yeast fermentation processes. Water was continuously analyzed in the Willaert study as an internal standard to correct for instrumental drift. Oxygen uptake and carbon dioxide evolution rates in an Escherichia coli fermentation process were measured on-line by mass s ec trometry as reported by Winter (E75). Oxygen, car\o, dioxide, and ethanol have been monitored in a study by Lloyd and James (E76) of the inhibition of glycolysis by oxygen in suspensionsof Saccharomyces uvamm and S. cerevisiae. With on-line mass spectrometric monitoring, they determined the ratio of anaerobic to aerobic rates of glycolysis and correlated them with the aerobic rates of carbon dioxide respiration and ethanol oxidation. Griot and co-workers(E77)have reported monitoring acetoin and butanediol as products of glucose fermentation by Bacillus subtilis. Headspace gases and dissolved gases have been monitored by Bohatka et al. (E78) during an erythromycin fermentation and a neomycin fermentation. Richards et al. (E79)reported a study of gaseous hydrocarbon oxidation by microbes where reactants and products in both the gas and aqueous support medium for the microbes were monitored. Analysiswith feedback control of processes was utilized by Lloyd et al. (E811and Whitmore et al. (E80, E82) to follow the effects of various parameters on thermophilic and mesophilic anaerobic digestion processes studied by monitoring methane and hydrogen. Chemical Reaction Monitoring. Mass spectrometry is not new as an on-line technique for monitoring gas-phase and liquid-phase chemical processes. The technique has been utilized extensively in the laboratory and at industrial production sites both as a primary investigative tool and as a complementary tool to other techniques to probe the


intricacies of chemical reactions in real time. Samplin devices are continually being developed to sample liqui! streams by mass spectrometry when current technology is found lacking in applicability. Tou and Reddy (E83)reported the mass spectrometric monitoring of the acid-induced hydrolysis of methyl acetate to methanol. Small volumes of the liquid sample from the process were repeatedly deposited into a vaporizing gas stream by an automated liquid injection valve, vaporized, and swept through a series of dilution chambers before bein analyzed by mass spectrometry. Didden and Duisings ( 84)also used a liquid injection valve in the analysis of the liquid reactor feed of a synthetic rubber production plant. Methane, ethylene, propylene, and a monomer were monitored in this process over a period of several months. A technique for the on-line monitoring of water in organic liquid streams has been reported by Bohatka and Degn (E85) to monitor the hydrolysis of acetyl chloride dissolved in octane by measuring the loss of water in the stream. Lee et al. (E86)reported the use of ion spray tandem mass spectrometry to monitor nonvolatile, liquid-phase process reactants, intermediates, and products. The solvolysis of methandrostenolone to epimethandostenolone, the enzymatic hydrolysis of 0-nitrophenyl j3-galactopyranoside by lactase to galactose, the enz atic hydrolysis of dynor hin 1-8 with a-chymotrypsin an with leucine aminopepti ase, and the reduction of the disulfide bridge in oxytocin by j3-mercaptoethanol were described. The rapid analysis of explosive nitrogen trichloride produced during the chlorinolysis of wastewater streams was reported by Savickas et al. (E87). Membrane sampling was utilized in this study to analyze the unstable nitrogen trichloride in a reactor headspace in order to gain information about safe operating practices for the process. Kotiaho and co-workers (E88,E89) have used a membrane extraction technique to follow the reaction process of chloramines with HC1 in the aqueous phase. This group (E90)also reported the use of a membrane extraction technique with negative chemical ionization mass spectrometry to detect low molecular weight (c1-c6) aldehydes in aqueous solutions. Multiple reaction monitoring along with aqueous-phase derivatization by 0-(2,3,4,5,6-pentafluorobenzy1)hydroxylaminewere utilized to achieve ppb-level sensitivity. ElectrochemicaL Gas- and liquid-phase reactions with surfaces have also been investigated by mass spectrometry. The catalytic conversion of methane to a synthesis gas over europium iridate, Eu21r20,has been monitored by Ashcroft and co-workers with mass spectrometry (E91).Chang et al. (E92),Volk et al. (E93),and Enyo (E94)have reviewed applications, limitations, and expectations for the on-line coupling of mass spectrometry to electrochemical processes. Thermospray ionization followed by mass spectrometric analysis was reported by Anastasijevic et al. (E95)to monitor the oxidation of NJV-ethylmethylaniline in ammonium acetate to N-ethyl-N-methylaminobenzyl-N-methylaniline and N-ethyl-N-methylaminobenzyl-N-ethylaniline.Thermospray mass spectrometry has also been a plied by Volk et al. (E%) to investigate the enzymatic an electrochemical oxidation of uric acid. In addition to carbon dioxide, avariety of nonvolatile intermediates were monitored, aiding in the elucidation of the oxidation mechanism. Carbon dioxide evolution was measured as a function of a plied potential for the electrooxidation of LiAsF6, LiBF4, an LiC104/propylene carbonate on platinum as reported by Catteneo and coworkers (E97). In a somewhat related study, the group examined the influence of water on the oxidation of propylene carbonate on platinum (E98).A PTFE membrane was coupled to a mass spectrometer by Hirata and co-workers (E99)to extract and analyze reaction products from an aqueous solution during the electrocatalytic reduction of carbon dioxide on nickel(I1)-cyclam. In addition to the on-line analysis of nonvolatile reaction products, mass spectrometric studies of the oxidation of toluene and formic acid to carbon dioxide on a platinum surface, as well as the reduction of benzene, toluene, and acetone to cyclohexane,methylcyclohexane,and propane were reported by Anastasi'evic et al. (E95).Solis et al. (E100) measured the carbon dioxide generated during the electrooxidation of formic acid on a palladium surface by mass spectrometry. Bolzan et al. (ElOl)used mass spectrometry

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to monitor the carbon dioxide generated during the electrooxidation of 13C-labeled glucose on platinum and gold surfaces to investigate reaction mechanisms. This group (E102)has shown the electrooxidation of urea on platinum to yield carbon dioxide, nitrogen, and nitro en oxides by membrane extraction mass spectrometr . imilarly, the electrocatalytic reduction of carbon dioxidYe to methane and ethylene on a variety of copper surfaces has been studied by Wasmus and co-workers (E103)using membrane extraction mass spectrometry. Wohlfahrt-Mehrens and Heitbaum (E104)studied the oxidation and reduction of ruthenium catalysts by monitoring oxygen and ruthenium tetraoxide by mass spectrometry. Semiconductor and Surface Modification. Semiconductor process monitoring by mass spectrometry, like the electrochemical applications discussed herein, is used to provide fundamental and mechanistic information about chemical processes as well as provide information necessary for manufacturing. Cai (E105)has reviewed a number of techniques for the analysis of semiconductors over the years from 1982 to 1987, showing the wealth of applications that mass spectrometry has in semiconductor process monitoring. Muller et al. (E106)applied mass spectrometry to the analysis of high-purity inert gas feed streams for the presence of trace level contaminants. Similarly, API-MS has been used to monitor the level of water vapor at the ppb level in highpurity nitrogen streams by Nishina and co-workers (E107, E108). High-purity argon and nitrogen feed monitoring has also been re orted for water va or, oxygen, methane, carbon dioxide, antcarbon monoxide gy Nishina (El09).Siefering and co-workers (El10)have demonstrated API-MS to be useful as a quantitative tool for the analysis of gas-phase impurities in ultrapure semiconductor processing gases at the ppt level. This analytical system was used for qualfication and certification tests on ultra-high-purity cylinder products, assemblies of gas handling components, large-scale inert gas purifiers, and state-of-the-art distribution systems. The gas-phase products formed during the laser treatment of silicon and copper surfaces in a silicon hexafluoride atmos here have been studied by Rossberg et al. (E111).This work Amonstrated the utility of the on-line analysis to study the kinetics of laser-induced processes. In addition to surface reactions, evaporation processesfor depositing thin films have been continuouslymonitored. The control of multicomponent layer growths by monitoring evaporation rates of the components from their source has been reported by Koprio and co-workers (E112, E113). Sputtering processes are also used in the semiconductor industry for growin films and altering surfaces. Mueller et al. (E114)describefan instrument for the on-line monitoring of ppb-level impurities in sputter processes at 10-2 mbar without pressure reduction. The possible interference of residual background and the influence of high-pressure side effects were discussed. Lee and co-workers (E115,E116)have developed special metalloorganic chemical vapor deposition reactor systems which utilize on-line mass spectrometry to monitor gas-phase products of reactions on gallium arsenide surfaces. The gasphase decomposition mechanisms of Ga(CH3)3,Ga(C2Hs)3, andAs(CH& in H2, Da, and He were discussed. Annapragada et al. (E117)have utilized on-line mass spectrometry to monitor the gas-phase products generated in the decomposition of tert-butylarsine on gallium arsenide in a chemical vapor deposition process. A novel technique for the analysis of elemental mercury in an atmospheric pressure metalloorganic vapor epitaxy reactor has been described by Lovergine et al. (E118).This system made use of a heated bypass line to probe gas samples from the reactor with fast response times and without mercury condensation. On-line mass spectrometry has been used by Wadayama et al. (E119)and by Groen et al. (E120)to study the reaction of tungsten hexafluoride with hydrogenated amorphous silicon. The pyrolysis of tricarbonyl(methylcyc1opentadieny1)manganese was investigated by Sang et al. (E121)by couplinga quadrupole mass spectrometer to an organometallic vapor-phase epitaxy reactor with a capillary inlet. The pyrolysis was determined to occur by successive loss of CO groups followed by breaking of the Mn ring bond. Thomas and co-workers(E1224125) have utilized mass spectrometry to study the composition of the plasma in plasma-assisted etching processes such as those encountered in the fabrication

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of integrated circuits. Saito and Kondo (E126) have used quadrupole mass spectrometry to measure gaseous products formed during gallium arsenide etching with HCl and HC1/ Hz mixtures in a molecular beam epitaxy chamber prior to epitaxial growth. Hase et al. (E127) have reported the use of mass s ectrometry to follow the selective etch of 111-V compouni semiconductor heterostructures which contain arsenic, allowing precise control of the etching on a monolayer scale. Miscellaneous. Mass spectrometry has been applied to a variety of diverse a plications that do not fall under the above categories. Ohtsugo et al. 03128) have described the use of an injection gas probe technique to measure the hydrogen content of liquid iron. The technique involves the injection of an inert gas into molten iron through a nozzle with the collection of the ascending bubbles and subsequent determination of the hydrogen concentration by mass spectrometry. The experimental result was shown to be in good agreement with theoretical calculations of the hydrogen content. Pressouyreet al. (E1291described a technique to measure hydrogen evolution in zones affected by heat during welding. The technique involves the use of square block specimens with holes drilled parallel to the heat-affected area and connected to the mass spectrometer for analysis. The fluid dynamics behavior of reactors, such as process residence times and mixing characteristics, have been studied by Luebbert et al. (E1301 using a tracer compound analyzed by mass spectrometry. Similarly, chemical process vessels have been mass spectrometrically leak tested with a tracer as on a point-by-point basis to locate ambient air leaks, which t a d to degradative byproducts. Applications in polymer production have been reported by Scureman and Powers (E131)and in semiconductor production by Blessing (E132) and by Madsen (E133). A field-portable mass spectrometer has been used to detect helium in eothermal fluids using a membrane sampling system as fescribed by Marty et al. (E134).

CHEMOMETRICS Introduction. Many chemometricsfeasibilitystudies have been performed on data from simulations or experimental data where an actual on-line implementation was not performed or reported. For example, many studies examined the ability of principal components analysis (PCA) or partial least squares (PLS) to perform process monitoring and/or control using samples prepared in the laboratory. In general, these papers are not discussed in this report as the emphasis is on real on-line applications or studies that increased the understanding of real processes. The reader should also note that no explicit literature search was done for the application of experimental design methodolo to process optimization and/or design. The reader shoulKot infer that the use of experimental designs is outside the scope of chemometrics or is less important than the work reported here. In fact, experimental designs should be an integral part of most, if not all, chemometrics analyses (Deming et al. (F1)). Reviews. The review article on process analytical chemistry by Callis et al. (F2)included a section on the "Role of Chemometrics". The authors discussed the power of using chemometrics to estimate sample "specifications that are not obviously chemical in nature", citing the prediction of octane number of gasoline samples as an example. Other areas of chemometrics discussed included use of multivariate models to derive chemical information, applications of chemometrics to process control, and raw material analysis. Brown's article (F3)discussed the goals of chemometrics in analytical measurements of bioprocesses. Included in the article was a tutorial on different multivariate analysis techniques (classical and inverse least squares, princi al components regression, PLS, and Kalman filters) a n t a discussion of their potential use in bioprocesses. Tranter (F4) discussed the challenges the analyst faces when attemptin to implement chemometrics in a process setting. The autaor pointed out the differences in culture that exist between manufacturing and research departments. He stressed that these differences must be considered in order to gain acceptance of the new methods. He also discussed data uality and validation concerns and cited examples of how clemometrics has been implemented. He concluded by 208R


Table I. Potential and Demonstrated Applications for On-Line Mass Spectrometry Cited in the Literature Environmental Monitoring monitoring and rapid screening of E17-El9, E23-E26, water for trace level contaminants E51-E55, E135 air monitoring for leaks, spills, stack E23-E26, E29, E36-E38, emissions, and general air quality E40-E42, E47-E50, E53, E136-E142 incineration and combustion process E4, E15, E16, E20, E21, monitoring E40, E43-E46 explosive vapor monitoring E23, E24, E41, E87-E89, E138, E139 monitoring of soil for contaminants E22-E28, E30-E32, E143 E56, E57 aerosol monitoring Biofermentation fermentation off-gas monitoring E64-E67, E78, E79, E138, E144, E145 fermentation broth monitoring E68-E71, E73, E74, E78-ES2, E145 Chemical Reaction liquid-phase reaction monitoring E83-E90 electrocatalytic process monitoring E95-El04 gashurface catalytic process E91 monitoring Semiconductor Production and Surface Modification surface off-gas monitoring Elll-E113, E115-El21, E126, E127 gas purity monitoring E106-El10, E114, E146, E147 E122-El25 plasma monitoring Manufacturing steel Droduction E128. E137. E146-E149 coke bven and blast furnace E137; E146 monitoring acrylonitrile production monitoring E137, E146, E150 E135 ethylene and ethylene oxide production monitoring fuel gas production monitoring E151 vessel/reactor leak testing E 131-E 133 and location monitoring

stating that "chemometrics must be seen, therefore, as a part of the overall measurement system", it is "one of the tools available for the effective monitoring of processes". Martens and Foulk (F5) discussed multivariate calibration as it is applied to near-infrared spectroscopy. They noted that nearIR spectroscopy has been well received by industry but has not gained acceptance by universities. The goal of the article was to demonstrate that near-IR coupled with the multivariate techniques has a "solid spectroscopic rationale". The article discussed the theory behind multivariate calibration regression methods and illustrated their use on a three-component system of organic solvents. In a similar vein, Donahue (F6) stressed the importance of not minimizing the "chemistry in chemometrics". The author pointed out that chemical knowledge is important when designing an analytical system, especially in the calibration design and algorithm selection phases. He illustrated these points using experimental and process examples. Process Optimization. The following articles discussed the use of chemometrics techniques to aid in the identification and/or understanding of important process parameters. The goal of this research was to use this information to select operating parameters to optimize some aspect of the process. Scott (F7)discussed the use of PCA to study the correlation between a color measurement made at the time a switch was activated to redirect column flow and the resulting purity and yield of a batch purification process. In a series of articles, Cruciani, Pitea, et al. (F8-Fl 1)examined the use of PLS and response surface modelin to optimize a munici al solid waste incinerator pilot plant. T%eauthors employed KLS modeling to search for operating conditions that minimized the emission of target compounds. Additionally, nonlinear PLS was used to define a response surface from which operating conditions that optimized the postcombustor efficiency were derived.


components were identified, a two-level fractional factorial design was used to determine the magnitude of the effect of each component on the silver removal. One section of the article by Chen (F13)discussed the use of pattern recognition tooptimize industrialchemicalprocessesinChina. The author very briefly cited examples including the improvement of the quality of butadiene rubber and applications in the production of solvent oils, dyestuffs, aluminum, and penicillin. The author concluded the section by stating "optimization by chemical pattern recognition methods is now widely used for the improvement of the technical/economic parameters (including energy consumption, raw material consumption and product quality) of industrial processes in China". Process Monitoring. Chemometric techniques have also been applied to process data in order to monitor the state of the process. Examples of different states include the concentration of a reaction product, in-control vs out-of-control, or any other characteristic of the process that aids in determining control actions. O'Rourke (F14)discussed the use of fiber optic spectrophotometry and chemometrics to monitor streams at the radiochemical separation plants at Savannah River Laboratory. The author discussed all phases of the measurement processes from interaction with plant personnel to data analysis and error detection. Smith and Gonzalez (F15) described a pattern recognition system developed to monitor measurements made during the operation of a nuclear reactor. The system went beyond flagging "normal" vs "abnormal" operation by providing summary plots and tables that gave the analyst insight into the status of the plant component being monitored. The authors included a detailed description of how the limits of normal operation were defined and discussed the use of the system during a 2.5-year series of experiments at the Sequoyah-1 Nuclear Power Plant. Konstantinov and Yoshida (F16) used fuzzy sets theory and pattern recognition to help control a continuous fermentation process for single cell protein production where the physiolo ical characteristic of the culture did not remain constant. TLe authors developed a technique to detect the physiologicalstate and used this information to calculate the appropriate control action. With a similar objective in mind, Locher et al. (F17)applied a pattern recognition algorithm to detect complex states durin a bioreaction. The authors examined the results of their affgorithm using different pretreatment schemes and also discussed the potential for using their technique for detecting sensor failures. Mejdell and Skogestad (F18)used PLS to estimate the product composition on a distillation column using tem erature readings from 11 column trays as the indepen ent variables. The authors evaluated the method using simulated data (assuming constant relative volatility and molal flows) and experimental data obtained on a pilot-plant distillation column separating a binary mixture of ethanol and butanol. They found the models derived from experimental data outperformed the simulations and proposed a method of improving the simulation models by augmentation with any available experimental data. Wallbaecks et al. (F19)analyzed l3C NMR spectra of samples from a kraft pulping process using PCA and PLS. They proposed usin PCA to study the compositionchangesthat occurred during t e ulping process. They also constructed a three-component PLg model capable of monitoring the lignin content of the pulp. Another area of process monitoring which has seen activity in recent years is that of multivariate statistical process control (MSPC). These methods are becoming more important because of the increased usage of process computers and the enormousamount of data that is collected during the operation of many processes. These data often contain a large amount of information that is lar ely ignored because much of it is not processed. If the t a t a are analyzed, conventional statistical process control techni ues are used which examine only a few of the variables. Thisloes not have to be the case. The MSPC methods are available and can be used to compress the data into a more manageable, lower dimensional space. These methods allow the plant personnel to monitor the lant performance using all of the information that is availabre. In many cases, this will result in better control and improved

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fault diagnostics. As stated in one article (F26),the goal of statistical process control is to help detect (1)unacceptable trends and systematic error in one or more process variables, (2) unacceptable random error in one or more variables, and/ or (3) unacce table changes in the correlation structure between variabes. This section cites some of the work that attempts to achieve these goals using all available measurements. Not all of the articles referenced describe applications to real processes; these were included, however, to round out the discussion on this topic. Kresta et al. (F20)discussed the use of PCA and PLS for monitoring processes. They applied the methods to two simulations, a fluidized bed reactor and an extractive distillation column. The article included a very clear introduction to this field. Skagerberg et al. (F21) applied the method sug ested by Kresta et al. (F20) to simulated data from a low-tensity polyethylene tubular reactor production plant. A 'three-dimensional" MSPC chart was used to monitor temperature along the reactor, the wall temperature, and solvent feed rate. The authors successfully detected simulated upsets in the reactor and used model residuals and raw signals to assign causes. Wise et al. (F22) also used PCA to monitor temperature, power, and current measurements made on the West Valley liquid fed ceramic melter during operation. The goal was to determine whether the method could be used to identify process upsets and sensor failures. The authors found that the first two principal components provided a good representation of the state of the process and made proposals as to how the method could be applied to real-time analyses. The article by Wise and Ricker (F23) included an overview of the use of PCA and PLS in MSPC. The emphasis of this article was to demonstrate how the techniques could be used to enhance feedback control. The authors used the data in another publication (F22)to demonstrate how PLS could be used to predict the molten glass level in the liquid-fed ceramic melter. In another paper, Wise et al. (F24) provided a theoretical discussion on the use of PCA to monitor dynamic (vs steady-state) process data. The authors discussed the situations where the application of PCA to dynamic processes was appropriate and included a discussion of how to interpret the results. Efthimiadu and Tham (F25) also applied the PCA methodologyto nonlinear data derived from a simulation of a continuous tank reaction. Smith et al. (F26) discussed the use of composite multivariate quality control (CMQC) to control processes. The authors discussed the advantages of CMQC over other approaches including PCA due to its ability to handle missing values and enhance interpretability. CMQC (a combination of univariate, multivariate, and pairwise correlation control statistics) was presented, and recommended action and warning rules were iven for each part of the CMQC method. The use of the toofs was demonstrated using a laboratory process with 40 process variables, 40 calibration runs, and 23 prediction runs. Calibration Transfer. Another area of chemometrics research that has potential impact on on-line analysis is the development and evaluation of instrument standardization technologies. When an instrument is calibrated for a particular system, a mathematical model is derived that relates the instrument response to the chemicalor physical properties of the samples of interest. This model must describe the characteristics of the instrument as well as the physical relationship between response and sample properties. On the other hand, when one performs standardization, only the instrumentalproperties are characterized. It is assumed that the physical relationship between response and sample properties does not change. Because of this, it is possible to standardize using a much smaller number of samples than would be required for calibrating an instrument. Some uses of standardization include (1)transferring calibration models developed on laboratory instruments to on-line instruments where the introduction of calibration standards is difficult or im ossibleand (2) correcting for instrumental drift. In recent puhications, Wang et al. have studied recalibrating an instrument usin a subset of the original calibration samples (F27),the transkr of a model from an instrument with good signal to noise (S/N) to another instrument with poorer S/N (F28), and the application of piecewise direct standardization to a set of gasoline samples (F29). The latter article also ANALYTICAL CHEMISTRY, VOL. 65, NO. 12, JUNE 15, 1993

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examined the feasibility of using generic standards to erform recalibration. Adhihetty et al. (F30)took a slightly Jfferent approach by building more robust calibration models using information about the instrument parameters that affected the model transferability. Artificial Neural Networks. Introduction. Another area of research that has seen increased activity in recent years is the use of artificial neural networks (ANN) to analyze spectroscopic data. For readers interested in the topic, the article by Jansson (F31)is a eneral overviewand introduction to ANN technolo AnotEer recent article by Gemperline (F32) discussed current efforts in analyzing nonlinear multivariate spectral data. The author discussed the use of more classical linear models along with the potential for using ANN to model different functional nonlinearities. Similarly, Long et al. (F33) and Gemperline et al. (F34) discussed the use of ANN to build calibration models on nonlinear data using ANN. In the area of pattern recognition, Wythoff et al. (F35)used ANN to detect peaks in vapor-phase IR spectra, and Robb and Munk (F36)and Munk et al. (F37)investigated the use of ANN to recognize functional groups in organic compounds using IR spectra. None of these articles targeted on-line analysis for applications of the networks. In the chemical engineering literature, however, a large number of articles have been published in recent years on the use of ANN for process monitoring and control. In addition to two dissertations (F38,F39), several articles have been published that discussed the use of ANN to monitor chemical processes. The main advantages that the authors cited for using neural networks were the following: (1) the ability to control processes where there is no first principle model for the process or where the knowledge is incomplete, (2) the ability to model complex (e.g., nonlinear) relationships, and (3) the ability to detect sensor and process faults. Some of the disadvantages mentioned included the following: (1) it is easy to use the methods as "black boxes" since no functional model is generated, (2) it may be necessary to use many training sam les to build the model, (3)the amount of computer time neefed to build the ANN model can be prohibitive, and (4) the neural network does not output error estimates for the estimated arameters. As this is still a fairly new area, most of the articyes described methods which were evaluated using simulated or pilot-plant data. Additionally, the variables being monitored or used for control were typically transducer measurements (e.g., temperature, pressure) rather than analytical measurements. They were included here because they discuss an area of research that may be of interest to chemists that are involved in process control. Reviews. Shaw's article (F40) discussed the use of neural networks for process monitoring and alarming. The paper discussed the role neural networks can take in MSPC, state determination, data preprocessing, and fault detection/ correction. The goal of the article was to simply introduce ANN as a tool for the process control engineer. No data were analyzed. Boger's article (F41)was a review of the application of ANN techni ues to wastewater treatment plants. The author discusse! the advantages and disadvantages of neural networks compared to expert systems and more classical approaches. The review article by Novotny et al. (F42) also discussed wastewater treatment plants, but mainly referenced applications of autoregressive-moving average time series models for plant monitoring and control. The authors included a section entitled "Neural Network Models-The Next Generation" and briefly discussed ANN for analyzing the levels of microorganisms in treatment plants. Hernandez and Arkun (F43) discussed the properties of ANN models and used this information to design model-based control algorithms. The bulk of the article discussed the structure and analytical properties of ANN models; exampleswere given of the application of neural networks to nonlinear dynamic systems. The article by Thibault (F44) included an introduction to the use of ANN al orithms for monitoring dynamic systems. Many model builfiin aspects were discussed, and applications to simulated a n t real process data were presented. The review article by Samad (F45) discussed the application of neural networks to various aspects of process control (e.g., modeling, reinforced learning, process identification). Monitoring and Control. Lee and Park (F46) presented a method for improving control in the presence of unknown

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disturbances using ANN. To improve the operating range of model predictive controllers (MPC) and to enable them to model non-linear systems, a neural network was connected in parallel with an MPC and trained on-line to handle unmodeled effects. The technique was evaluated on simulation results from two applications. Psichogios and Ungar (F47) described the use of ANN for both modeling and controlling processes. The authors discussed different approaches to model-based control (MBC) and incorporated neural networks in two MBC strategies. They then applied their techniques on simulated data from a continuously stirred tank reactor where the objective was to control the output concentration. In another article ( F a ) , the same authors described a modeling scheme that combines a partial first principles model with a neural network that was used to estimate important process parameters that were not measured. The resulting hybrid model required fewer training samples and resulted in more accurate predictions than one built without using prior knowledge about the process. Ungar et al. (F49)examined the use of ANN for modeling/ controlling processes as well as detecting process faults. The article demonstrated fault detection in a small model chemical plant and the control capabilities of ANN on a nonlinear bioreactor. Rudd (F50) discussed the use of neural network in the pulp and paper industry. The author discusse general neural network background information and, in two applications, described the use of ANN for the control of bleach and brownstock washers. Su and McAvoy (F51) discussed the use of a parallel training approach for neural networks for monitoring chemical processes. The article discussed the difference between this approach and the more conventional feed-forward series-parallel approach and compared the performance of the two methods using data from a pilot-scale wastewater treatment plant and a catalytic re-forming system in an oil refinery. Kooi and Khorasani (F52) compared the performance of a backpropagation ANN model to a self-tuning regulator (STR) for controlling the specific energy in an industrial wood chip refiner. They compared both a static neural network built off-line and a dynamic neural network that updated the weights on-line. Both networks performed well at emulating the STR controller results. Pollard et al. (F53) performed a series of tests to examine the ability of ANN to model different functional relationships between inputs and outputs of a process. The authors employed a robust objective function and cross validation in analyzing both simulated and real data from a distillation column in their studies. Their conclusion was that ANN worked well where prior knowledge about the process was limited and where adequate training sam les were available. Kramer (F54) introduced a novel methoffor screening data using an autoassociative network (AAN). This specially constructed network was trained to approximate the identity function (outputs = inputs). The author demonstrated how this network could be used for noise reduction, replacing missing data, and detecting and correcting gross errors. The performance of standard and robust versions of the AAN was evaluated using the temperature data from a simulated distillation column. Hoskins and Himmelblau (F55)discussed the use of a neural network based on reinforced learning. These networks could be used in control situations where the objective function could be defined only as the success or failure of a control action (vs a numerical value). They compared training this type of neural network to a human learning by trial and error. The authors described the architecture of the network and applied it to simulated data from a continuously stirred tank reactor. Cooper et al. (F56) compared the performance of a back-propagation network and a vector-quantized network as a pattern recognizer.They evaluated the ability of these two different schemes to tune a controller to optimally respond to set point changes. Using simulated and pilot-scale laboratory data, the authors demonstrated the ability of both ANNs to learn to control processes when step changes in set points were made. The performance of the ANNs was superior when compared to two more traditional control algorithms (generalized predictive control (GPC) algorithm and recursive least squares based GPC).

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Other applications of ANN technolo ies to process monitoring included the following: contro ling an electric arc furnace (Staib et al. (F57)), controlling the temperature in a reaction vessel during an exothermic reaction (Zaldivar et al. (F58)), on-line prediction of fermentation variables (Van Breusegem et al. (F59), Thibault et al. (F60), and Cleran et al. (HI)), measuring bubble size and interfacial area in bioreactors using li ht or ultrasound measurements (Bugmann et al. (F62)), modering in-vitro drug release parameters from formulation variables (Hussain et al. (8’6311, capturing the knowledge of process operators (Gingrich et al. (F64)), estimating parameters and states in bioprocesses (Linko and Zhu (F65)), using a neural network flame emulator to control combustion (Gutmark et al. (F66)), using a layered network for water-level control (Ishida (F67)), and work examini?g the use of neural networks to monitor various parameters in nuclear ower plants (Zwingelstein et al. (F68), Uhrig (F69), and Paryos et al. (F70)). Fault Detection. Several articles have also been written that used ANN schemes to perform multivariate statistical process control where the main oal was in detecting and/or correcting process faults (Iordacte et al. (F71), Hoskins et al. (F72), Shaw (F73), and Hsu and Yu (F74)). Venkatasubramanian et al. (F75)examined the use of the back-propagation algorithm to diagnose process failures in steady-state processes. Their article gave a detailed overview and analysis of the use of ANN techniques for fault detection in chemical processes. The authors examined the learning, recall, and eneralization characteristics of neural networks and appliec! the techniques to two case studies. Watanabe et al. (F76)also used the back-propagation algorithm to develop a two-stagenetwork for the detection of process faults. The first stage was trained to determine the cause of the fault while the second stage estimated the degree. Venkatasubramanian and Chan (F77)discussed the advantages of ANN applications over knowledge-based expert systems for fault detection and applied the ANN methodologies to data from an oil refinery case study. Bulsari et al. (F78)investigated the use of state vector estimator and feedforward neural networks to detect sensor faults in biochemical processes. Sensor fault detection was achieved by examination of the model residuals. Kavuri and Venkatasubramanian (F79)used a combination of an assumption-based approach and neural network based pattern recognition techniques to detect process faults. The authors gave examples usin simulated data from a continuously stirred tank reactor wkch illustrated the use of their technique for detecting parameter and sensor faults.

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FLOW INJECTION ANALYSIS The advantages of flow injection analysis (FIA) in process analytical chemistry have been realized since the late 1970s with the technique having been widely implemented in industrial process monitoring throughout the 1980s (GI). The popularity of flow injection analysis is mostly attributed to its simplicity, versatility, and the adaptability of its instrumentation to different environments (G2).These features also enable the technique to be used in combination with other analytical techniques: as a solution handling system, e.g., as sample introduction (E70), concentration (B43, B44), or dilution systems. This section of the review focuses on the use of flow injection technology when it is applied as a process analyzer. In process analytical applications process flow injection analysis (PFIA) was often confused with other automated wet chemical analysis techniques. A review by Gissin and Thommen (G3)compared flow injection analysis with other automated wet chemical analysis techniques and pointed out that the most significant characteristic of FIA is the concentration gradient caused by sample dispersion in the carrier stream. In other automated wet chemical analysis techniques, e.g., continuous flow analysis (CFA), sample integrit is conserved by segmenting the flow stream with air bubiles (G4). The concentration gradient caused b dispersion produces chromatography-like peaks in FIA. 6uantization of the analyte concentration based on a eak profile was compared to quantization based on a &viation from a continuous signal; this led to more accurate results due to the ability to correct for baseline drift. In addition to high

accuracy, improved precision is another advantage of FIA over CFA when dealin with mixed phases, e.g., complex gas and liquid streams. FfKs simplicity in handling of solutions makes the technique practical in process applications. A variety of flow injection analysis techniques have been implemented in PFIA. Flow injection-gradient dilution (Garn et al. (G5,G6)) and flow injection-titration (Yalvac (G7) and Swaim (G8)) techniques have found several ap lications in industrial process monitoring. Reversed ow injection analysis (RFIA), where the sam le is used as the carrier, has been applied by Baughman et (C9).The RFIA has potential advantages in process flow injection analysis when the amount of sample is not limited, e.g., wastewater, seawater, etc. Silicon membrane separators have been incorporated in process flow in’ection analysis in order to increase selectivity, such as in the determination of phenol in salic lic acid as described by Melcher et al. (G10).Ogbomo et al. (811)and Ludi et al. (G12)used membrane separators in fermentation monitoring where the culture medium was brought in contact with buffer solutions via membranes. Gas diffusion FIA systems enabled the analysis of many volatile compounds (G13415).Sequential injection analysis, born from flow injection analysis and based on the same princi les, differs in operational aspects (G16419).Marshall an8,an Staden (G20)highlighted the important parameters of sequential injection analysis which has already found several a plications in process analytical chemistry. Chung et al. (821)and Taylor et al. (G22)have applied the technique to fermentation monitoring and to a cyanide determination in hydrometallurgical recovery of gold. A variety of detection techniques have been used in the laboratory for flow injection analysis. However, many of these techniques are too complex and expensive to make ractical detectors for process flow injection. The popular gtection techniques in process flow injection are spectrophotometric and electrochemical detection. The rimary spectrophotometric techniques used are UV-, visibe-, and fluorescencebased detectors (G23425).An overview of the advantages of spectrophotometric detection techniques for process monitoring is given by Benson et al. (G26), and an example of double-beam photometry for determination of nitrate, ammonia, and aluminum for water quality monitoring is described. Recently, diode array detectors have been used successfully in flow injection analysis for multicomponent monitoring coupled with quantitative chemometrics (1327C31).Papers discussing the advantages of photodiode array detection and the potential of FIA-photodiode arraymultivariate calibration systems for on-line determination such as by MacLaurin et al. (G32)are valuable reviews. However, the number of papers describing practical on-line applications is small. A good example of such an app!ication which describes the determination of glucose, ammonium ion, and protein in fed-batch fermentation processes by usin single-lineFIA coupled with diode array detection is authore! by Chung et al. (G33).Fluorescence detection is used widely in biotechnology to follow enzymatic reactions for determination of fermentation roducts (G34,G35). Englbrecht et al. (G36)described in letail the determination of glucose, lactate, isoleucin, ethanol, acetaldehyde, and glycerol via enzymatic conversion of NAD+ to NADH for on-line fermentation monitoring and control. NADH formed proportional to the analyte concentration in these enzymatic reactions was detected fluorometrically. The most common electrochemical detection techniques used in process flow injection analysis are conductometric, potentiometric, coulometric, and amperometric detection techniques. A wide variety of potentiometric detectors are employed such as pH probes and ion-selective and metal electrodes. Wolcott et al. (C37)first reported the flow injection-dual end oint titration technique for determination of sodium car\onA and caustic in alkaline process streams. The determination of sodium thiosulfate by the flow injection-oxidationfreduction-titration technique is an example of the use of metal electrodes in process flow injection analysis (G38).Ion-selective electrodes have been used as a detector for cyanide determination in monitoring of process streams for the cyanide-leachin plant in mining industry (G39,G40). Dullau et al. (G41)cfetermined glucose by using an “enzyme” electrode which is based on an amperometric oxygen electrode. The oxygen electrode measures the oxygen

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consumption rate during the reaction between glucose and oxygen in the resence of glucose oxidase. Amperometric oxygen electrofes are used similarly in the determination of lactate, amino acids, saccharides, maltose, lactose, and sucrose in fermentation media, as is described by Schugerl et al. (G42). Reagent simplicity, stability, and cost are important factors which are carefully considered in selectin the detection technique in rocess flow injection analysis. blectrochemical detection tec\niques seem to have an advantage in this area over colorimetric detection techni ues (G43). High reagent consumption rates in PFIA contr%ute to the maintenance requirements of the analyzers. Miniaturization of the instrumentation is expected to minimize this problem in future applications, as described by Luedi et al. (G44). Although there are innovative ways for increasing selectivity, insufficient selectivity remains one of the limiting reasons in implementation of PFIA for on-line determination of complex matrices in the chemical industr . The sampling and maintenance of sample lines present aditional problems for PFIA. Each application has its own specific problems in this area. For instance, the sterilization of sample lines is a difficult task in biotechnology (G41). The filtration of particulates in sampling of mixed phases further complicates the process flow injection applications (G24). The instrumentation of process flow injection analysis is an important issue in order to provide reliable, low-maintenance analyzers in process environments. Different types of pumps, valves, and detectors are being used in construction of the analyzers based on the experience available in-house. The separation of wet components and electronics was described by Yalvac (G2)as an advantage since it enables the installation of wet components closer to the sampling points, which in turn shortens the troublesome sample lines. Overall, the lack of commercially available rugged process flow injection analyzers seems to be the most important limiting factor in the implementation of process flow injection analysis in process monitoring and control.

PROCESS ANALYTICAL NEEDS Many reasons exist for the growing interest in process analytical measurements. Increased emphasis on environmental, safety, quality, and productivity issues has opened a window of opportunity for the application of on-line analytical instruments. Programs involvin academia, industry, and instrument companies are needet! to develop and provide the technology necessary to achieve the benefits of process analytical tools. Currently only a few engineering schools and chemistry programs have courses in process anal ical chemistry. Increased emphasis in this area is nee ed. In particular, it would be very advantageous if engineering programs exposed their students to the concepts and benefits of process analytical chemistry and developed a greater appreciation for this technology. This would serve the students well when they subsequently are involved with industrial manufacturing processes. Instrument companies need to provide commercially available process analytical systems (analytical and sampling equipment, software) on a more timely basis after proof of concept has been demonstrated within the academiclindustrial community. A number of cooperative efforts between industry and academia have resulted in the development of new generations of on-line analytical instruments. In most cases, however, industrial companies have relied on in-house custom-fabricated instruments to utilize the technology on a timely basis. Although this approach has served these companies well, there are shortcomings to the a proach. A significant drawback is the lack of global distrigution and support necessary in the deployment of this instrumentation across most companies. More importantly, however, the application of the new technology, which could be applied productively across the industry, is essentially limited to the originating company. To maximize the benefits of the online analytical tools, it is essential that this technology get into the market place as soon as possible.

8

ACKNOWLEDGMENT We thank Fran Voci for her help and guidance in the searches,and H. D. Ruhl for his insight and fruitful discussions in the area of process analytical chemistry. 212R


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