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Elements emitted from the exhausts of new Ford Falcon Forte cars powered by unleaded petrol (ULP) and liquefied petroleum gas (LPG) were measured on a chassis dynamometer. The measurements were carried out in February, June and August 2001, and at two steady state driving conditions (60 and 80kmh1). Thirty seven elements were quantified in the exhaust samples by inductively coupled plasma mass spectrometry (ICPMS). The total emission factors of the elements from the exhausts of ULP cars were higher than those of LPG cars at both engine speeds even though high variability in the exhaust emissions from different cars was noted. The effect of the operating conditions such as mileage of the cars, engine speed, fuel and lubricating oil compositions on the emissions was studied. To investigate the effects of these conditions, multivariate data analysis methods were employed including exploratory principal component analysis (PCA), and the multi-criteria decision making methods (MCDM), preference ranking organization method for enrichment evaluation (PROMETHEE) and geometrical analysis for interactive aid (GAIA), for ranking the cars on the basis of the emission factors of the elements. PCA biplot of the complete data matrix showed a clear discrimination of the February, June and August emission test results. In addition, (i) platinum group elements (PGE) emissions were separated from each other in the three different clusters viz. Pt with February, Pd with June and Rh with August; (ii) the motor oil related elements, Zn and P, were particularly associated with the June and August tests (these vectors were also grouped with V, Al and Cu); and (iii) highest emissions of most major elements were associated with the August test after the cars have recorded their highest mileage. Extensive analysis with the aid of the MCDM ranking methods demonstrated clearly that cars powered by LPG outperform those powered by ULP. In general, cars tested in June perform better than those tested in August, which suggested that mileage was the key criterion of car performance on the basis of elemental emission factors.

Organophosphorus pesticides, such as parathion methyl (PTM), fenitrothion (FT), parathion (PT), and isocarbophos (ICP), have sensitive but overlapped voltammetric peaks with peak potentials −309, −364, −317, and −480 mV, respectively, in Britton‐Robinson buffer of pH 4.8 by application of linear sweep stripping voltammetry (LSSV). In this work, two multivariate calibration methods, partial least squares (both PLS‐1 and PLS‐2), and principal component regression (PCR), were applied to quantitatively resolve the overlapping voltammogram of the mixtures of these four pesticides. The prediction results obtained from a set of independent test samples showed that PLS‐1 method performed better prediction ability than PLS‐2 and PCR methods. The proposed method was successfully applied to the determination of these four pesticides in grain samples after a pre‐extraction step with a solvent of acetone.

Raman spectroscopy has been used to investigate raw cotton acetylation using acetic anhydride/4-dimethylaminopyridine (DMAP) catalyst blend without solvent. The Raman data further confirm successful acetylation as shown by FTIR that was demonstrated previously to be highly sensitive for determining the level of acetylation. However, the Raman peaks are much weaker than the FTIR bands. Nevertheless, the variations of the extent of acetylation estimated from both Raman and FTIR spectra with weight percent gain due to acetylation (WPG) were observed to follow the same pattern. The degrees of acetylation calculated from Raman data were also found to increase linearly with that calculated from the more sensitive FTIR technique. Raman technique is thus suitable for further development as an analytical tool for determining the acetylation level of natural cellulose fibres. Raman data have also shown that the acetylation reaction reduces the crystallinity of cotton.

Anti-bacterial drugs such as sulfonamides and trimethoprim, are commonly used in medical and veterinary applications. The tablets often contain mixtures of drugs such as sulfadiazine, sulfadimidine, sulfamethoxazole, sulfanilamide and trimethoprim. Thus, a simple, rapid and inexpensive method for the simultaneous determination of these drugs was researched and developed with the aid of chemometrics methods comparing the classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS) models. UV-spectra were collected in the 200–350 nm range from a set of samples containing aqueous ethanolic solutions (pH = 9.9) of drug mixtures prepared from the above compounds with the aid of an orthogonal array design. Initial studies of the UV-spectra of the individual compounds showed that satisfactory linear regression calibration models could be constructed in the concentration range of approximately 1.0–24.0 mg l− 1 for all compounds with LOD values in the range of ca. 0.2–1.0 mg l− 1 for each of the five drugs. These studies also indicated the significant spectral overlap of the UV- spectra of the drugs showing the need for chemometrics modeling for simultaneous analysis of the mixtures. Calibration models for the three multivariate methods were constructed with the use of the raw and derivative spectral data sets. These were verified with the aid of UV-spectral data obtained from a separately prepared set of drug mixture samples. The %RPE values for analysis of the individual drugs in mixtures were in the range of 2–10 with %Recoveries being close to 100 for the PCR and PLS models while the CLS method performed relatively poorly. The four PCR and the PLS models constructed could not be distinguished on prediction performance for practical purposes, and the PCR calibration based on the raw data matrix was utilised to illustrate successfully the application of the proposed method for analysis of the drugs in commonly available pharmaceutical tablets.

A magnetic and fluorescent nano-composite was prepared. It comprised of a core of Fe3O4 nanoparticles (NPs), a silica shell and satellitic Au nano-clusters (AuNCs) capped with bovine serum albumin (BSA). This nano-composite has many desirable properties, e.g. magnetism, red emission, high water solubility, and high resistance to photo-bleaching. On addition of the analyte, 6-mercaptopurine (6-MP) or indeed other similar thiols, AuNCs formed aggregates because the existing cross-links within the Fe3O4 NPs@SiO2 and AuNC structure were broken in favor of the gold-thiol bonds. On suitable irradiation of such aggregates, red fluorescence was emitted at 613 nm. It decreased significantly as a function of the added 6-MP concentration, and the quenching ratio (F0 - F) / F0 was related linearly to the concentration of 6-MP in the range of 0.01 to 0.5 μmol L(-1). The detection limit was 0.004 μmol L(-1) (S/N=3). The method was strongly selective for 6-MP in the presence of oxidants, phenols, heavy-metal ions, and especially bio-thiols.

In this study, complex substances such as Mint (Mentha haplocalyx Briq.) samples from different growing regions in China were analyzed for phenolic compounds by high-performance liquid chromatography with diode array detection and for the volatile aroma compounds by gas chromatography with mass spectrometry. Chemometrics methods, e.g. principal component analysis, back-propagation artificial neural networks, and partial least squares discriminant analysis, were applied to resolve complex chromatographic profiles of Mint samples. A total of 49 aroma components and 23 phenolic compounds were identified in 79 Mint samples. Principal component analysis score plots from gas chromatography with mass spectrometry and high-performance liquid chromatography with diode array detection data sets showed a clear distinction among Mint from three different regions in China. Classification results showed that satisfactory performance of prediction ability for back-propagation artificial neural networks and partial least squares discriminant analysis. The major compounds that contributed to the discrimination were chlorogenic acid, unknown 3, kaempherol 7-O-rutinoside, salvianolic acid L, hesperidin, diosmetin, unknown 6 and pebrellin in Mint according to regression coefficients of the partial least squares discriminant analysis model. This study indicated that the proposed strategy could provide a simple and rapid technique to distinguish clearly complex profiles from samples such as Mint.

This paper describes a sequential chemometrics study of the use of a phenotypic property of sugarcane, its epicuticular wax, as a potential genetic marker and predictor of desirable plant traits. Epicuticular wax collected from 122 sugarcane clones was analysed by gas chromatography (GC). Fourteen principal GC peaks were identified and confirmed with the aid of Gas Chromatograph-Mass Spectrometer (GC-MS). The 122×14 GC data matrix was submitted to exploratory principal component analysis (PCA), which showed that the GC data separated according to the performance of the sugarcane clones with respect to a particular resistance trait as classified by conventional field-based rating systems. From the PCA biplot, it was possible for the first time to associate the important wax molecular components with the resistance characteristics of various sugarcane clones. This analysis stimulated research to rank the samples according to the GC data with the use of multicriteria decision-making methods (MCDM), PROMETHEE and GAIA. This experiment indicated that the ranking based on epicuticular wax components was similar to, but arguably more refined than, that obtained by the conventional field-based ratings scale. Such studies suggested that the performance of sugarcane clones could be predicted based on the molecular measurements obtained by GC. A partial least squares (PLS) calibration was constructed for the prediction of the conventional field-based performance ratings on the basis of the GC data matrix, and acceptable prediction results were obtained. Thus, it is now possible to express the sugarcane quality parameter based on accurate molecular measurements derived directly from the surface wax–a phenotypic property of the sugarcane. Additionally, this approach should reduce the time taken for breeders to rank plants.

The effectiveness of hydrothermal treatment for the destruction of the organic content of sludge waste was investigated. The sludge sampled in this study contained approximately 2% solids. The experimental program consisted of hydrothermal treatment experiments conducted in a batch reactor at temperatures between 100 and 250 °C, with the addition of an oxidant (hydrogen peroxide) in the range of 0–150% with reference to TCOD, and reaction times of up to 60 min. The results suggested that the availability of oxidant, reaction temperature and reaction time were the determining factors for COD removal. A significant fraction of the COD remaining after treatment consisted of the dissolved COD. The results confirmed that hydrothermal treatment proceeds through hydrolysis resulting in the production of dissolved organic products followed by COD removal through oxidation. Two MCDM chemometrics methods, PROMETHEE and GAIA, were applied to process the large data matrix so as to facilitate the selection of the most suitable hydrothermal conditions for sludge destruction. Two possible scenarios were produced from this analysis—one depended on the use of high temperatures and no oxidant, while the second offered a choice of compromise solutions at lower temperatures but with the use of at least some oxidant. Thus, for the final choice of operating conditions, the decision maker needs local knowledge of the costs and available infrastructure. In principle, such information could be added as further criteria to the data matrix and new rankings obtained.

Voltammetric behaviour of four carbamate pesticides, propoxur, isoprocarb, carbaryl and carbofuran, was investigated, and a method was developed for the simultaneous determination of these compounds. This was based on their anodic voltammetric behaviour observed following their alkaline hydrolysis, which produced electroactive phenol derivatives. It was found that by applying the differential pulse voltammertric (DPV) method in the presence of perchloric acid, the four compounds have well defined voltammetric oxidation waves with peak potentials at 712, 888, 664, and 688 mV, respectively. For each compound, a linear calibration was obtained in the concentration range of 1.0–30 mg l −1 . Serious overlapping of individual voltammetric peaks was observed for the mixtures of these four compounds, and to facilitate the resolution of these complex voltammograms, different calibration models were investigated based on four different chemometrics methods, viz., classical least squares (CLS), principal component regression (PCR), partial least squares (PLS) and radial basis function-artificial neural networks (RBF-ANN). The prediction ability of these models were tested with the use of a data set constructed from synthetic solutions of the four pesticides. The analytical performance of the prediction models was characterized with the use of various figures of merit, and the best results were obtained with the PC-RBF-ANN method (%RPE T = 5.6 and %Recovery (average) = 100). This method was then applied for the determination of the four pesticides in different water samples.

Maltol (MAL), ethyl maltol (EMA), vanillin (VAN) and ethyl vanillin (EVA) are food additives, and they have well defined UV spectra. However, these overlapped seriously, and it is difficult to determine them individually from their mixtures without a pre-separation. In this paper, chemometric approaches were applied to resolve the overlapping spectra and to determine these compounds simultaneously. The analysis of these four compounds was facilitated by the use of an orthogonal array data set consisting of absorption spectra in the 200–350 nm ranges obtained from a calibration set of mixtures containing these compounds. With this dataset, seven different chemometric models were built, such as classical least squares (CLS), principal components regression (PCR), partial least squares (PLS), and artificial neural networks (ANN). These chemometric models were then tested by the use of a validation dataset constructed from synthetic solutions of these four compounds. The analytical performance of these chemometric methods was characterized by relative prediction errors (RPE) and recoveries. The proposed methods were successfully applied to the analysis of commercial food samples. It was found that the radial basis function artificial neural networks (RBF-ANN) gave better results than other chemometric methods. PLS, PCR, DPLS, and DPCR also give satisfactory results, while CLS and DCLS perform poorer. It was also found that there was no advantage to pre-treat spectra by taking derivatives. The four compounds, when taken individually, behaved linearly in the 1.0–20.0 mg l −1 concentration range, and the limits of detection (LOD) for MAL, EMA, VAN and EVA were 0.39, 0.56, 0.49 and 0.38 mg l −1 , respectively.

In this work, artificial neural network (ANN), a powerful chemometrics approach for linear and non-linear calibration models, was applied to detect three pesticides in mixtures by linear sweep stripping voltammetry (LSSV) despite their overlapped voltammograms. Electrochemical parameters for the voltammetry, such as scan rate, deposit time and deposit potential, were evaluated and optimized from the signal response data using ANN model by minimizing the relative prediction error (RPE). The proposed method was successfully applied to the detection of pesticides in synthetic samples and several commercial fruit samples.

A differential pulse stripping voltammetry method (DPSV) is proposed for the determination of parathion-methyl (PTM), fenitrothion (FT) and parathion (PT) at a hanging mercury drop electrode (HMDE). The voltammograms of these three compounds overlap strongly, and it is difficult to determine the compounds individually from their mixtures. Quantitative analysis for each of the pesticide compounds in a mixture has been investigated with the aid of chemometrics and the prediction performance of the different methods such as classical least squares (CLS), principal component regression (PCR), partial least squares (PLS), Kalman filter (KF) and radial basis function-artificial neural networks (RBF-ANN), was compared. A set of synthetic mixtures of the three compounds was analysed by using the proposed methods, and it was found that the lowest relative prediction error (RPE) and satisfactory % recovery were achieved with the RBF-ANN procedure. The proposed method was also applied to several vegetable samples spiked with known amounts of the pesticides with satisfactory results.

Voltammetric behaviour of maleic hydrazide pesticide dissolved in a Britton-Robertson buffer was investigated by cyclic voltammetry (CV) and differential pulse voltammetry (DPV). It was found that the process at the Hg electrode was diffusion controlled; the reaction was irreversible and involved a change of one proton and a transfer of one electron. A quantitative differential pulse voltammetric method for determination of maleic hydrazide was developed on the basis of these studies involving the reduction of the compound at a hanging mercury drop electrode. A linear calibration was obtained in the range of 0.5-5.5mgl(-1), and the developed DPV methodology was then applied for the determination of maleic hydrazide in spiked vegetable samples by the standard addition method. Satisfactory percentage R.S.D. ( approximately 2%), percentage recovery values ( approximately 85%) and LOD (0.215mgl(-1)) were obtained. These compared well with the results from the alternative spectrophotometric method.

A method for the simultaneous determination of the pesticides, carbofuran, isoprocarb and propoxur in fruit and vegetable samples has been investigated and developed. It is based on reaction kinetics and spectrophotometry, and results are interpreted with the aid of chemometrics. The analytical method relies on the differential rates of coupling reactions between the hydrolysis product of each carbamate and 4-aminophenol in the presence of potassium periodate in an alkaline solution. The optimized method was successfully tested by analyzing each of the carbamates independently, and linear calibration models are described. For the simultaneous determinations of the carbamates found in ternary mixtures, kinetic and spectral data were processed either by three-way data unfolding method or decomposed by trilinear modeling. Subsequently, 10 different RBF-ANN, PARAFAC and NPLS calibration models were constructed with the use of synthetic ternary mixtures of the three carbamates, and were validated with a separate set of mixtures. The performance of the calibration models was then ranked on the basis of several different figures of merit with the aid of the multi-criteria decision making approach, PROMETHEE and GAIA. RBF-ANN and PC-RBF-ANN were the best performing methods with %Relative Prediction Errors (RPE) in the 3–4% range and Recovery of about 97%. When compared with other recent studies, it was also noted that RBF-ANN has consistently outperformed the more common prediction methods such as PLS and PCR as well as BP-ANN. The successful RBF–ANN method was then applied for the determination of the three carbamate pesticides in purchased vegetable and fruit samples.

This paper presents a study undertaken to evaluate site suitability for sewage effluent renovation based on physico-chemical characteristics of the soil. The results obtained showed that as the soil becomes acidic, the phosphorus concentration in the soil reduces accordingly. The chloride ion concentration was found to be a reliable indicator for evaluating the soil capacity to remove nitrogen. A high cation exchange capacity (CEC) can enhance the renovation of sewage effluent. Soils with high quartz content had a low CEC with high organic matter content (OM) being able to compensate. Therefore, an understanding of the micro-nutrients in the soil, organic matter content and chloride ion concentration are important. To facilitate a multi-variate approach for site selection, multicriteria decision-making (MCDM) methods, PROMETHEE and GAIA, were applied for analysis of a sequence of three matrices consisting of 8, 16, and 48 soil site objects, respectively, and seven soil property parameters. Matrix models and the interpretation of results are discussed in detail. From these analyses, PROMETHEE II net outranking flows, ϕ , found that two sites were always among the top three ranks of the three matrix models, which suggested that they were the most suitable for sewage effluent renovation. The criteria CEC and OM, were particularly important for the selection of these better sites, but pH and Cl − attributes discriminated the weaker performing sites from the better ones; as well the PO 4 3− and the NH 3 –N criteria were in general opposition to CEC, OM, pH and Cl − but were much less effective as discriminators. Consideration of net outranking flows suggested an approach method for the selection of other possibly suitable sites for sewage effluent renovation.

A voltammetric method, aided by chemometrics, was developed for the simultaneous determination of paracetamol and phenobarbital in pharmaceuticals. Both of these analytes gave well‐defined oxidation peaks in the Britton–Robinson buffer (pH 5.72) when analyzed by differential pulse‐stripping voltammetry (DPSV) at a glassy carbon electrode. The experimental conditions were optimized: 200 mV—deposition potential, 160 s—deposition time, 4 mV—increment potential, 50 mV—amplitude, and 60 ms—pulse width. Under these selected conditions, the oxidation current had a linear relationship with concentration of paracetamol [ranges: 0.09–0.93 mg l−1 (r 2 = 0.999) and 0.9–11.7 mg l−1 (r 2 = 0.999)], and phenobarbital [1.0–22.0 mg l−1 (r 2 = 0.999)]. Due to the overlapping voltammograms from the two analytes, two chemometrics methods, partial least squares (PLS), and principal component regression (PCR), were used for building calibration models from voltammograms of mixtures. These models were applied for predi...

The application of multicriteria decision-making methods to the results of in vitro antifungal properties of organotin compounds of the type PhxSnXz (x = 2 or 3; X = O2CC6H4OH, O2CC6H4OCOCH3, Cl or O2CCH3; z = 1 or 2) and of free 2-hydroxybenzoic and 2-acetoxybenzoic acids against Aspergillus niger, Aspergillus flavus, Candida albicans, Penicillium citrinum, Trichophyton rubrum and Trichophyton violaceum have been described. Ranking information necessary to select one toxicant in preference to others and to assess the properties influencing the preference has been obtained. Patterns in the multivariate analyses suggest that cationic and anionic moieties of the toxicant play some roles in their fungicidal activities. The triphenyltin compounds were generally more active than their diphenyltin analogues, but the acetoxybenzoates were more active than the corresponding hydroxybenzoates, acetates or chlorides. Thus, triphenyltin acetoxybenzoate is up to 7.5 times as active as the corresponding acetate, which is commercially marketed as a fungicide. The results of the analyses have been discussed in the light of the mechanism of antifungal activity of organotin compounds and the potential of multivariate data analysis techniques to facilitate the screening and ranking of antifungal agents. Copyright © 2003 John Wiley & Sons, Ltd.

This paper reviews the synthesis and the absorbing properties of the wide variety of porous sorbent materials that have been studied for application in the removal of organics, particularly in the area of oil spill cleanup. The discussion is especially focused on hydrophobic silica aerogels, zeolites, organoclays and natural sorbents many of which have been demonstrated to exhibit (or show potential to exhibit) excellent oil absorption properties. The areas for further development of some of these materials are identified.

Metal ions such as Co(II), Ni(II), Cu(II), Fe(III) and Cr(III), which are commonly present in electroplating baths at high concentrations, were analysed simultaneously by a spectrophotometric method modified by the inclusion of the ethylenediaminetetraacetate (EDTA) solution as a chromogenic reagent. The prediction of the metal ion concentrations was facilitated by the use of an orthogonal array design to build a calibration data set consisting of absorption spectra collected in the 370–760 nm range from solution mixtures containing the five metal ions earlier. With the aid of this data set, calibration models were built based on 10 different chemometrics methods such as classical least squares (CLS), principal component regression (PCR), partial least squares (PLS), artificial neural networks (ANN) and others. These were tested with the use of a validation data set constructed from synthetic solutions of the five metal ions. The analytical performance of these chemometrics methods were characterized by relative prediction errors and recoveries (%). On the basis of these results, the computational methods were ranked according to their performances using the multi-criteria decision making procedures preference ranking organization method for enrichment evaluation (PROMETHEE) and geometrical analysis for interactive aid (GAIA). PLS and PCR models applied to the spectral data matrix that used the first derivative pre-treatment were the preferred methods. They together with ANN-radial basis function (RBF) and PLS were applied for analysis of results from some typical industrial samples analysed by the EDTA-spectrophotometric method described. DPLS, DPCR and the ANN-RBF chemometrics methods performed particularly well especially when compared with some target values provided by industry.

When trace elements present in complex matrices are analysed by inductively coupled plasma optical emission spectroscopy (ICP-OES) correction must be made for the background if it overlaps with the desired trace analyte spectrum. However, often this is difficult to achieve because the required pure materials for the complex background matrix cannot be obtained, and hence the standard spectra are unavailable. A chemometrics solution to resolve the overlapping ICP-OES spectra of some such systems (gray systems) is proposed in this paper so as to obviate the need for the background standards. The case considered involves trace calcium in the presence of a large rare-earths background: Pr–Ca, Nd–Ca, Tb–Ca, Ho–Ca and Er–Ca. The application of iterative target transformation factor analysis (ITTFA) is explored to resolve the spectral interferences produced by the ultra-high-purity rare-earth matrices so as to facilitate the determination of the trace calcium. Once the ITTFA method has extracted the required background spectrum, a Kalman filter (KF) procedure is then used for the quantitative determination of the trace element. The calcium results are compared with those estimated by the conventional standard addition method, and improved results are observed. In addition, while in the absence of suitable standards such an approach is essential for the problem of the determination of the trace calcium in the rare-earth matrix described, this method should also be applicable to white systems, thereby often reducing costs of analysis as well as labour associated with the preparation of background material standards.

The FTIR spectra were measured for raw Uplands Sicala-V2 cotton fibers over a temperature range of 40–325°C to explore the temperature-dependent changes in the hydrogen bonds of cellulose. These cotton–cellulose spectra exhibited complicated patterns in the 3800–2800 cm−1 region and thus were analyzed by both the exploratory principal component analysis (PCA) and two-dimensional (2-D) correlation spectroscopy methods. The exploratory PCA showed that the spectra separate into two groups on the basis of thermal degradation of the cotton–cellulose and the consequent breakage of intersheet H-bonds present in its structure. Frequency variables, which strongly contributed to each principal component highlighted in its loadings plot, were linked to the frequencies assigned to vibrations of the OH groups involved in different kinds of H-bonds, as well as to vibrations of the CH groups. Deeper insights into reorganization of the temperature-dependent hydrogen bonding were obtained by 2-D correlation spectroscopy. Synchronous and asynchronous spectra were analyzed in the temperature ranges of 40 to 150 and 250 to 320°C, the ranges indicated by PCA. Detailed band assignments of the OH stretching region and changes in the patterns of the hydrogen bonding network of the cotton–cellulose were proposed with the aid of the 2-D correlation spectroscopy analysis. Below 150°C, distinctly different bands assigned to the less stable Iα and the more stable Iβ interchain H-bonds O6H6…O3′ were observed at about 3230 and 3270 cm−1, respectively. Evaporation of water entrapped in the cellulose network was examined by means of the band at about 3610 cm−1. The cooperativity of hydrogen bonds, which play a key role in the cellulose conformation, was monitored by frequencies assigned to intrachain H-bonds. It was possible to separate the frequencies assigned to the O2H2…O6 and O3H3…O5 intrachain H-bonds into two separate ranges, the spread of which was controlled by the cooperativity effect. The temperature dependence of the asynchronous spectra indicated that the less stable O3H3…O5 bonds gave rise to an absorption extending from 3300 to 3384 cm−1, while the more stable O2H2…O6 bonds were characterized by the absorption between 3400 and 3470 cm−1. The final breaking of the inter- and intrachain H-bonds, which occurs at the higher temperatures, was monitored by the asynchronous peaks at 3533 and 3590 cm−1, respectively. On the basis of both the exploratory PCA and 2-D correlation spectroscopy investigations, it was possible to extract well-defined wavenumber ranges assigned to different kinds of intra- and interchain hydrogen bonds, as well as to the free OH groups of the cotton–cellulose. © 2002 Wiley Periodicals, Inc. Biopolymers (Biospectroscopy) 67: 456–469, 2002

Variations in the enzyme activity of acetylcholinesterase (AChE) in the presence of the nano-material, graphene oxide (GO), were investigated with the use of molecular spectroscopy UV-visible and fluorescence methods. From these studies, important kinetic parameters of the enzyme were extracted; these were the maximum reaction rate, Vm , and the Michaelis constant, Km . A comparison of these parameters indicated that GO inhibited the catalytic activity of the AChE because of the presence of the AChE-GO complex. The formation of this complex was confirmed with the use of fluorescence data, which was resolved with the use of the MCR-ALS chemometrics method. Furthermore, it was found that the resonance light-scattering (RLS) intensity of AChE changed in the presence of GO. On this basis, it was demonstrated that the relationship between AChE and GO was linear and such models were used for quantitative analyses of GO.

A rapid and effective sensor for the analysis of nitrophenol-based explosive substances, represented by trinitrophenol (TNP), has been developed with the use of the blue luminescent graphene quantum dots (GQDs); these GQDs are derived from citric acid by a pyrolysis procedure. They emit strong blue fluorescence at 450 nm after excitation at 365 nm, and TNP can quench this fluorescence because a fluorescence resonance energy transfer occurs. The quenching ratio ( F 0 − F )/ F 0 was related linearly to the concentration of TNP in the range of 0.1–15 μmol L −1 with a detection limit of 0.091 μmol L −1 ( S / N = 3). The developed method exhibits high sensitivity, good linearity and reliable reproducibility for the quantitative analysis of TNP in water samples. The GQDs were used directly without any further treatment or complicated modification.

A novel electrochemical biosensor, DNA/hemin/nafion–graphene/GCE, was constructed for the analysis of the benzo(a)pyrene PAH, which can produce DNA damage induced by a benzo(a)pyrene (BaP) enzyme-catalytic product. This biosensor was assembled layer-by-layer, and was characterized with the use of cyclic voltammetry, electrochemical impedance spectroscopy (EIS) and atomic force microscopy. Ultimately, it was demonstrated that the hemin/nafion–graphene/GCE was a viable platform for the immobilization of DNA. This DNA biosensor was treated separately in benzo(a)pyrene, hydrogen peroxide (H2O2) and in their mixture, respectively, and differential pulse voltammetry (DPV) analysis showed that an oxidation peak was apparent after the electrode was immersed in H2O2. Such experiments indicated that in the presence of H2O2, hemin could mimic cytochrome P450 to metabolize benzo(a)pyrene, and a voltammogram of its metabolite was recorded. The DNA damage induced by this metabolite was also detected by electrochemical impedance and ultraviolet spectroscopy. Finally, a novel, indirect DPV analytical method for BaP in aqueous solution was developed based on the linear metabolite versus BaP concentration plot; this method provided a new, indirect, quantitative estimate of DNA damage.

A simple UV spectrophotometric method has been developed for resolving ternary mixture of food colorants, Tartrazine, Sunset Yellow and Ponceau 4R, which are species with highly overlapped spectra, by using H-point standard addition method (HPSAM). In this method, the concentration of one colorant was calculated from overlapping spectra at two appropriate wavelengths, where the other two colorants were selected as interferents present the equal absorbance relationship. These wavelength pairs are generally easily found, and can be selected to give the most precise analytical results. This method was satisfactorily applied to determination of colorants of Tartrazine, Sunset Yellow and Ponceau 4R in synthetic ternary mixtures and several commercial products.

The voltammetric behavior of antipsychotic drugs, such as, chlorpromazine hydrochloride and promethazine hydrochloride has been investigated at a glassy carbon electrode in Britton–Robinson buffer of pH 9. It was found by applying the differential pulse stripping voltammetry (DPSV) that both chlorpromazine hydrochloride and promethazine hydrochloride had well formed oxidation voltammetric waves, with the peak potential for chlorpromazine hydrochloride at 620 mV, and for the two peaks of promethazine hydrochloride at 444 and 668 mV. The calibrations were linear for chlorpromazine hydrochloride and promethazine hydrochloride in the concentration ranges of 0.05–1.2 and 0.1–1 mg l−1, respectively. However, the voltammetric peaks of these two drugs, seriously overlap and it is difficult to determine them individually from a response of a drug mixture. In this work, a method for the simultaneous determination of these two drugs is proposed, and is based on their oxidation at the glassy carbon electrode. The interpretation of the complex voltammograms is achieved with the aid of chemometric methods, such as, classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS). The proposed method was applied to determine these two drugs in a set of synthetic mixtures and blood samples, and in general, satisfactory results were obtained.

The degradation of poly(ethylene oxide) (PEO) by electrolysis was investigated in an aqueous chloride or bromide medium adjusted to pH 6.5 at 25°C. The degradation was monitored by the reduction in viscosity of the reaction system. The PEO was degraded more readily by electrolysis in the presence of halide ion than in their absence. The degradability of PEO increased with an increase in halide ion concentration under a constant current and the degradation in a chloride solution is easier than that in a bromide solution. The initiation mechanism of PEO degradation is discussed; a hypohalide ion is generated during electrolysis in the presence of a halide ion, and the hydroxyl radical may be generated from this ion. This radical abstracts a hydrogen atom from the polymer to form polymer alkyl radical, and further cause chain scission.

The voltammetric behaviour of five nitro-substituted aromatic compounds, such as nitrobenzene, 2-, 3-, 4-nitrophenol and 2,4-dinitrophenol, was investigated, and a method was developed for the simultaneous determination of these compounds, based on their reduction at a hanging mercury drop electrode (HMDE). It was found that by applying the differential pulse voltammetric (DPV) approach in a Britton–Robinson buffer of pH 5.4, nitrobenzene, 2-, 3- and 4-nitrophenol had well defined voltammetric reduction waves with peak potentials at −344, −284, −292 and −376 mV, respectively. However, 2,4-dinitrophenol had two peaks with potentials at −240 and −364 mV under the same conditions. For each compound linear calibration graphs were obtained in the general concentration range of 0.05–3.0 mg l−1. In mixtures of the five compounds, serious overlapping of voltammetric peaks was observed, and with conventional analytical methodology pre-separation steps would be required. In this study, chemometrics methods of data analysis, such as partial least squares (PLS), principal component regression (PCR) and classical least squares (CLS), were applied to resolve the overlapped voltammograms. Orthogonal experimental design was used for construction of the training sets containing the five aromatic compounds in the concentration range of 0.1–2.6 mg l−1. Five significant factors or principal components were modelled for prediction by the PLS and PCR methods, respectively. The percent of relative prediction error (RPE) was similar and acceptable for both methods being approximately ±10%. The percent of recoveries were within ±10% of the target value. The CLS method performed poorly (RPET=38%). The developed method was then applied to the analysis of these nitro-substituted aromatic compounds in field samples with similar satisfactory results.

The self-assembly of layered molybdenum disulfide-graphene (MoS2-Gr) and horseradish peroxidase (HRP) by electrostatic attraction into a novel hybrid nanomaterial (HRP-MoS2-Gr) is reported. The properties of the MoS2-Gr were characterized by X-ray diffraction (XRD), high-resolution transmission electron microscopy (TEM), electrochemical impedance spectroscopy (EIS) and cyclic voltammetry (CV). UV-vis and Fourier transform infrared spectroscopy (FT-IR) indicate that the native structure of the HRP is maintained after the assembly, implying good biocompatibility of MoS2-Gr nanocomposite. Furthermore, the HRP-MoS2-Gr composite is utilized as a biosensor, which displays electrocatalytic activity to hydrogen peroxide (H2O2) with high sensitivity (679.7 μA mM(-1)cm(-2)), wide linear range (0.2 μM-1.103 mM), low detection limit (0.049 μM), and fast amperometric response. In addition, the biosensor also exhibits strong anti-interference ability, satisfactory stability and reproducibility. These desirable electrochemical properties are attributed to the good biocompatibility and electron transport efficiency of the MoS2-Gr composite, as well as the high loading of HRP. Therefore, this biosensor is potentially suitable for H2O2 analysis in environmental, pharmaceutical, food or industrial applications.

A novel, highly selective resonance light scattering (RLS) method was researched and developed for the analysis of phenol in different types of industrial water. An important aspect of the method involved the use of graphene quantum dots (GQDs), which were initially obtained from the pyrolysis of citric acid dissolved in aqueous solutions. The GQDs in the presence of horseradish peroxidase (HRP) and H2O2 were found to react quantitatively with phenol such that the RLS spectral band (310 nm) was quantitatively enhanced as a consequence of the interaction between the GQDs and the quinone formed in the above reaction. It was demonstrated that the novel analytical method had better selectivity and sensitivity for the determination of phenol in water as compared to other analytical methods found in the literature. Thus, trace amounts of phenol were detected over the linear ranges of 6.00×10(-8)-2.16×10(-6)M and 2.40×10(-6)-2.88×10(-5)M with a detection limit of 2.20×10(-8)M. In addition, three different spiked waste water samples and two untreated lake water samples were analysed for phenol. Satisfactory results were obtained with the use of the novel, sensitive and rapid RLS method.

A kinetic spectrophotometric method has been developed for simultaneous quantitative determination of acetaminophen and phenobarbital in pharmaceutical preparations, and relies on the different kinetic rates of the analytes in their oxidative coupling reaction with 3-methylbenzothiazolin-2-one hydrazone (MBTH) in the presence of hydrochloric acid and the Fe(III) oxidant. The absorbance was measured and recorded from 440 to 740 nm every 60 s from 15 to 435 s. An artificial neural network (ANN) coupled with principal component analysis (principal component artificial neural network, PC-ANN) has been described, and its principles and applications were illustrated by a simulated kinetic system. The performance of the PC-ANN was compared with a conventional ANN model. PC-ANN, as well as ANN and partial least squares (PLS), were applied to a validation set of overlapping spectra containing kinetic data of binary mixtures with different concentration ratios of acetaminophen and phenobarbital. The results show that PC-ANN is the most efficient of the three chemometrics methods applied for prediction of the two analytes.

The voltammetric behavior of synthetic food antioxidants, such as butylated hydroxyanisole (BHA), butylated hydroxytoluene (BHT), propyl gallate (PG) and tert-butylhydroquinone (TBHQ), at a glassy carbon electrode in solution of 0.1 mol l−1 perchloric acid containing 1% methanol has been investigated. The obtained linear sweep voltammograms (LSV) showed that all these four compounds have well-defined oxidation waves with peak potentials of 629, 818, 599 and 501 mV for BHA, BHT, PG and TBHQ, respectively. Linear calibration graphs were also obtained in the concentration ranges of 0.5–15.0, 0.5–8.0, 1.0–15.0 and 1.0–15.0 mg l−1 for BHA, BHT, PG and TBHQ, respectively. However, the voltammetric peaks of these antioxidants seriously overlap and it is difficult to determine them individually from a mixture without prior separation. In this work, a method for simultaneous determination of these antioxidants, based on their oxidation at the glassy carbon electrode, with the aid of chemometric approaches, such as classical least squares (CLS), principal component regression (PCR) and partial least squares (PLS), has been developed. The method was applied to determine the four antioxidants in a set of synthetic mixtures and several commercial food samples; in general, satisfactory results were obtained.

Decoloration of dyes such as methylene blue and tartrazine solutions is investigated by subjecting dye solution to electrogenerated oxygen or chlorine species in electrolytes at a Pt anode. Decoloration is weak in the presence of electrogenerated oxygen species but increases in the KCl electrolyte. Decoloration in this solution is accomplished by the electrogenerated hypochlorite ion. Also, when placed in contact with a Pt anode, cotton fabric dyed with reactive dyes is decolorized significantly after short-term electrolysis in an electrolyte containing KCl, but decoloration of dyed fabrics is very weak in an electrolyte that is free from KCl.

A general approach using principal component analysis was applied to amperometric data obtained from flow injection analysis (FIA) to select conducting electroactive polymers (CEPs) and applied potential waveforms for discrimination of potassium and methylamine. The results were compared with the selection from the application of the PCA approach for cyclic voltammetry data in our previous research. Good agreement between the two methods of selection was found, which indicates that within the general qualitative limits of the approach, PCA can be applied for selection of chemical and electrochemical parameters for FIA detection/discrimination using CEP sensor arrays detector for a range of analytes.

Many active oxygen species, especially the hydroxyl radical, may play an important role in damaging cotton fabric treated at a Pt electrode with electrogenerated oxygen. To elaborate the mechanism of this damage, we have investigated the generation of hydroxyl and superoxide radicals in electrolysis and used the colorimetric thiobarbituric acid and epinephrine spectrophotometric methods, respectively, for detection.. Generation of hy droxyl radical during electrolysis is confirmed at a Pt anode but speroxide radical is not. The electro-oxidation reactions for some model carbohydrates indicate nearly the same behavior as that with Fenton's reagent. Apparently, cotton fabric damage occurs through a reaction with a hydroxyl radical that is formed on the surface of the electrode, being initiated by the abstraction of a hydrogen atom from a cellulose molecule by the hydroxyl radical.

Human-scalp hair samples were discriminated by Fourier transform infrared (FT-IR) micro-spectroscopy and chemometrics. The hairs were flattened with a small metallic roller, and the spectra were collected in the reflectance mode. The effects of gender, race and hair oxidation were examined. The results indicate a clear separation between FT-IR spectra collected from the heads of two different subjects of the same gender, race, hair colour, hair length, and treatment. The same results have also indicated a discrimination between spectra of hairs collected from the LHS and RHS of a head of a given subject. In addition, FT-IR spectra collected from different subjects were discriminated on the basis of treatment and gender. The study has demonstrated that chemometrics provides information that is not readily available by conventional visual methods of spectral interpretation.

Various rice samples were collected in Vietnam from the Red River region, and some other parts of the country as well as from Yanco, NSW, Australia. The rice samples were analysed for 14 elements (P, K, Mg, Ca, Mn, Zn, Fe, Cu, Al, Na, Ni, As, Mo, and Cd) by ICP-AES, ICP-MS and FAAS. The analytical procedures were carefully controlled and validated using the rice flour certified material (NIES No 10). In general, the results showed that Vietnamese rice has elemental concentration ranges similar to those of the Australian and other overseas rice. However, analyses for some elements are characteristic of some Vietnamese and Australian rice samples. Thus, Vietnamese rice shows somewhat higher levels of P, K and Mg than rice samples from other countries; Mn could be a marker for the Australian rice grown in the Yanco region, and the analysed Australian samples were also very low in Cd (0.003 mg kg-1). An unusual distribution of Ni, present in higher concentrations in the white rice samples than in the brown ones, was observed for some Vietnamese rice samples.

Rice is a major cereal crop in Japan and in Asia. Its taste is determined by such factors as protein and water content as well as stickiness. It has been well established that protein and water content can be estimated by near infrared spectroscopic measurements. However, the measurement of amylose content, which is closely related to rice stickiness, at present, must be carried out by wet chemical methods. Vibrational spectroscopic techniques are possible alternative approaches for the determination of amylose content in rice and, in this paper, we report on the initial steps for the development of methodology for this purpose, namely on the comparison of FT-NIR DRIFT (Diffuse Reflectance Infrared Fourier Transform Spectroscopy), PAS (Photo-Acoustic spectroscopy) and FT-Raman spectroscopy for the discrimination of glutinous and non-glutinous rice. Perkin-Elmer System 2000 FTIR (equipped with DRIFT and PAS accessories) and System 2000 NIR FT-Raman spectrometers were used to collect spectra from ground samples of seven glutinous and 12 non-glutinous rice. When SIMCA (Soft Independent Modelling of Class Analogy) was used to classify raw spectral data, the best discrimination was achieved with the FT-Raman results followed by those from the PAS measurements. FT-Raman spectra of some samples of non-glutinous rice showed strong fluorescence effects. When these samples were excluded from analysis, modelling and classification improved.

To measure the amylose content of rice, discrimination between glutinous and non-glutinous rice by vibrational spectroscopy was performed. It was previously demonstrated that classification of raw spectra by the SIMCA method showed the FT-Raman technique provided the best discrimination of classes. In this paper, the effects of spectral pre-treatments such as differentiation and multiplicative scatter correction (MSC) on classification of the rice samples are presented. For FT-NIR DRIFT measurements, differences in classification following different pre-treatments were relatively small but the best classification was obtained with the 2nd derivative pre-treatment, although precision was generally poor. With the PAS spectral sampling method, the classification was better after MSC pre-treatment of raw spectra than either after conversion to the 1st derivative or 2nd derivative. For FT-Raman, the best result was obtained with the MSC pre-treatment. The different effects of pre-treatment on the classification of spectra of the two types of rice probably reflect the information contained in the width of the absorbance bands, because the spectra were collected at 4 cm−1 step with 8 cm−1 resolution. Since the differentiation procedure follows the moving average, very small bands would be eliminated in the process, and would not contribute to the classification analysis. It was noted that effects of fluorescence in the FT-Raman spectra were not removed, even after the MSC pre-treatment.

Raw naturally coloured and white cotton cellulose fibres were investigated by Fourier transform near-infrared (FT-NIR) spectroscopy and chemometric methods, namely principal component analysis (PCA). In general, the white cotton exhibited bands that could be associated with the structural features of the cotton cellulose polymer. But the FT-NIR spectrum of the green cotton, which is reported for the first time, exhibited a sharp band at 4250 cm–1. Further band analysis indicated that green cotton contains a higher C–H content and a lower C–C/C–O and O–H fractions than other natural cotton fibres, suggesting that it has undergone an oxidation process as indicated in the previous FT-Raman spectroscopic study (see Liu, Y., Kokot, S., and Sambi, J., Analyst, 1998, 123, 633). Although the PCA scores plot of FT-NIR spectra of seven types of cotton fibres showed no better separation than that of FT-Raman spectra, it is still possible to differentiate the various types of natural cotton fibres.

A diffuse reflectance Fourier transform infrared spectroscopy (DRIFTS) investigation was performed on a series of poplin cotton fabrics treated with a bifunctional reactive dye of unknown chemical structure and composition, and in different states on the substrate (unfixed or fixed to the cotton substrate as well as chemically treated). The cotton-cellulose bands (log 1/R) dominate the spectra of the dyed fabric samples, and this leads to difficulties in the discrimination and matching of such spectra. However, it is demonstrated that qualitative discrimination is achieved by using principal component analysis (PCA). The dye state is the basis for this; also, within the % dye concentration series separation of spectra is observed according to the amount of the dye present. Exploratory quantitative analysis of such samples, attempted with partial least squares (PLS) regression, shows that it may be possible to predict the % concentrations with larger calibration sets. Further, series of fabrics were dyed with different reactive dyes and again treated to obtain various reactive dye states. The DRIFT spectra of these fabrics were submitted to PCA, with qualitative discrimination being achieved on the basis of dye colour and the reactive dye state. It is shown that the spectra of the unfixed dyes are similar to those of the neat dye powders. This study indicates that DRIFTS may be useful for matching, discrimination and prediction of reactive dyes on cotton substrates even if the dye structure is unavailable. This points to potential applications in the dye and general textile industry as well as specific forensic cases involving relatively large samples. In addition, it is clear that further carefully designed experiments may lead to a clarification of the details of binding of polyfunctional reactive dyes on cotton.

The degradation of azo dyes such as Orange I_??_IV was investigated in an electrolyte solution containing chloride or bromide ions as halide ions with electrolysis. In the presence of halide ions, the electrolyzed degradation was accomplished because of the generated electrophilic halonium ions as active species with electrolysis that involve initial attack at azo groups. It was presumed that these degradations were due to the molecular structure of dyes relating to the existence of azo-hydrazone equilibria in hydroxyazo dyes and electron-donating group in aminoazo dyes. In the case of an electrolyte solution containing chloride ion, the degradation of dyes was significantly influenced by the pH of this electrolyte and decrease with rising pH. The ability of degradation with electrolysis was larger in bromide ion than that in chloride ion and the pH of electrolyte had no influence on the degradation in the case of bromide ion, compared with chloride ion.

A simple, inexpensive and sensitive kinetic spectrophotometric method was developed for the simultaneous determination of three anti-carcinogenic flavonoids: catechin, quercetin and naringenin, in fruit samples. A yellow chelate product was produced in the presence neocuproine and Cu(I) - a reduction product of the reaction between the flavonoids with Cu(II), and this enabled the quantitative measurements with UV-vis spectrophotometry. The overlapping spectra obtained, were resolved with chemometrics calibration models, and the best performing method was the fast independent component analysis (fast-ICA/PCR (Principal component regression)); the limits of detection were 0.075, 0.057 and 0.063 mg L(-1) for catechin, quercetin and naringenin, respectively. The novel method was found to outperform significantly the common HPLC procedure.

Phenols are well known noxious compounds, which are often found in various water sources. A novel analytical method has been researched and developed based on the properties of hemin-graphene hybrid nanosheets (H-GNs). These nanosheets were synthesized using a wet-chemical method, and they have peroxidase-like activity. Also, in the presence of H2O2, the nanosheets are efficient catalysts for the oxidation of the substrate, 4-aminoantipine (4-AP), and the phenols. The products of such an oxidation reaction are the colored quinone-imines (benzodiazepines). Importantly, these products enabled the differentiation of the three common phenols - pyrocatechol, resorcin and hydroquinone, with the use of a novel, spectroscopic method, which was developed for the simultaneous determination of the above three analytes. This spectroscopic method produced linear calibrations for the pyrocatechol (0.4-4.0 mg L(-1)), resorcin (0.2-2.0 mg L(-1)) and hydroquinone (0.8-8.0 mg L(-1)) analytes. In addition, kinetic and spectral data, obtained from the formation of the colored benzodiazepines, were used to establish multi-variate calibrations for the prediction of the three phenol analytes found in various kinds of water; partial least squares (PLS), principal component regression (PCR) and artificial neural network (ANN) models were used and the PLS model performed best.

Interactions between the anti-carcinogens, bendamustine (BDM) and dexamethasone (DXM), with bovine serum albumin (BSA) were investigated with the use of fluorescence and UV–vis spectroscopies under pseudo-physiological conditions (Tris–HCl buffer, pH 7.4). The static mechanism was responsible for the fluorescence quenching during the interactions; the binding formation constant of the BSA–BDM complex and the binding number were 5.14 × 105 L mol−1 and 1.0, respectively. Spectroscopic studies for the formation of BDM–BSA complex were interpreted with the use of multivariate curve resolution – alternating least squares (MCR–ALS), which supported the complex formation. The BSA samples treated with site markers (warfarin – site I and ibuprofen – site II) were reacted separately with BDM and DXM; while both anti-carcinogens bound to site I, the binding constants suggested that DXM formed a more stable complex. Relative concentration profiles and the fluorescence spectra associated with BDM, DXM and BSA, were recovered simultaneously from the full fluorescence excitation–emission data with the use of the parallel factor analysis (PARAFAC) method. The results confirmed that on addition of DXM to the BDM–BSA complex, the BDM was replaced and the DXM–BSA complex formed; free BDM was released. This finding may have consequences for the transport of these drugs during any anti-cancer treatment.

A novel modified electrode was constructed by the electro-polymerization of 4,5-dihydroxy-3-[(2-hydroxy-5-sulfophenyl)azo]-2,7-naphthalenedisulfonic acid trisodium salt (acid chrome blue K (ACBK)) at a graphene oxide (GO)-nafion modified glassy carbon electrode (GCE). The characterization of an electrochemically synthesized poly-ACBK/GO-nafion film was investigated by electrochemical impedance spectroscopy (EIS), cyclic voltammetry (CV), atomic force microscopy (AFM) and scanning electron microscopy (SEM) techniques, and the results were interpreted and compared at each stage of the electrode construction. Electrochemical oxidation of eight β-agonists – clenbuterol, salbutamol, terbutaline, ractopamine, dopamine, dobutamine, adrenaline, and isoprenaline, was investigated by CV at the different electrodes. At the poly-ACBK/GO-nafion/GCE, the linear sweep voltammetry peak currents of the eight β-agonists increased linearly with their concentrations in the range of 1.0–36.0 ng mL−1, respectively, and their corresponding limits of detection (LODs) were within the 0.58–1.46 ng mL−1 range. This electrode showed satisfactory reproducibility and stability, and was used successfully for the quantitative analysis of clenbuterol in pork samples.

A comparison of predicted values of the breaking force of cotton fabrics as measured by diffuse reflectance infrared Fourier transform (DRIFT) spectroscopy and thermogravimetry (TG) was carried out with the aid of the partial least squares (PLS) method. Excellent agreement was found for the validation set of samples with a standard errors of prediction (SEP) value of about 3%. Three thermal degradation parameters of eight different cellulosic samples, predicted from thermogravimetric measurements again using PLS, gave good analytical results on a small validation sample set.

Thermal behavior of different cellolusic fabrics was investigated in air and nitrogen by TG, DTG and DTA. Kinetic parameters based on weight loss for the initial and major stages of thermal degradation were determined. The weight loss in the TG curve for the cellulosic fabrics can be divided into four stages. In general, Ea values in air are lower than those in nitrogen, and the enthalpy changes as well as rates of degradation in air are much larger than those in nitrogen. This indicates that the thermal degradation of cellulosic fabric is promoted by oxygen. The Ea values of regenerated cellulose fabrics (viscose and modal) at the rapid weight loss stage are relatively higher than those of the cotton and linen fabrics. The raw cotton has the lowest Ea of all cellulosic fabrics, but its frequency factor and rate of weight loss are also the lowest. The thermal behavior of linen is similar to that of the raw cotton. Bleached, boiled and antibacterially finished cotton fabrics are also compared. Thermal behavior and kinetic parameters for the different cellulosic fabrics are discussed in the light of their structural characteristics, including degree of polymerization, crystallinity, crystalline form, orientation and morphology. Also the effects of the impurities and additives on the fabric are considered. © 1996 John Wiley & Sons, Inc.

Electrochemical behavior of three antioxidants: butylated hydroxyanisole (BHA), butylated hydroxytoluene (BHT) and butylated hydroquinone (TBHQ), was investigated at a glassy carbon electrode modified with gold nanoparticles (AuNPs/GCE). This electrode was characterized by scanning electron microscopy (SEM). The experimental results indicated that the modified electrode was strongly electroactive during the redox reactions of BHA, BHT and TBHQ, and this was confirmed by the observed increased redox peak currents and shifted potentials; in addition, the oxidation products of BHA and TBHQ were found to be the same. The experimental conditions were optimized and the oxidation peaks of BHA and BHT were clearly separated. Based on this, an electrochemical method was researched and developed for the simultaneous determination of BHA, BHT and TBHQ in mixtures with the use of first derivative voltammetry; the linear concentration ranges were 0.10-1.50 μg mL(-1), 0.20-2.20 μg mL(-1) and 0.20-2.80 μg mL(-1), and detection limits were 0.039, 0.080 and 0.079μgmL(-1), for BHA, BHT and TBHQ, respectively. The proposed method was successfully applied for the analysis of the three analytes in edible oil samples.

Diffuse reflectance infrared spectra of differently mercerized cotton poplin fabrics are interpreted with the aid of fuzzy clustering and multivariate chemometrics methods (PCA and SIMCA). Fuzzy clustering analysis of spectra from blank, slack, and stretch mercerized samples shows that three clusters can be identified, and this conclusion is supported by the PCA display method and SIMCA classification. Spectra from slack mercerized samples, treated at three different temperatures, are also readily discrim inated by the same three chemometrics methods.