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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.

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%.