Process Analytical Chemistry

Double-UV Photoionizaion Detector with Graphene Oxide-Coated Electrodes

The structure of a photoionization detector was optioned and researched. In order to solve the problem of the photoionization detector' lamp surface residue interference, a new structure of the self-cleaning double-UV detector was adopted. At the same time, the air flow field of the detector was simulated by the finite element method. Through analyzing the results of the simulation experiment, further optimization of the gas channel for the microdetector was carried out, and the ionization chamber with axial flow structure was finally chosen. The new nanomaterial, graphene oxide was used to modify the surface of the collector plate of detector to improve the gas sensitivity and sensitivity of the photoionization detector. Through the experimental analysis, the performance indexes of detector were described in detail. The minimum detection limit of the detector is 2.5 × 10⁻⁷. The linearity response of the detector was analyzed, and the linear correlation coefficient reaches 0.993. The experimental results show that the double-UV detector can improve the overall gas sensing characteristics and provide an ideal detection unit for volatile organic compound (VOC) gas detection.

Cost-benefit analysis of calibration model maintenance strategies for process monitoring

The long-term prediction performance of spectroscopic calibration models is a critical factor to monitor or control many production processes. Over time, new variations may emerge that deteriorate prediction performance. Therefore, models have to be maintained to retain or improve their prediction performance through time, requiring considerable resources and data. Maintenance should improve relevant predictions but also needs to be resource and cost efficient. Current approaches do not consider these trade-offs. We propose a new method to quantify the effectiveness and cost of model maintenance strategies based on historical data. Model performance over time for past, imminent and future samples is evaluated as these may react differently to maintenance. The model performance and required updating resources are translated into relative cost and benefit to compare strategies and determine optimal maintenance parameters. We used this method to evaluate a maintenance strategy that combines adding incoming samples to the calibration data with re-optimization of spectral preprocessing and modelling parameters. Continuously adding samples to the calibration data is shown to improve prediction performance and leads to more robust and generic models for emerging variations in all investigated data streams. Selectively adding incoming sample variations showed a reduced prediction performance but saves considerably in resources. Comparing model performance on the different sampling windows can also be used to determine an optimal updating frequency. This novel strategy to evaluate the expected performance and determine an optimal maintenance strategy is generally applicable and should lead to robust and consistently high prospective and/or retrospective model performance through time, which can be crucial for optimal operation and fault detection in industrial processes.

Fiberoptic-Coupled Spectrofluorometer with Array Detection as a Process Analytical Chemistry Tool for Continuous Flow Monitoring of Fluoroquinolone Antibiotics

Nowadays, there is an increasing need for sensitive real-time measurements of various analytes and monitoring of industrial products and environmental processes. Herein, we describe a fluorescence spectrometer in continuous flow mode in which the sample is fed to the flow cell using a peristaltic pump. The excitation beam is introduced to the sample chamber by an optical fiber. The fluorescence emitted upon excitation is collected at the right angle using another optical fiber and then transmitted to the fluorescence spectrometer which utilizes an array detector. The array detection, as a key factor in process analytical chemistry, made the fluorescence spectrometer suited for multiwavelength detection of the fluorescence spectrum of the analytes. After optimization of the experimental parameters, the system has been successfully employed for sensitive determination of four fluoroquinolone antibiotics such as ciprofloxacin, ofloxacin, levofloxacin, and moxifloxacin. The linear dynamic ranges of four fluoroquinolones were between 0.25 and 20 μg·mL-1, and the detection limit of the method for ciprofloxacin, ofloxacin, levofloxacin, and moxifloxacin were 81, 36, 35, and 93 ng·mL-1, respectively. Finally, the proposed system is carried out for determination of fluoroquinolones in some pharmaceutical formulations.

A small-volume PVTX system for broadband spectroscopic calibration of downhole optical sensors

An instrument is presented that is capable of measuring the optical spectrum (long-wave ultraviolet through short-wave mid-infrared) of fluids under a range of temperature and pressure conditions from ambient pressure up to 138 MPa (20 000 psi) and 422 K (300 °F) using ∼5 ml of fluid. Temperature, pressure, and density are measured in situ in real-time, and composition is varied by adding volatile and nonvolatile components. The stability and accuracy of the conditions are reported for pure ethane, and the effects of temperature and pressure on characteristic regions of the optical spectrum of ethane are illustrated after correction for temperature and pressure effects on the optical cell path length, as well as normalization to the measured density. Molar absorption coefficients and integrated molar absorption coefficients for several vibrational combination bands are presented.

A compact Raman converter for UV-VIS spectrometers

A small form factor, easily constructed converter that adapts fiber coupled UV/VIS CCD detector-based spectrometers into a right angle scattering Raman spectrometer is described. Its design philosophy and design are discussed. An example measurement, the depolarization ratio of carbon tetrachloride, a classic Raman test compound, is presented. The unique instrument features a blue-violet (405 nm wavelength) diode laser that takes advantage of the inverse fourth power wavelength dependence of Raman scattering. The converter also features Glan-Thompson polarizing prisms that enable measurement of depolarization ratios. The spectrometer is also capable of measuring a standard Raman spectrum. A fiber optic link offers flexibility when adapting the converter to any spectrometer system that accepts a fiber optic input. The performance of the instrument is critically discussed in the context of an example measurement.

Development of FT-NIR models for the simultaneous estimation of chlorophyll and nitrogen content in fresh apple (Malus domestica) leaves

Agricultural practices determine the level of food production and, to great extent, the state of the global environment. During the last decades, the indiscriminate recourse to fertilizers as well as the nitrogen losses from land application have been recognized as serious issues of modern agriculture, globally contributing to nitrate pollution. The development of a reliable Near-Infra-Red Spectroscopy (NIRS)-based method, for the simultaneous monitoring of nitrogen and chlorophyll in fresh apple (Malus domestica) leaves, was investigated on a set of 133 samples, with the aim of estimating the nutritional and physiological status of trees, in real time, cheaply and non-destructively. By means of a FT (Fourier Transform)-NIR instrument, Partial Least Squares (PLS) regression models were developed, spanning a concentration range of 0.577%–0.817% for the total Kjeldahl nitrogen (TKN) content (R² = 0.983; SEC = 0.012; SEP = 0.028), and of 1.534–2.372 mg/g for the total chlorophyll content (R² = 0.941; SEC = 0.132; SEP = 0.162). Chlorophyll-a and chlorophyll-b contents were also evaluated (R² = 0.913; SEC = 0.076; SEP = 0.101 and R² = 0.899; SEC = 0.059; SEP = 0.101, respectively). All calibration models were validated by means of 47 independent samples. The NIR approach allows a rapid evaluation of the nitrogen and chlorophyll contents, and may represent a useful tool for determining nutritional and physiological status of plants, in order to allow a correction of nutrition programs during the season.

Near infrared spectroscopy in the development of solid dosage forms

The use of near infrared (NIR) spectroscopy has rapidly grown partly due to demands of process analytical applications in the pharmaceutical industry. Furthermore, newest regulatory guidelines have advanced the increase of the use of NIR technologies. The non-destructive and non-invasive nature of measurements makes NIR a powerful tool in characterization of pharmaceutical solids. These benefits among others often make NIR advantageous over traditional analytical methods. However, in addition to NIR, a wide variety of other tools are naturally also available for analysis in pharmaceutical development and manufacturing, and those can often be more suitable for a given application. The versatility and rapidness of NIR will ensure its contribution to increased process understanding, better process control and improved quality of drug products. This review concentrates on the use of NIR spectroscopy from a process research perspective and highlights recent applications in the field.

Fast quantitative determination of microbial rhamnolipids from cultivation broths by ATR-FTIR Spectroscopy

BACKGROUND

Vibrational spectroscopic techniques are becoming increasingly important and popular because they have the potential to provide rapid and convenient solutions to routine analytical problems. Using these techniques, a variety of substances can be characterized, identified and also quantified rapidly.

RESULTS

The rapid ATR-FTIR (Attenuated Total Reflectance Fourier Transform Infrared Spectroscopy) in time technique has been applied, which is suitable to quantify the concentrations of microbial rhamnolipids in a typical cultivation process. While the usually applied HPLC analysis requires an extensive and time consuming multi step extraction protocol for sample preparation, the ATR-FTIR-method allows the quantification of the rhamnolipids within 20 minutes. Accuracies between 0.5 g/l - 2.1 g/l for the different analytes were determined by cross validation of the calibration set. Even better accuracies between 0.28 g/l - 0.59 g/l were found for independent test samples of an arbitrarily selected cultivation.

CONCLUSION

ATR-FTIR was found to be suitable for the rapid analysis of rhamnolipids in a biotechnological process with good reproducibility in sample determination and sufficient accuracy. An improvement in accuracy through continuous expansion and validation of the reference spectra set seems very likely.

Development of PLS calibration models from UV-Vis spectra for TOC estimation at the outlet of a fuel park wastewater treatment plant

In the present work ultraviolet (UV)-visible spectra of water samples collected at the outlet of a fuel park wastewater treatment plant, including biological treatment, were acquired and used for the development of partial least squares (PLS) calibration models for the fast and simple estimation of total organic carbon (TOC). Three different PLS models were developed and compared on the basis of a common spectral range. The first model was obtained using spectra of raw samples, the second using spectra of diluted samples, to assess signal saturation in the UV region, and the third using spectra of both diluted and raw samples, in order to expand the narrow interval of TOC concentration values present in the original dataset. The root mean squared error of cross-validation values for the developed PLS models were 2.3, 1.0 and 4.4 mg Cl(-1), respectively, and the validation results where highly satisfactory (root mean squared error of prediction values of 1.8, 0.8 and 4.5 mg Cl(-1), respectively).

Multivariate curve resolution-alternating least squares (MCR-ALS) applied to spectroscopic data from monitoring chemical reactions processes

This paper overviews the application of multivariate curve resolution (optimized by alternating least squares) to spectroscopic data acquired by monitoring chemical reactions and other processes. The goals of the resolution methods and the principles for understanding their applications are described. Some of the problems arising from these evolving systems and the limitations of the multivariate curve resolution methods are also discussed. This article reviews most of the applications of multivariate curve resolution applied to reacting systems published between January 2000 and June 2007. Some basic papers dated before 2000 have also been included.

An unaddressed issue of agricultural terrorism: a case study on feed security

In the late winter of 2003, a number of livestock animals in the Midwest were poisoned due the accidental contamination of a popular commercial feed with a lethal additive. Although all the evidence indicates this incident had no malicious or terrorist intent, it is informative as a case study highlighting potential security implications with respect to a terrorist event directed at U.S. agriculture.

Using ultrasonic attenuation to monitor slurry mixing in real time

Staff at Pacific Northwest National Laboratory have developed and applied a simple ultrasonic attenuation measurement to measure slurry concentration in real time during suspension of solids settled in a large tank. This paper presents a simple single frequency ultrasonic measurement technique that demonstrates the ability of ultrasonic sensors to measure slurry concentration. Sensor calibration data show that in this attenuation regime ultrasonic signal attenuation is proportional to the applied frequency and to the slurry volume fraction. Real-time measurements of ultrasonic signal attenuation were used to track the process of slurry mixing using single sensors and sensor arrays. Results from two experiments show the use of real-time measurements of ultrasonic signal attenuation to track the process of slurry mixing in situ and to track the ability to maintain a well-mixed steady state condition. Comparison of concentration means of the ultrasonic measurements with concentration means obtained from discrete extractive measurements show that the distributions overlap and cannot be statistically distinguished. The real-time ultrasonic sensor can be used as a primary measurement method or to reduce reliance upon extractive methods to measure slurry density and solids concentration.

Verification of the chemical composition and specifications of haemodialysis membranes by NMR and GPC-FTIR-coupled spectroscopy

The chemical composition of a dialysis membrane is decisive towards determining its physical and biochemical properties--two fundamental determinants of the success of therapy offered to patients suffering from chronic renal failure. From the vast variety of synthetic polymers available, only a few are suitable for the manufacture of dialysis membranes that have to conform to the diverse demands of modern haemodialysis and related therapies. Recently, a membrane labelled as polyamide (Polyamide S) has caused some confusion to end-users in that the product specification for the membrane is given as 'polyarylethersulfone' or simply as Polyamide S membrane. As the chemical and physical properties of these two polymer types are distinctly different, it is unclear whether the functional characteristics of Polyamide S are to be attributed to polyamide, polyarylethersulfone, or, to both polymers. We therefore undertook investigations to ascertain the exact chemical nature of the Polyamide S membrane using a series of chemical analytical tools and an appropriate polyamide reference. The analytical techniques were conventional gel permeation chromatography (GPC), GPC-FTIR coupled spectroscopy using dimethyl acetamide and hexafluoroisopropanol as solvents and nuclear magnetic resonance spectroscopy. Glass transition temperature measurements and quantitative elemental analysis were also carried out. None of the analytical techniques used showed any traces of polyamide in Polyamide S; no aliphatic or aromatic polyamide chemical entities were detected in any of the samples tested. The Polyamide S dialysis membrane thus comprises, solely, of polyarylethersulfone, which is also known as polyethersulfone.

An automated workstation for forced degradation of active pharmaceutical ingredients

This article describes a system capable of performing and analysing multiple degradation experiments on drug substances as part of the process of developing stability indicating separations methods. Qualitative data are generated on the significant primary degradation processes of the drug of interest. Ten samples are refluxed with stirring in a single heating block. The robot arm is equipped with a sampling device capable of removing aliquots, during the reflux experiment, and transferring them to an HPLC injector. On-line analysis using fast HPLC with diode array and electrospray mass spectrometric detection allows identification of degradants. The methods described offer a significant time savings compared to the previously applied manual approach, and also provide data from multiple time points for each reaction. This increased knowledge about the progress of the reaction aids us in focussing efficiently on the primary degradation processes.

Automation of a procedure to find the polynomial which best fits (kappa, c1, c2, T) data of electrolyte solutions by non-linear regression analysis using MATHEMATICA software

A MATHEMATICA package, 'CONDU.M', has been developed to find the polynomial in concentration and temperature which best fits conductimetric data of the type (kappa, c, T) or (kappa, c1, c2, T) of electrolyte solutions (kappa: specific conductivity; ci: concentration of component i; T: temperature). In addition, an interface, 'TKONDU', has been written in the TCL/Tk language to facilitate the use of CONDU.M by an operator not familiarised with MATHEMATICA. All this software is available on line (UPV/EHU, 2001). 'CONDU.M' has been programmed to: (i) select the optimum grade in c1 and/or c2; (ii) compare models with linear or quadratic terms in temperature; (iii) calculate the set of adjustable parameters which best fits data; (iv) simplify the model by elimination of 'a priori' included adjustable parameters which after the regression analysis result in low statistical significance; (v) facilitate the location of outlier data by graphical analysis of the residuals; and (vi) provide quantitative statistical information on the quality of the fit, allowing a critical comparison among different models. Due to the multiple options offered the software allows testing different conductivity models in a short time, even if a large set of conductivity data is being considered simultaneously. Then, the user can choose the best model making use of the graphical and statistical information provided in the output file. Although the program has been initially designed to treat conductimetric data, it can be also applied for processing data with similar structure, e.g. (P, c, T) or (P, c1, c2, T), being P any appropriate transport, physical or thermodynamic property.

Chemical analysis of wood chips in motion using thermal-emission mid-infrared spectroscopy with projection to latent structures regression

The opacity and random surface orientation of process streams of solids complicates the application of spectroscopy to on-line analysis of solid streams. We have used a specialized form of thermal-emission mid-infrared spectroscopy, called transient infrared spectroscopy, combined with PLS regression to analyze a moving stream of wood chips for lignin, hemicellulose, glucan, and extractives content. Sixty-eight softwood samples from 6 species were analyzed using one regression, and 28 hardwood samples from 14 species were analyzed with another. Root-mean-square errors of prediction for the properties varied from 0.8 to 1.9 wt %, depending on property and wood type, with lignin and hemicellulose being the most accurately determined and glucan being the least.

Mass spectrometry in the U.S. space program: past, present, and future

Recent years have witnessed significant progress on the miniaturization of mass spectrometers for a variety of field applications. This article describes the development and application of mass spectrometry (MS) instrumentation to support of goals of the U.S. space program. Its main focus is on the two most common space-related applications of MS: studying the composition of planetary atmospheres and monitoring air quality on manned space missions. Both sets of applications present special requirements in terms of analytical performance (sensitivity, selectivity, speed, etc.), logistical considerations (space, weight, and power requirements), and deployment in perhaps the harshest of all possible environments (space). The MS instruments deployed on the Pioneer Venus and Mars Viking Lander missions are reviewed for the purposes of illustrating the unique features of the sample introduction systems, mass analyzers, and vacuum systems, and for presenting their specifications which are impressive even by today's standards. The various approaches for monitoring volatile organic compounds (VOCs) in cabin atmospheres are also reviewed. In the past, ground-based GC/MS instruments have been used to identify and quantify VOCs in archival samples collected during the Mercury, Apollo, Skylab, Space Shuttle, and Mir missions. Some of the data from the more recent missions are provided to illustrate the composition data obtained and to underscore the need for instrumentation to perform such monitoring in situ. Lastly, the development of two emerging technologies, Direct Sampling Ion Trap Mass Spectrometry (DSITMS) and GC/Ion Mobility Spectrometry (GC/IMS), will be discussed to illustrate their potential utility for future missions.

Application of quantitative chemometric analysis techniques to direct sampling mass spectrometry

This paper explores the use of direct sampling mass spectrometry coupled with multivariate chemometric analysis techniques for the analysis of sample mixtures containing analytes with similar mass spectra. Water samples containing varying mixtures of toluene, ethyl benzene, and cumene were analyzed by purge-and-trap/direct sampling mass spectrometry. Multivariate calibration models were built using partial least-squares regression (PLS), trilinear partial least-squares regression (tri-PLS), and parallel factor analysis (PARAFAC), with the latter two methods taking advantage of the differences in the temporal profiles of the analytes. The prediction errors for each model were compared to those obtained with simple univariate regression. Multivariate quantitative methods were found to be superior to univariate regression when a unique ion for quantitation could not be found. For prediction samples that contained unmodeled, interfering compounds, PARAFAC outperformed the other analysis methods. The uniqueness of the PARAFAC model allows for estimation of the mass spectra of the interfering compounds, which can be subsequently identified via visual inspection or a library search.

Simultaneous analysis of butene isomer mixtures using process mass spectrometry

The feasibility of simultaneous analysis of mixtures containing two to four butene isomers and up to six total components using process mass spectrometry is assessed. As for typical (nonisomeric) applications of process mass spectrometry, simultaneous analysis is based on the assumption that the electron ionization mass spectra of mixtures are linear combinations of the spectra of the individual constituents. Limits of detection for binary isomer mixtures are on the order of 0.1% to 10%, limited by the ability to distinguish small differences between similar spectra. As spectral and mixture complexity increase, both accuracy and precision decrease. Not surprisingly the similarity of the spectra of stereoisomers cis- and trans-2-butene is greater than that of the other (nonstereoisomeric) isomer pairs, and mixtures containing both cis- and trans-2-butene are the most difficult to quantitate. However, even for mixtures of all four butenes, accuracy (root-mean-square error = 2.43%), precision (average coefficient of variation = 6.72%), and linearity (correlation coefficient of a plot of measured versus actual concentration r2 = 0.985 +/- 0.002) are reasonably good.

Spectroscopic monitoring of batch reactions for on-line fault detection and diagnosis

This paper presents the general methodology to use spectroscopic measurements directly for on-line process monitoring and detection and diagnosis of disturbances. An application of the on-line monitoring of a chemical batch reaction using UV-visible spectroscopy is discussed in detail. Successful historical batches are used to build a statistical model of the batch reaction. The model uses external information such as the pure spectra of the compounds and their concentration profiles to improve the interpretability. Control charts are developed for on-line monitoring of new batches. It is shown that this model is capable of detecting erroneous batches. In combination with contribution plots, the actual cause of the disturbances can be diagnosed.

Miniature mass analyzers

Increased efforts are being made to develop miniature mass spectrometers, including those which are hand-portable, and to retain the performance characteristics of traditional laboratory instruments as much as possible in the miniature instruments. This review of miniature mass analyzers emphasizes analytical performance and compares the relative merits of each type of miniature mass analyzer. Miniature instruments discussed include sector, Wien filter, time-of-flight, linear quadrupole, quadrupole ion trap and Fourier transform ion cyclotron resonance mass spectrometers, as well as combinations of and variations on these major types. Special considerations that apply to small mass analyzers are noted and suggestions are made regarding the possible future development of this field. Copyright 2000 John Wiley & Sons, Ltd.

Next generation fluidized bed granulator automation

A system for fluidized bed granulator automation with in-line multichannel near infrared (NIR) moisture measurement and a unique air flow rate measurement design was assembled, and the information gained was investigated. The multivariate process data collected was analyzed using principal component analysis (PCA). The test materials (theophylline and microcrystalline cellulose) were granulated and the calibration behavior of the multichannel NIR set-up was evaluated against full Fourier Transform (FT) NIR spectra. Accurate and reliable process air flow rate measurement proved critical in controlling the granulation process. The process data describing the state of the process was projected in two dimensions, and the information from various trend charts was outlined simultaneously. The absorbence of test material at correction wavelengths (NIR region) and the nature of material-water interactions affected the detected in-line NIR water signal. This resulted in different calibration models for the test materials. Development of process analytical methods together with new data visualization algorithms creates new tools for in-process control of the fluidized bed granulation.

Membrane introduction mass spectrometry: trends and applications

Recent advances in membrane introduction mass spectrometry (MIMS) are reviewed. On-line monitoring is treated by focusing on critical variables, including the nature and dimensions of the membrane, and the analyte vapor pressure, diffusivity, and solubility in the membrane barrier. Sample introduction by MIMS is applied in (i) on-line monitoring of chemical and biological reactors, (ii) analysis of volatile organic compounds in environmental matrices, including air, water and soil, and (iii) in more fundamental studies, such as measurements of thermochemical properties, reaction mechanisms, and kinetics. New semipermeable membranes are discussed, including those consisting of thin polymers, low vapor pressure liquids, and zeolites. These membranes have been used to monitor polar compounds, selectively differentiate compounds through affinity-binding, and provide isomer differentiation based on molecular size. Measurements at high spatial resolution, for example, using silicone-capped hypodermic needle inlets, are also covered, as is electrically driven sampling through microporous membranes. Other variations on the basic MIMS experiment include analyte preconcentration through cryotrapping (CT-MIMS) or trapping in the membrane (trap-and-release), as well as differential thermal release methods and reverse phase (i.e., organic solvent) MIMS. Method limitations center on semivolatile compounds and complex mixture analysis, and novel solutions are discussed. Semivolatile compounds have been monitored with thermally assisted desorption, ultrathin membranes and derivatization techniques. Taking advantage of the differences in time of membrane permeation, mixtures of structurally similar compounds have been differentiated by using sample modulation techniques and by temperature-programmed desorption from a membrane interface. Selective ionization techniques that increase instrument sensitivity towards polar compounds are also described, and comparisons are made with other direct sampling (nonchromatographic) methods that are useful in mixture analysis.