Flow Injection Analysis in the Undergraduate Laboratory

Flow Injection Analysis (FIA) is one of the most popular continuous-flow techniques and its versatility and simplicity can help to bring automation to teaching laboratories; however, the small number of educational papers about this technique indicates that the adoption of FIA procedures in the undergraduate curriculum has been scarce. In this work the fundamentals of FIA are presented using simple laboratory experiments. Some drawbacks that can hinder the employment of FIA by first-time users are discussed. Practical strategies to overcome these hindrances are suggested in order to facilitate the use of FIA for undergraduate laboratories.     

流动注射分析系统中的化学动力学研究

运用对流－扩散模型研究了流动注射分析系统中的化学动力学，基于无化学反应时试样分散的浓度分布公式，运用数学归纳法导出了在一定条件下一级和二级反应的产物浓度分布公式，所得解析解便于计算机模拟产物生成曲线。解释了双峰的产生，并讨论了相关的动力学信息。     

On the mathematical model of flow injection analysis-II. The second order chemical reaction in a straight tube

The mathematical model of flow injection analysis (FIA) for fast second-order chemical reaction in a straight tube is presented. The sample and reagent are initially premixed and the analytical solution for the detection output, i.e. the integral of the product of reaction concentration over the tube cross-section is given. The optimization of FIA is discussed. It is proposed to put the detector in the real FIA systems immediately after the point where the sample and reagent are satisfactorily mixed.     

Comparison of PLS and kinetic models for a second-order reaction as monitored using ultraviolet visible and mid-infrared spectroscopy

A second-order reaction between benzophenone and phenylhydrazine to give benzophenone phenylhydrazone was followed using UV/vis and mid-infrared spectroscopic probes. Established kinetic (hard) and partial least squares (soft) modelling chemometrics methods were applied to both datasets in order to compare the information acquired with each probe. To this purpose, an experimental design with 25 samples and a test set with 5 samples were used to build a partial least squares calibration model to predict the concentration profiles of the compounds present in the reaction vessel. In addition, multivariate kinetic modelling was also performed on the spectroscopic data. Using a guess of the rate constant, concentration profiles were estimated. The profiles are then used to calculate the estimated spectroscopic profile, which is compared to the data acquired experimentally. The residual is minimised and the rate constant estimated; this procedure is iterated until convergence. A total of four profiles were obtained for each compound, corresponding to two sets of probes and two sets of models. The results were compared and discussed. It is shown that several different spectroscopic techniques can be used in reaction monitoring, with increasing benefits in terms of information and interpretation of the results. The profiles obtained agreed well which was also demonstrated when comparing the different rate constants obtained.     

A computer controlled photon counting flame emission spectrometer

An automated emission spectrometer has been developed around a simple commercial instrument. The manner in which a computer is used for control and the way data are acquired and assimilated are discussed. The interfacing to the computer is described, sample programs are illustrated and methods of analyses are given. Sensing is achieved through photon counting. The linearity of the system has been examined and it was found that, for lithium, quantitative results can be obtained with an accuracy of 1 per cent for a concentration range of four orders of magnitude. The time required for analysis is discussed and, although the spectrometer is serial in nature, the increased information rate obtained through photon counting results in high speed data acquisition.     

High resolution capillary gas chromatographic hydrocarbon-type analysis of naphtha and gasoline

A slightly modified, commercially available high resolution capillary gas chromatograph and a PC-based data processing system running proprietary software (“PONA”) have been employed in the development of a system for petroleum type analysis which would be equivalent or superior to the FIA (fluorescent indicator adsorption) method in terms of ease of use and the speed, variety, and accuracy of the analytical data produced. The system is capable of performing identification and quantitation of most of the individual components in a complex gasoline sample consisting of more than 230 components and can report weight percentage and/or volume percentage for each component as well as types by carbon number (e.g., isoparaffins, normal paraffins, olefins, naphthenes, aromatic compounds) within a ca. 70 minute analysis cycle. Precolumn sulfonation to trap olefins and aromatic compounds has been used as an complementary technique to the basic mass spectrometric identification of components of interest. The estimation of correction factors for weight percentage (or volume percentage) calculation are also discussed. Comparisons are made between this system and others, and the results indicate that the proposed method supersedes the conventional method employing FIA.     

Sparse models by iteratively reweighted feature scaling: a framework for wavelength and sample selection

In the past decade, there has been an increase in the use of sparse multivariate calibration methods in chemometrics. Sparsity describes a parsimonious state of model complexity and can be defined in terms of a subset of samples or covariates (e.g., wavelengths) that are used to define the calibration model. With respect to their classical counterparts such as principal component regression or partial least squares, sparse models are more easily interpretable and have been shown to exhibit non‐inferior prediction performance. However, sparse methods are still not as fast as the classical methods in spite of recent numerical advances. In addition, for many chemometricians, sparse methods are still “black‐box” algorithms whose internal workings are not well understood. In this paper, we describe a simple framework whereby classical multivariate calibration methods can be iteratively used to generate sparse models. Moreover, this approach allows for either wavelength or sample sparsity. We demonstrate the effectiveness of this approach on two spectroscopic data sets. Copyright © 2013 John Wiley & Sons, Ltd.     

Simple approach for elimination of blank peak effects in flow-injection analysis of samples containing trace analyte and an excess of another solute

A blank peak effect in FIA systems often found for samples containing an excess of solute other than the analyte has been studied. Emphasis has been given to trace level determinations and a simple approach for elimination of this effect is presented. The present approach is based on the use of a large sample injection volume, which results in a portion of the sample plug being undiluted with carrier and hence prevents the formation of refractive index gradients in the undiluted portion. The quantitative performance of this approach was demonstrated with the determination of iron in the presence of 0.20M sodium chloride and cobalt in the presence of 0.10M glucose. No significant difference in the accuracy, precision, and limit of detection was observed between samples for iron both in the presence and absence of sodium chloride and for cobalt in the presence and absence of glucose. Despite using a large sample volume (0.89 ml for a 400-cm sample loop), the sample throughput was about 25/hr.     

Determination of glycol in aircraft ground deicing/anti-icing fluids using flow injection with refractive index detection

A simple method for determining glycol in deicing/anti-icing fluids has been developed. The method uses a single line FIA system with detection based on Schlieren optics. The concentration range was 0-5% glycol and the limit of detection was 0.05%. Samples were preferably pumped at a flow rate of 0.7 ml/min and 100 mul of distilled water was injected (reverse FIA). Detection was accomplished with an 18 mul spectrophotometric flow cell at a wavelength of 410 nm. The conduit connecting the injector and the detector was 10 cm long and had an inner diameter of 0.5 mm. The traditional FIA approach can also be applied, i.e. injection of samples into a carrier of water, but the linear working range is narrower in comparison to the reverse FIA method. Standard addition and near infrared spectroscopy confirmed the validity of the developed method.     

Hyphenated flow injection systems and high discrimination instruments

An overview of the state-of-the-art in flow injection analysis (FIA) coupled to instruments capable of providing either multidetection and/or multi-information is reported. The versatility of FIA endows the hyphenated instruments with analytical capabilities which increase from simple sample introduction to more complex sample handling such as automatic dilution and calibration, solvent exchange, derivatization reactions and on-line separation processes, among others. Unexplored aspects of these powerful problem solvers are also discussed.     

Adaptation of a commercial ion selective fluoride electrode to a tubular configuration for analysis by flow methodologies

The determination of fluoride ions in water samples is accomplished by using a tubular flow through detector constructed by drilling a channel through a commercially available LaF(3) crystal electrode in such a way that the original contacts of the non-modified unit are maintained. Its performance when incorporated in both FIA and SIA systems was evaluated and the results show that the tubular unit retains the characteristics of the non-modified electrode. In SIA conditions an extended linear range of response and lower detection limit were achieved when compared with the electrode performance in FIA conditions. These aspects together with the additional advantage of low sample and reagent consumptions in SIA when compared to FIA, makes the incorporation of the proposed tubular ISE in a SIA system the preferred approach for on line determination and monitoring of fluoride content in natural water samples.     

Application of A Multichannel Potentiostat to Metal Ion Determinations in Flow Injection Analysis

Abstract

A 4-channel potentiostat has been developed for use with an amperometric array and applied to the determination of a mixture of metal ions in flow injection analysis (FIA). The use of an array facilitates the acquisition of three dimensional electrochemical information in real-time (current vs. potential vs. time). The data acquired can be saved in ASCII format which facilitates post-run plotting of the 2-and 3-D voltammograms in Microsoft Excel. The results demonstrate the increased information content available with an amperometric array over fixed potential electrodes. The ability to identify the individual species in mixed component injections, which is normally not possible with FIA without a prior separation step has been demonstrated. Linear responses to injections of copper(II) ions in the concentration range 500 ppm to 100 ppb were obtained.     

High‐resolution peak analysis in TOF SIMS data

High mass resolution time‐of‐flight secondary ion mass spectrometry (TOF SIMS) can provide a wealth of chemical information about a sample, but the analysis of such data is complicated by detector dead‐time effects that lead to systematic shifts in peak shapes, positions, and intensities. We introduce a new maximum‐likelihood analysis that incorporates the detector behavior in the likelihood function, such that a parametric spectrum model can be fit directly to as‐measured data. In numerical testing, this approach is shown to be the most precise and lowest‐bias option when compared with both weighted and unweighted least‐squares fitting of data corrected for dead‐time effects. Unweighted least‐squares analysis is the next best, while weighted least‐squares suffers from significant bias when the number of pulses used is small. We also provide best‐case estimates of the achievable precision in fitting TOF SIMS peak positions and intensities and investigate the biases introduced by ignoring background intensity and by fitting to just the intense part of a peak. We apply the maximum‐likelihood method to fit two experimental data sets: a positive‐ion spectrum from a multilayer MoS₂ sample and a positive‐ion spectrum from a TiZrNi bulk metallic glass sample. The precision of extracted isotope masses and relative abundances obtained is close to the best‐case predictions from the numerical simulations despite the use of inexact peak shape functions and other approximations. Implications for instrument calibration, incorporation of prior information about the sample, and extension of this approach to the analysis of imaging data are also discussed.     

Comprehensive Review on Application of FTIR Spectroscopy Coupled with Chemometrics for Authentication Analysis of Fats and Oils in the Food Products

Currently, the authentication analysis of edible fats and oils is an emerging issue not only by producers but also by food industries, regulators, and consumers. The adulteration of high quality and expensive edible fats and oils as well as food products containing fats and oils with lower ones are typically motivated by economic reasons. Some analytical methods have been used for authentication analysis of food products, but some of them are complex in sampling preparation and involving sophisticated instruments. Therefore, simple and reliable methods are proposed and developed for these authentication purposes. This review highlighted the comprehensive reports on the application of infrared spectroscopy combined with chemometrics for authentication of fats and oils. New findings of this review included (1) FTIR spectroscopy combined with chemometrics, which has been used to authenticate fats and oils; (2) due to as fingerprint analytical tools, FTIR spectra have emerged as the most reported analytical techniques applied for authentication analysis of fats and oils; (3) the use of chemometrics as analytical data treatment is a must to extract the information from FTIR spectra to be understandable data. Next, the combination of FTIR spectroscopy with chemometrics must be proposed, developed, and standardized for authentication and assuring the quality of fats and oils.     

Practical approach to archival and retrieval of analytical data in the laboratory

Today's analytical laboratory uses a large number of different instruments that are connected in networks. Together with increasing automation, data are produced at a rate that can easily reach gigabytes per month, which generates the problem of systematic archival. In addition, working under Good Laboratory Practice requires that archival of raw data be performed in such a way that they can be readily retrieved upon request, even years later. While systematic archival of data is already performed in most laboratories, it is the retrieval of saved information that is often far from straightforward. This paper describes a simple but systematic approach for both archival and retrieval of data files and related electronic documents. It consists of an unambiguous scheme for the naming of electronic files, an efficient backup strategy, a simple database holding information about any data acquired, and a convenient interface to this database that can be accessed from any workplace while assuring restricted access. The system is capable of handling several databases concurrently and is used in our facility to archive data from several workgroups. The use of freely available software such as the Linux operating system made it possible to implement a fast and stable solution at exceptionally low cost.     

Automated correlation and classification of secondary ion mass spectrometry images using a k-means cluster method

We present a novel method for correlating and classifying ion-specific time-of-flight secondary ion mass spectrometry (ToF-SIMS) images within a multispectral dataset by grouping images with similar pixel intensity distributions. Binary centroid images are created by employing a k-means-based custom algorithm. Centroid images are compared to grayscale SIMS images using a newly developed correlation method that assigns the SIMS images to classes that have similar spatial (rather than spectral) patterns. Image features of both large and small spatial extent are identified without the need for image pre-processing, such as normalization or fixed-range mass-binning. A subsequent classification step tracks the class assignment of SIMS images over multiple iterations of increasing n classes per iteration, providing information about groups of images that have similar chemistry. Details are discussed while presenting data acquired with ToF-SIMS on a model sample of laser-printed inks. This approach can lead to the identification of distinct ion-specific chemistries for mass spectral imaging by ToF-SIMS, as well as matrix-assisted laser desorption ionization (MALDI), and desorption electrospray ionization (DESI).     

Estimation of second order rate constants using chemometric methods with kinetic constraints

Several methods are described for determining rate constants for second order reactions of the form U + V --> W using chemometrics and hard modelling to analyse UV absorption spectroscopic data, where all species absorb with comparable concentrations and extinctions. An interesting feature of this type of reaction is that the number of steps in the reaction is less than the number of absorbing species, resulting in a rank-deficient response matrix. This can cause problems when using some of the methods described in the literature. The approaches discussed in the paper depend, in part, on what knowledge is available about the system, including the spectra of the reactants and product, the initial concentrations and the exact kinetics. Sometimes some of this information may not be available or may be hard to estimate. Five groups of methods are discussed, namely use of multiple linear regression to obtain concentration profiles and fit kinetics information, rank augmentation using multiple batch runs, difference spectra based approaches, mixed spectral approaches which treat the reaction as two independent pseudospecies, and principal components regression. Two datasets are simulated, one where the spectra are quite different and the other where the spectrum of one reactant and the product share a high degree of overlap. Three sources of error are considered, namely sampling error, instrumental noise and errors in initial concentrations. The relative merits of each method are discussed.     

Multivariate calibration: What is in chemometrics for the analytical chemist?

Chemometrics has been used for some 30 years but there is still need for disseminating the potential benefits to a wider audience. In this paper, we claim that proper analytical chemistry (1) must in fact incorporate a chemometric approach and (2) that there are several significant advantages of doing so. In order to explain this, an indirect route will be taken, where the most important benefits of chemometric methods are discussed using small illustrative examples. Emphasis will be on multivariate data analysis (for example calibration), whereas other parts of chemometrics such as experimental design will not be treated here. Four distinct aspects are treated in detail: noise reduction; handling of interferents; the exploratory aspect and the possible outlier control. Additionally, some new developments in chemometrics are described.     

Chemometrics in pharmaceutical analysis: an introduction, review, and future perspectives

Chemometrics is the application of statistical and mathematical methods to analytical data to permit maximum collection and extraction of useful information. The utility of chemometric techniques as tools enabling multidimensional calibration of selected spectroscopic, electrochemical, and chromatographic methods is demonstrated. Application of this approach mainly for interpretation of UV-Vis and near-IR (NIR) spectra, as well as for data obtained by other instrumental methods, makes identification and quantitative analysis of active substances in complex mixtures possible, especially in the analysis of pharmaceutical preparations present in the market. Such analytical work is carried out by the use of advanced chemical instruments and data processing, which has led to a need for advanced methods to design experiments, calibrate instruments, and analyze the resulting data. The purpose of this review is to describe various chemometric methods in combination with UV-Vis spectrophotometry, NIR spectroscopy, fluorescence spectroscopy, electroanalysis, chromatographic separation, and flow-injection analysis for the analysis of drugs in pharmaceutical preparations. Theoretical and practical aspects are described with pharmaceutical examples of chemometric applications. This review will concentrate on gaining an understanding of how chemometrics can be useful in the modern analytical laboratory. A selection of the most challenging problems faced in pharmaceutical analysis is presented, the potential for chemometrics is considered, and some consequent implications for utilization are discussed. The reader can refer to the citations wherever appropriate.