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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.

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 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.

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.

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.

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