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This worlk proposes a rapid, sensitive and accurate flow-batch digital image colorimetric (FB-DIC) system to zinc oxid determination in ointments. The method was based on the reaction between Zn(II) ions and zincon at pH = 9.0. The Zn(II)-zincon complex was formed and detected in the mixing chamber. It was designed with two opposite glass windows: one for the webcam and other for the ultra-bright LED. Absorbance was calculated by the norm of the vector in the RGB space. The method had a linear range between 1.0-8.2 mg L–1 with R2 = 0.9998 (n=8) and limit of detection estimated as 5.7 mg L–1. The relative standard deviation (RSD) and sample throughput were estimated at 0.06% and 109 samples h-1, respectively. Ointment commercial samples were analyzed by FB-DIC and the refference method. The results shown no statistically significant difference between them, when was applied the paired t-test at the 95% confidence level. According to green analytical chemistry (GAC) principles the FB-DIC system can be considered eco-driendly due to its low samples and reagents consumption as its low waste generation.

Matrix complexity of fruit juices and their low antimony level requires sensitive, cost-effective instruments, time-consuming and error-prone sample pretreatment methods. Therefore, a flow-batch procedure (HG-FBA-AFS) was developed for the fast and sensitive determination of total inorganic Sb in grape juice samples by hydride generation atomic fluorescence spectrometry. The sample pretreatment, pre-reduction and stibine formation steps run through the mixing chamber. The HCl and NaBH

This work describes a 3D-printed robotic system named RSAWA (robotic system for automatic water analysis) for fully automated water analysis. RSAWA consists of a robotic arm coupled to a syringe pump, temperature and conductivity sensors, a low-cost webcam as colorimetric detector, and a 96-well microplate placed on a 3D-printed platform. The robotic system is controlled by software and it performs all analytical procedures. RSAWA was applied to measure conductivity (CDT), pH, total alkalinity (TA), total hardness (TH), chloride (Cl−), nitrite (NO2−), total dissolved phosphorus (TP), and total iron (TI) in drinkable water samples. A simple circuit was designed for conductivity determinations, while colorimetric pH determinations were carried out using Hue values extracted from digital images and a pH universal indicator. HSV histograms were used to calculate Pearson's correlation coefficients, allowing the construction of accurate titration curves. In addition to achieving sample throughputs of 112 h−1 for TA and TH determinations and 92 h−1 for Cl− determinations, RSAWA produced 99.5% less waste than the corresponding reference methods during titrations. Colorimetric measurements were performed through RGB vector norms calculated from digital images were used as analytical signals. Limits of quantification (μg L−1) were 6.83, 13.0 and 1.5 mg L−1 for NO2−, TP, and TI determinations, respectively. Sample throughputs (samples h−1) were 83 for NO2− and TP and 72 for TI with a 98.5% reduction in waste generation. Thus, RSAWA is a low-cost, feasible, and environmentally friendly alternative to quickly and accurately determine several chemical and physicochemical parameters in aqueous samples.

A green, rapid and sensitive automated analytical method with imaging detection for the determination of sulfite in vinegars using the pararosaniline (PRA)–formaldehyde–sulfite reaction is demonstrated. This work proposes the use of a flow-batch analyzer (FBA) in association with digital images (DIs) obtained from a webcam to perform fast and accurate quantification of sulfite in vinegar samples with low waste generation and high sensitivity. The FBA designed for the monitoring of the PRA–formaldehyde–sulfite reaction under non-equilibrium conditions consisted of a mixing chamber (MC) with a lateral glass window and an ultra-bright LED mounted on top of the MC. Rigorous luminosity and time control were required to acquire accurate and precise data from digital images taken during the reaction. An algorithm based on RGB norm vectors (∥νRGB∥) with gamma correction was developed for absorbance calculations. The proposed method was applied to sulfite quantification in five different vinegar samples (apple cider, distilled, lemon, and white and red wine), with iodometric titration as a comparative method. The estimated LOD was 0.04 mg L−1, with a linear range of from 0.13 to 32.7 mg L−1, recoveries were in the range 94–107%, and the sample throughput was 43 h−1 at a reaction time of 30 s. Both the proposed and reference methods were statistically compared using a paired t-test at a confidence level of 95% and the maximum standard deviation was 1.6 and 1.7 mg L−1, respectively. All of the results reported here confirm the proposed method's potential to be a very rapid, low-cost and trustworthy tool, applicable for the quality control of sulfite in a wide variety of vinegar. The low levels of reagent consumption and waste generation in the proposed method qualify the analytical procedure as environmentally friendly and in alignment with green chemistry guidelines.

This study addresses the challenge of performing fast and accurate titrations with end points that are difficult to identify. In this sense, the combination of digital movies (DMs) with a flow-batch analyzer (FBA) has shown to be a promising analytical tool. In a digital movie-based automatic titrator (DMB-AT), a DM is recorded by a webcam as the titrant is added in the mixing chamber (MC). The DM is then decompiled into frames that are ordered sequentially. In the first frame, the region of interest (ROI) of 257 × 255 pixels is defined. The red (R) component is used to calculate the Pearson's correlation coefficient (r) between the first frame and each subsequent one. The titration curve is obtained in real time by plotting r values and the opening time of the titrant valve. The experimental titration curve is fitted in a sigmoidal regression, and the new titration curve is used to estimate the end point by means of the second derivative method. A software program written in Adobe AIR for a desktop platform programmed in ActionScript 3.0 controlled the opening time of the solenoid valves, gathered the analytical signal and carried out the analytical procedure in real time. The feasibility of the method was confirmed by determining the total hardness and the total alkalinity in mineral waters. The results were compared with classical batch titration and did not exhibit statistically significant differences when the paired t-test at the 95% confidence level was applied. The proposed method is able to process approximately 67 and 86 samples h− 1 for total hardness and total alkalinity, respectively. Its precision was confirmed by overall relative standard deviation (RSD) values of less than 1.0% in both applications.

This paper proposes a method to perform rapid and sensitive graphite furnace atomic absorption spectrometry (GFAAS) determination of Cr(VI) in vinegar samples without wet digestion. Taking into account low levels of Cr(VI) and the presence of several concomitants in the sample matrix, the proposed method uses single-phase liquid-liquid extraction (SPLLE). The method is automated, employing a flow-batch analyzer (FBA) which uses a mixing chamber designed to emulate a separation funnel promoting the formation/break of the single-phase solution, reaction and extraction. The Cr(VI) extraction procedure was performed by proportioned mixing of the vinegar sample (aqueous phase), amyl alcohol (organic phase), and ethanol (consolute) to form a single-phase solution. The chelating reagent sodium diethyldithiocarbamate (DDTC) dissolved in the consolute reacts rapidly with Cr(VI), in the single phase to produce a stable Cr-DDTC complex. The single-phase break step is performed by adding an excess of Britton-Robinson buffer, and then the organic phase enriched with Cr(VI) was analyzed by GFAAS. Factors such as extraction steps, single-phase composition, pH, chelating agent concentration, and flow-batch parameters were optimized. The FBA-SPLLE-GFAAS was evaluated in vinegar samples showing satisfactory analytical features in terms of limit of quantification (0.86 μg L −1 ), precision (RSD

This work proposes a simple, rapid and low-cost method for the determination of total furanic aldehyde (TFA, sum of furfural and hydroxymethylfurfural) compounds in Brazilian cachaca samples, based on liquid–liquid extraction followed by UV-vis spectrophotometry. For this, 5.0 mL of chloroform and the sample are mixed and the mixture is then stirred for 2 minutes to form an emulsion, which rests for 1 minute to complete the phase separation. An aliquot of the decanted chloroform phase is then analyzed in a quartz cell (10 mm optical path) for absorbance at 279 nm. Effects of solvent, pH, temperature, possible interferences and fraction extracted were investigated. This method is not only sensitive and accurate, with an LOQ of 0.0203 mg 100 mL−1 and recoveries in the range 101–109%, but also simple and rapid (15 h−1). The new method for TFA compounds can be a potential reference method in routine safety testing for Brazilian cachaca samples or other beverages.

In this paper, a flow-batch analysis (FBA) system, hydride generation (HG), and atomic fluorescence spectrometry (AFS) are coupled for the first time to develop a fast and sensitive FBA–HG–AFS method for automated inorganic antimony speciation in waters, whether from the sea, mineral water, tap water, or lakes. Unlike previous automated flow methods that use confluent fluids and complex devices, the main advantage of the proposed FBA-HG-AFS method is an innovative use of a simple laboratory made flow-batch chamber to simultaneously perform mixing, homogenization, reactions, antimony hydride formation, and gas–liquid separation. The FBA-HG-AFS method was optimized using two–level full factorial and Box–Behnken designs, and validated on the basis of real repeated measurements and analysis of variance, yielding a satisfactory working range (100–2000 ng L−1), precision (RSD = 4%), sensitivity, and limit of detection (6 ng L−1) for the water samples analyzed. Accuracy was evaluated by recovery tests and analysis of a standard reference material (SRM 1643e) of trace elements in water (NIST, USA), resulting in recovery rates of from 90 to 114%, and relative error = 0.7%. The high sampling throughput (54 speciations h−1), together with low waste generation, low costs, low reagent and sample consumption make this FBA-HG-AFS method an interesting proposal for fast large-scale analysis in routine laboratoy according to the principles of green analytical chemistry.

A lab-made magnetic-mechanical robotic (MMR) system coupled to a flow-batch analyzer (FBA) for magnetic nanoparticles solid phase extraction (MSPE) is presented. As an illustrative application, an NMR-FBA couple was connected to a graphite furnace atomic absorption spectrometer (GFAAS) for quantification of trace cadmium in edible oils. Factors affecting MSPE, such as the amount of adsorbent, the type, concentration and volume of the eluent and elution time were studied. Under the optimized experimental conditions, the interferents studied did not reveal a significant change in the analytical response, indicating that proposed method is selective. The sampling rate, characteristic mass, working linear range, limits of detection (LOD), and sensitivity were 10 h−1, 0.18 pg, 0.05–1.0 μg kg−1, 0.006 μg L–1, and 0.4197, respectively. An enrichment factor of 9 was achieved using a 2.5 mL oil sample. In order to evaluate the accuracy, a certified reference material was analyzed by the proposed and a reference method. The values obtained were compared with the one provided from the manufacturer and no statistically significant differences were observed among three values at a confidence level of 95% using paired t-test. In addition, the precision intra-day and inter day of the proposed method and the robustness were assessed and again no statistically significant differences were observed at a confidence level of 95%. The use of a microcolumn to immobilize the MNPs is not needed with the proposed MMR-FBA-GFAAS system, thus avoiding the well-known problem of non-uniform packing of the MNPs presented in previous flow-based automatic methods. Despite a high organic load of edible oils, the method developed is simple, robust and presents satisfactory analytical features when compared with others that have been reported in the literature, suggesting that it is a potentially useful alternative to determine trace analytes in viscous matrices without external pretreatment.

In this study, a micro-flow-batch analyzer (μFBA) using an in-line cadmium reduction microcolumn for the photometric determination of nitrate and nitrite in dairy samples is described. The method is based on the Griess-Llosvay reaction and measuring of the absorbance at 540 nm using a green LED integrated into the μFBA built in the urethane-acrylate resin. Initially, the nitrite content of the dairy sample is analyzed in the mixing chamber, while the nitrate is reduced to nitrite in cadmium sponge microcolumn coupled to the microsystem. Nitrate content was calculated from the difference between nitrate plus nitrite (expressed as nitrite) and nitrite content. The analytical curve for nitrate and nitrite was linear in the work range of 10.0–100.0 μg L−1 with a correlation coefficient of 0.992 and 0.998, respectively. The limit of detection and relative standard deviation were estimated at 0.39 μg L−1 and

This paper presents a theoretical study using density functional theory (DFT) to investigate the bonding between carbon monoxide (CO) molecules and type FeN4 macrocycle complexes of iron to form FeN4–CO adducts. In order to understand how different macrocycle ligands affect this interaction, CO molecules were bound to the following complexes: iron–porphyrin (FeP), iron–tetraaza[14]annulene (FeTAA), iron–tetramethyl-tetraaza[14]annulene (FeTMTAA), iron–dibenzotetraaza[14]annulene (FeDBTAA), and iron–tetramethyl-dibenzotetraaza[14]annulenes (FeTMDBTAA1, FeTMDBTAA2). The best description of the systems investigated was provided by the Lanl2TZ(f)/6-31G⁎ basis set, which was therefore used throughout the work. Analysis of the factors influencing the CO bonding process showed that different macrocycle ligands produced adducts that were different in terms of CO bond length, total CO fragment charge, CO vibrational frequency, and CO bond order. The activity of the interaction between CO and the iron-complex was inversely proportional to the energy gap between the HOMO of the FeN4 complex and the LUMO of CO. Finally, a greater degree of back-bonding was characterized by increased occupancy of the px and py orbitals of the O atom of the CO fragment, confirming that the TAAs were more active than porphyrin, in the ascending order: FeP

This paper proposes combining Multiple Linear Regression (MLR) and Digital Image-Based Flame Emission Spectrometry (DIB-FES) to overcome the inherent spectral interference in Flame Emission Spectrometry (FES) when sodium and calcium are present in the same sample. Metals in the air–butane flame emit radiation which is revealed in the digital images captured by a webcam (detector), on the basis of the Red-Green-Blue (RGB) color system. MLR calibration models for sodium and calcium were both developed and validated. In order to illustrate the feasibility of this proposal, the validated models were applied for the determination of sodium and calcium in powder milk. The results were compared with those obtained using Flame Atomic Absorption Spectrometry (FAAS) as the reference method. No statistically significant difference was observed between the results for both metals by using the paired t-test at a 95% confidence level. The accuracy of the models was also attested to by their recovery factors which fell between 97 and 103% for both metals. The results confirm the models' discriminating power in isolating each analyte's information from a single digital image, even with spectral interference.

This study proposes a digital image-based flow-batch analyzer (DIB-FBA) for aluminum (III) and chromium (VI) determinations in natural water. A webcam with a CCD sensor and RGB data are used. The method for determining aluminum is based on an Al(III) ion, quercetin, and cetyltrimethylammonium bromide (CTAB) reaction which yields a yellow colored complex in an acetate buffer medium (pH 5.5). The determination of chromium is based on a Cr(VI) ion with 1,5-diphenylcarbazide (DPC) reaction whose product is a violet colored complex. Digital images present the color of the emergent (complementary) radiation to that absorbed by the complexes formed in each analysis. RGB data were employed to build the analytical curves. All standard solutions were prepared in-line, and all analytical processes were completed by simply changing the operational parameters in the DIB-FBA control software. The working ranges were from 10 to 600 μg L − 1 for Al(III) with r = 0.9994 (n = 5), and 10 to 300 μg L − 1 for Cr(VI) with r = 0.999 (n = 5), the limits of detection were 3.97 and 2.65 μg L − 1 respectively for Al(III) and Cr(VI). The relative standard deviation (RSD %) and sampling rate were estimated at 1.5% and 137 h − 1 and at 1.7% and 134 h − 1 for Al(III) and Cr(VI), respectively. Comparing with the reference method, no statistically significant differences were observed when applying the paired t -test at a 95% confidence level.

In this study a flow-batch analyzer (FBA) was utilized and its feasibility was demonstrated for the determination of Fe(III) in edible and lubricating oils without external pretreatment. The FBA method uses the reaction of this ion with thiocyanate in organic medium. The formed red complex was monitored by employing a light emitting diode (LED, λmax = 520 nm) and a phototransistor linked to the mixing chamber by optical fibers. All standard solutions were prepared in-line and all analytical processes were carried out by simply changing the operational parameters in FBA control software. Comparing with the reference method, no statistically significant differences were observed when applying the paired t-test at a 95% confidence level. The relative standard deviation, analytical frequency and limit of detection were estimated for both viscous matrices (edible and lubricating oils) at

This paper introduces for the first time the combination of digital images taken with a webcam and a micro-flow-batch analyzer as a novel strategy for implementing quantitative chemical analysis. The digital image-based micro-flow-batch analyzer (DIB-μFBA) was formed using urethane-acrylate resin, glass slides and ultraviolet lithography. The glass slides were used as sealant layers on both sides of the substrate urethane-acrylate and provide the necessary transparency to the microsystem to conduct studies using digital images. DIB-μFBA uses digital images obtained from a webcam with CCD sensor, based on the RGB (red–green–blue) color model. The analyzer was used for determining the tannins in green tea employing the well-known ferrous tartrate method. All standard solutions were prepared in-line, and all analytical processes were completed by simply changing the operational parameters in DIB-μFBA control software. The paired t test, at a 95% confidence level, showed no statistically significant differences between results obtained by DIB-μFBA and the spectrophotometric reference method. The proposed microsystem presented satisfactory physical and chemical properties while keeping the flexibility, versatility, robustness and multi-task characteristics of conventional flow-batch analysis. Therefore, it was possible to build a low-cost device with high sample throughput (about 190 h− 1) and reduced reagent consumption (about 300 times less than the reference method), contributing to the basic principles of green chemistry and the advancement of micro-analytical procedures.

Since its inception, flow-based analysis has dramatically transformed the way that sample analysis is handled. What used to be manual, slow and prone to error has become automated, rapid and precise. Though many improvements and modifications have already been explored, a most promising development has been the flow-batch analyzer. Through use of an instantaneous stop-mixing chamber and computer-controlled, flow-based sampling, it achieves extraordinarily high sampling rates. We review its historical evolution, components, features and operation, and analytical applications.

The principal thermodynamic advantages of using microemulsions over standard emulsions for flow metal analysis are the greatly increased analyte stability and emulsive homogeneity that improve both the ease of sample preparation, and the analytical result. In this study a piston propelled flow-batch analyzer (PFBA) for the determination of Cu, Cr and Pb in gasoline and naphtha by graphite furnace atomic absorption spectrometry (GF AAS) was explored. Investigative phase modeling for low dilution was conducted both for gasoline and naphtha microemulsions. Rheological considerations were also explored including a mathematical flow derivation to fine tune the system's operational parameters, and the GF AAS coupling. Both manual and automated procedures for microemulsion preparation were compared. The results of the paired t test at a 95% confidence level showed no significant differences between them. Further recovery test results confirmed a negligible matrix effect of the sample on the analyte absorption signals and an efficient stabilization of the samples (with metals) submitted to microemulsion treatment. The accuracy of the developed procedure was attested by good recovery percentages in the ranges of 100.0 ± 3.5% for Pb in the naphtha samples, and 100.2 ± 3.4% and 100.7 ± 4.6% for Cu and Cr, respectively in gasoline samples.

A flow injection photometric system that exploits Schlieren signals for analytical measurement is described. The system was designed to be used as a new strategy for determining the contents of sodium chloride, potassium chloride and glucose, each respectively in injectable drugs. The proposed methodology was based on the difference between the refractive indices of the sample zone and of the carrier stream. With this perspective, a lab-made photometer based on LED-phototransistor technology was employed as a detection system to investigate the different analytical profiles related to the Schlieren effect in low flow rate conditions. The parameters of the flow system, such as flow-rate, optical path length, and sampling loop, were adjusted in order to obtain suitable Schlieren profiles for the measurements. Data evaluation was performed with the application of partial least squares regression (PLS-1). The obtained results demonstrated the predictive ability of the constructed PLS models, and the predicted concentration values were in agreement with the reference values, with a 95% confidence level.

An enzymatic flow-batch system with spectrophotometric detection was developed for simultaneous determination of levodopa [(S)-2 amino-3-(3,4-dihydroxyphenyl)propionic acid] and carbidopa [(S)-3-(3,4-dihydroxyphenyl)-2-hydrazino-2-methylpropionic acid] in pharmaceutical preparations. The data were analysed by univariate method, partial least squares (PLS) and a novel variable selection for multiple lineal regression (MLR), the successive projections algorithm (SPA). The enzyme polyphenol oxidase (PPO; EC 1.14.18.1) obtained from Ipomoea batatas (L.) Lam. was used to oxidize both analytes to their respective dopaquinones, which presented a strong absorption between 295 and 540 nm. The statistical parameters (RMSE and correlation coefficient) calculated after the PLS in the spectral region between 295 and 540 nm and MLR-SPA application were appropriate for levodopa and carbidopa. A comparative study of univariate, PLS, in different ranges, and MLR-SPA chemometrics models, was carried out by applying the elliptical joint confidence region (EJCR) test. The results were satisfactory for PLS in the spectral region between 295 and 540 nm and for MLR-SPA. Tablets of commercial samples were analysed and the results obtained are in close agreement with both, spectrophotometric and HPLC pharmacopeia methods. The sample throughput was 18 h-1. Fil: Grunhut, Marcos. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina Fil: Centurión, María Eugenia. Universidad Nacional del Sur. Departamento de Química; Argentina Fil: Fragoso, Wallace D.. Universidade Federal da Paraíba; Brasil Fil: Almeida, Luciano F.. Universidade Federal da Paraíba; Brasil Fil: de Araújo, Mário C.U.. Universidade Federal da Paraíba; Brasil Fil: Fernández Band, Beatriz Susana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Química del Sur. Universidad Nacional del Sur. Departamento de Química. Instituto de Química del Sur; Argentina

The increasing development of miniaturized flow systems and the continuous monitoring of chemical processes require dramatically simplified and cheap flow schemes and instrumentation with large potential for miniaturization and consequent portability. For these purposes, the development of systems based on flow and batch technologies may be a good alternative. Flow-batch analyzers (FBA) have been successfully applied to implement analytical procedures, such as: titrations, sample pre-treatment, analyte addition and screening analysis. In spite of its favourable characteristics, the previously proposed FBA uses peristaltic pumps to propel the fluids and this kind of propulsion presents high cost and large dimension, making unfeasible its miniaturization and portability. To overcome these drawbacks, a low cost, robust, compact and non-propelled by peristaltic pump FBA is proposed. It makes use of a lab-made piston coupled to a mixing chamber and a step motor controlled by a microcomputer. The piston-propelled FBA (PFBA) was applied for automatic preparation of calibration solutions for manganese determination in mineral waters by electrothermal atomic-absorption spectrometry (ET AAS). Comparing the results obtained with two sets of calibration curves (five by manual and five by PFBA preparations), no significant statistical differences at a 95% confidence level were observed by applying the paired t-test. The standard deviation of manual and PFBA procedures were always smaller than 0.2 and 0.1mugL(-1), respectively. By using PFBA it was possible to prepare about 80 calibration solutions per hour.

This study proposes the use of digital movies (DMs) in a flow–batch analyzer (FBA) to perform automatic, fast and accurate titrations. The term used for this process is “Digital movie-based on automatic titrations” (DMB-AT). A webcam records the DM during the addition of the titrant to the mixing chamber (MC). While the DM is recorded, it is decompiled into frames ordered sequentially at a constant rate of 26 frames per second (FPS). The first frame is used as a reference to define the region of interest (ROI) of 28×13 pixels and the R , G and B values, which are used to calculate the Hue ( H ) values for each frame. The Pearson's correlation coefficient ( r ) is calculated between the H values of the initial frame and each subsequent frame. The titration curves are plotted in real time using the r values and the opening time of the titrant valve. The end point is estimated by the second derivative method. A software written in C language manages all analytical steps and data treatment in real time. The feasibility of the method was attested by application in acid/base test samples and edible oils. Results were compared with classical titration and did not present statistically significant differences when the paired t -test at the 95% confidence level was applied. The proposed method is able to process about 117–128 samples per hour for the test and edible oil samples, respectively, and its precision was confirmed by overall relative standard deviation (RSD) values, always less than 1.0%.

The exploitation of digital images obtained from a CCD camera (WebCam) as a novel instrumental detection technique for titration is proposed for the first time. Named of digital image-based (DIB) titration, it also requires, as a traditional titration (for example, spectrophotometric, potentiometric, conductimetric), a discontinuity in titration curves where there is an end point, which is associated to the chemical equivalence condition. The monitored signal in the DIB titration is a RGB-based value that is calculated, for each digital image, by using a proposed procedure based on the red, green, and blue colour system. The DIB titration was applied to determine HCl and H3PO4 in aqueous solutions and total alkalinity in mineral and tap waters. Its results were compared to the spectrophotometric (SPEC) titration and, by applying the paired t-test, no statistic difference between the results of both methods was verified at the 95% confidence level. Identical standard deviations were obtained by both titrations in the determinations of HCl and H3PO4, with a slightly better precision for DIB titration in the determinations of total alkalinity. The DIB titration shows to be an efficient and promising tool for quantitative chemical analysis and, as it employs an inexpensive device (WebCam) as analytical detector, it offers an economically viable alternative to titrations that need instrumental detection.

Near-infrared (NIR) spectrometry and chemometric methods of classification were used to classify and verify adulteration of 69 samples of alcoholic beverages (whiskey, brandy, rum and vodka). The characterization of the drinks was accomplished by chemometric models based on principal component analysis and soft independent modelling of class analogy elaborated for each different group. Alcoholic beverages adulterated with 5% and 10% (v/v) of water, ethanol or methanol were analyzed and used to verify the models capacity of prediction. Besides, actual samples with suspicions of adulteration were analyzed by gas chromatography and used to test the chemometric models which were able to predict the adulteration in the actual samples. The proposed method was successfully applied in the verification of alcoholic beverages adulteration with 100% of correct prediction at 95% of confidence level. The absence of reagents, low sample consumption, high sampling throughput and good predictive ability enables the developed methodology to be applied as a screening analysis to verify adulteration of the alcoholic beverage, that is, a prior step used to condition the sample to a deeper analysis only when a positive result for adulteration is obtained by the proposed method.

A novel strategy to evaluation of adulteration in alcoholic beverages based on the measurement of the Schlieren effect using an automated FIA system with photometric detection is proposed. The assay is based on the Schlieren effect produced when beverage samples are injected in a single-line FIA system that uses water as carrier stream and a light-emitting diode–phototransistor photometer controlled by microcomputer as detector. The flow system presents limited mixing conditions which make possible to create gradients of refractive index (Schlieren effect) in the injected sample zone. These gradients are reproducible, characteristic of each alcoholic beverage and undergo specific modifications when adulterations with water or ethanol are imposed. Schlieren effect data of brandies, cachacas, rums, whiskies and vodkas were treated by SIMCA to elaborate class models applied in the evaluation of alcoholic beverages adulteration. Samples of the original matrix of each sort of beverages were adulterated in laboratory by adding water, methanol and ethanol in levels of 5% and 10% (v/v). These samples were used as test set to validate SIMCA class models. The verification of authenticity using Schlieren effect measurements presented good results making possible to identify 100% of the beverages samples adulterated in laboratory and 93% of the actual adulterated alcoholic beverages with confidence levels of 95%. As principal advantage, the automated system does not use reagents to carry out the analysis.

A novel strategy for implementing the automatic standard addition method (SAM) is described. By using a flow–batch system that presents the intrinsic favourable characteristics of the flow and batch techniques, the proposed strategy performs fast standard additions with sufficient flexibility and versatility and employs only one standard solution per analyte. To calculate the analyte concentration, a mathematical model based on a classical SAM and flow variables of the system was developed. The proposed flow–batch SAM was applied to copper determination by flame atomic absorption spectrometry (AAS) in sugar cane-made alcoholic beverages, known as “Cachaca”, available in Brazil. A SAM has been recommended for these analyses because “Cachacas” presents a significantly different composition causing matrix effects and copper determination by calibration using matrix-matching standards can yield inaccurate results. The results show good agreement between the obtained values with the proposed flow–batch SAM and a manual SAM. The mean relative errors and overall standard deviations were always

Density functional theory (DFT) was used to examine the interaction between molecular oxygen (O2) and macrocyclic iron complexes of the type FeN4 during the formation of FeN4–O2 adducts. In order to understand how this interaction is affected by different macrocyclic ligands, O2 was bonded to iron-tetraaza[14]annulene (FeTAA), iron-tetramethyl-tetraaza[14]annulene (FeTMTAA), iron-hexamethyl-tetraaza[14]annulene (FeHMTAA), iron dibenzotetraaza[14]annulene (FeDBTAA), and two iron-tetramethyl-dibenzotetraaza[14]annulene complexes (FeTMDBTAA1, FeTMDBTAA2). The ground state for FeN4-O2 adducts was the open-shell singlet. Analysis of the factors influencing the O2 bonding process showed that different macrocyclic ligands yielded adducts with differences in O-O and Fe-O2 bond lengths, total charge over the O2 fragment, O-O vibrational frequency, and spin density in the O2 fragment. A smaller energy gap between the α-HOMO of the FeN4 complexes and the β-LUMO of O2 increased the interaction between the complex and the O2 molecule. The order of activity was FeDBTAA

In this work, a micro-flow-batch analyzer (µFBA) using webcam for spectrophotometric determination of ortho-phosphate and aluminium(III) in tap water is proposed. PO43- and Al3+ determinations were performed by employing molybdenum blue and quecertin methods, respectively. In order to build linear analytical curves, a mathematical model was used on the basis of the RGB (red, green and blue) values. Working ranges were from 25 to 500 µg L-1 for both analytes with estimated limits of detection, relative standard deviation (RSD, n = 5) and sampling rate of 0.82 µg L-1, < 0.8% and 160 h-1 for PO43-, and 0.93 µg L-1, < 1.1% and 160 h-1 for Al(III). Comparing with the reference methods, no statistically significant differences were observed when applying the paired t-test at a 95% confidence level. Recovery study shows results between 98.1 and 102.8%. The proposed µFBA presented satisfactory portability, robustness, flexibility, low-cost device and reduced chemicals consumption.

1 and < 1.4% (n = 5), respectively. The accuracy was assessed through recovery test (98.5 to 102.8%).The ruggedness of the method was assessed by comparison of the intra- and inter-day using the iodometric titration method at a 95% confidence level. The system presented satisfactory robustness, high sampling rate (153 h -1 ), and reduced chemical consumption.

In this study, a micro-flow-batch analyzer (μFBA) with solenoid micro-pumps for the photometric determination of iodate in table salt is described. The method is based on the reaction of iodate with iodide to form molecular iodine followed by the reaction with N,N-diethyl-p-phenylenediamine (DPD). The analytical signal was measured at 520 nm using a green LED integrated into the μFBA built in the urethane-acrylate resin. The analytical curve for iodate was linear in the range of 0.01-10.0 mg L(-1) with a correlation coefficient of 0.997. The limit of detection and relative standard deviation were estimated at 0.004 mg L(-1) and

This work introduces the monosegmented flow-batch (MSFB) analysis concept. This system combines favourable characteristics of both flow-batch and the monosegmented analysers, allowing use of the flow-batch system for slow reaction kinetics without impairing sensitivity or sampling throughput. The MSFB was evaluated during spectrophotometric determination of boron in plant extracts, which is a method that involves a slow reaction between boron and azomethine-H. All calibration solutions were prepared in-line, and all analytical processes completed by simply changing the operational parameters in the MSFB control software. The limit of detection was estimated at 0.008 mg L−1. The measurements could be performed at a rate of 120 samples per hour with satisfactory precision. The proposed MSFB was successfully applied to analyse 10 plant samples and the results are in agreement with the reference method at a 95% level of confidence.

An automatic method for kinetics independent spectrometric analysis is proposed in this study. It uses a non-linear calibration model that explores concentration gradients generated by a flow-batch analyser (FBA) for the samples, dye, and the single standard solution. The procedure for obtaining the gradients of the dye and standard solution is performed once at the beginning of analysis. The same procedure is applied thereafter for each sample. For illustration, the proposed automatic methodology was applied to determine total protein and albumin in blood serum by using the Biuret and Bromocresol Green (BCG) methods. The measurements were made by using a laboratory-made photometer based on a red and green bicolour LED (Light-Emitting Diode) and a phototransistor, coupled to a "Z" form flow cell. The sample throughput was about 50 h(-1) for albumin and 60 h(-1) for total protein, consuming about 7 microL of sample, 2.6 mL of BCG and 1.2 mL of biuret reagents for each determination. Applying the paired t-test for results from the proposed analyser and the reference method, no statistic differences at 95% confidence level were found. The absolute standard deviation was usually smaller than 0.2 g dL(-1). The proposed method is valuable for the determination of total protein and albumin; and can also be used in other determinations where kinetic effects may or may not exist.

A digital image-based flame emission spectrometric (DIB-FES) method for the quantitative chemical analysis is proposed here for the first time. The DIB-FES method employs a webcam to capture the digital images which are associated to a radiation emitted by the analyte into an air-butane flame. Since the detection by webcam is based on the RGB (red-green-blue) colour system, a novel mathematical model was developed in order to build DIB-FES analytical curves and estimate figures of merit for the proposed method. In this approach, each image is retrieved in the three R, G and B individual components and their values were used to define a position vector in RGB three-dimensional space. The norm of this vector is then adopted as the RGB-based value (analytical response) and it has revealed to be linearly related to the analyte concentration. The feasibility of the DIB-FES method is illustrated in three applications involving the determination of lithium, sodium and calcium in anti-depressive drug, physiological serum and water, respectively. In comparison with the traditional flame emission spectrometry (trad-FES), no statistic difference has been observed between the results by applying the paired t-test at the 95% confidence level. However, the DIB-FES method has offered the largest sensitivities and precision, as well as the smallest limits of detection and quantification for the three analytes. These advantageous characteristics are attributed to the trivariate nature of the detection by webcam.

The study proposes a low cost and very simple quantitative spot test technique for determination of soluble tannin in green tea samples using a portable diffuse reflectometer. The lab-made instrument was made of polytetrafluoroethylene (PTFE), using a light emitting diode (LED) for its light source, and a phototransistor as the detector. The proposed method measured diffuse reflectance from a complex formed by reaction between soluble tannin and ferrous tartrate in a buffered medium at pH 6.8. The spot test is a reliable and advantageous alternative technique because it uses fewer chemicals than the reference method. The study obtained good limits of detection (0.11 mg L−1), and precision (RSD = 0.9%), and at a 95% confidence level (paired t-test) no statistically significant difference between the results of either method was found.