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Microplastic pollution is a global concern theme, and there is still the need for less laborious and faster analytical methods aiming at microplastics detection. This article describes a high throughput screening method based on near-infrared hyperspectral imaging (HSI-NIR) to identify microplastics in beach sand automatically with minimum sample preparation. The method operates directly in the entire sample or on its retained fraction (150 μm-5 mm) after sieving. Small colorless microplastics (<600 μm) that would probably be imperceptible as a microplastic by visual inspection, or missed during manual pick up, can be easily detected. No spectroscopic subsampling was performed due to the high-speed analysis of line-scan instrumentation, allowing multiple microplastics to be assessed simultaneously (video available). This characteristic is an advantage over conventional infrared (IR) spectrometers. A 75 cm 2 scan area was probed in less than 1 min at a pixel size of 156 × 156 μm. An in-house comprehensive spectral dataset, including weathered microplastics, was used to build multivariate supervised soft independent modelling of class analogy (SIMCA) classification models. The chemometric models were validated for hundreds of microplastics (primary and secondary) collected in the environment. The effect of particle size, color and weathering are discussed. Models' sensitivity and specificity for polyethylene (PE), polypropylene (PP), polyamide-6 (PA), polyethylene terephthalate (PET) and polystyrene (PS) were over 99% at the defined statistical threshold. The method was applied to a sand sample, identifying 803 particles without prior visual sorting, showing automatic identification was robust and reliable even for weathered microplastics analyzed together with other matrix constituents. The HSI-NIR-SIMCA described is also applicable for microplastics extracted from other matrices after sample preparation. The HSI-NIR principals were compared to other common techniques used to microplastic chemical characterization. The results show the potential to use HSI-NIR combined with classification models as a comprehensive microplastic-type characterization screening., (Copyright © 2021 Elsevier Ltd. All rights reserved.)

The use of near-infrared spectroscopy (NIRS) based on a low-cost portable instrument for monitoring the quality of the three major formulations of ethanol-based hand sanitizers used for prevention against CoVID-19 disease is described. The quality of the sanitizers was evaluated using two approaches. In the first, a qualitative method was developed to identify gross non-conformities, using NIR spectral data compression by principal components analysis and projection of the spectrum of the tested sample in the principal component space delimited by samples of sanitizers prepared in the laboratory. In the second, a quantitative method was designed to determine the active substance (ethanol) employing multivariate regression based on partial least squares. The results demonstrate that the first approach can be used to detect non-conformities in the sanitizer composition, mostly associated with incorrect ethanol content. The second explores the use of NIRS for determination of the ethanol content in the three formulations aiming the quality control of the sanitizer manufacturing process. The ethanol content can be determined with an absolute root mean square error of prediction (RMSEP) equal to 0.68% (m/m), 0.83% (m/m) and 1.0% (v/v) for the three formulations evaluated. The RMSEP was estimated as 1.3% (m/m) for the commercial products. The measurement protocol takes approximately 1 min and requires only about 120 µL of a sample. Besides, NIRS was employed to compare the rate of volatilization of the ethanol in the different formulations, an important parameter concerning the efficacy of ethanol-based sanitizers., Competing Interests: The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (© 2020 Elsevier B.V. All rights reserved.)

A quantitative analytical method based on laser ablation molecular isotopic spectrometry (LAMIS) and multivariate analysis was developed and evaluated for the determination of the isotopic composition of enriched materials. The method consists preparing a concentrated solution of the enriched material, using small quantities of a sample (125 mg), and ensuring the economic efficiency of the analysis. Standard solutions of known isotopic contents are prepared by employing mixtures of urea highly enriched in 15 N and urea of natural isotopic ratio and analyzed by mass spectrometry. A small volume (30 μL) of these solutions is delivered to a filter paper disc (3 cm diameter). After drying, the disc, offering a homogeneously distributed analyte, is presented to a LAMIS equipment to acquire the vibronic emission spectra containing information about the isotopologues of interest. To illustrate the proposed method, the content of 15 N is determined in enriched samples of urea. In this case, each spectrum is normalized by the intensity of emission of the CN isotopologues for the electronic (Δν = 0) emission band at 387.1 nm, ensuring better accuracy. Selected regions and single wavelengths of the vibronic emission spectrum (Δν = + 1 or - 1) related to CN species were employed to construct multivariate partial least squares (PLS) and univariate regression models to predict the isotopic content of new samples. Besides, the LAMIS data set was evaluated by multivariate curve resolution (MCR) algorithm. The best MCR and PLS models presented similar results regarding the accuracy to determine 15 N content in enriched urea. MCR is capable of identifying spectral interferences and minimizing its effect. The results show that the proposed method based on LAMIS and PLS or MCR multivariate analysis can determine the 15 N content in the range 5-50% with a root mean square error of prediction (RMSEP) respectively equal to 0.5 or 0.7% (m/m) in comparison with reference results obtained by mass spectrometry. Graphical abstract.

The potential of a low-cost (∼US$ 1000) portable near-infrared (NIR) spectrophotometer for in situ characterization of seized cocaine samples was evaluated. A set of 240 samples of cocaine seized in several regions and cities across Brazil by its federal police was employed in this study. These samples were previously analyzed by chromatography at the Forensic Chemistry Laboratory of the National Institute of Criminalistics in Brasília-DF for the contents of several constituents to chemically characterize the samples. A low-cost NanoNIR spectrophotometer (Texas instruments) was used to acquire the NIR spectra of the samples in the range 900-1700 nm. The spectra set was treated by the second derivative to construct and validate multivariate regression (Partial Least Square - PLS) and classification (software independent modeling of class analogy - SIMCA) models aiming to characterize the samples. Consequently, an informative toll for objective decision making could be used by the police agents to produce immediate answers to forensic questions raised at the point of seizing. Among those questions the most relevant are: does the seized sample contain cocaine? what is the cocaine form? what is its content? is the sample adulterated and/or diluted? what is the content of adulterant? is the sample significantly adulterated and/or diluted? what is the degree of oxidation of the cocaine? The results of this work allow to propose a NIR/chemometrics based analytical protocol providing fast answers to these questions with satisfactory confidence level for the purpose of reliably screen the seized samples., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Laser-induced breakdown spectroscopy (LIBS) is an appealing analytical technique for simultaneous multi-elemental analysis. Near-infrared spectroscopy (NIRS) has also been suggested for the same purpose, mainly for vegetable samples. However, LIBS has failed to provide adequate results in many cases due to sample matrix complexity, and NIRS performance is harmed because of its lack of sensitivity and indirect correlation with inorganic elemental species. In this work, the performance of these two techniques are compared for the determination of micro- and macroelements in vegetable samples (Brachiaria forages) using multivariate regression. In addition, a data fusion scheme, in which spectral data sourced by NIRS is integrated with LIBS, is proposed to improve elemental content determination in those samples. The information of the molecular composition detected by NIR vibrational spectroscopy was consistently selected by recursive partial least squares to yield quantitative multivariate models for K, Ca, Mg, Mn and Fe in forage plants that are superior to models based on the use of individual NIRS and LIBS spectral information. While all data fusion models showed better predictive accuracy than any of the two individual techniques, best results were observed for Ca. This suggests that matrix composition affects each element determination by LIBS distinctively and supports the idea that a successful quantitative data fusion strategy for LIBS requires a technique such as NIRS which is sensitive to this variability., (Copyright © 2019 Elsevier B.V. All rights reserved.)

Last decade's advances and modern aspects of near infrared spectroscopy are critically examined and reviewed. Innovative instrumentation, highlighted by portable and imaging instruments, chemometrics data multivariate processing, and new and valuable applications are presented and discussed. Because of these advances, this mature analytical technique is continually experiencing renewed interest. The drawbacks and misuses of the technique and its supporting mathematical tools are also addressed. The principal achievements in the field are shown in a critical manner, in order to understand why the technique has found intensive application in the most diverse and modern areas of analytical importance during the last ten years., (Copyright © 2018 Elsevier B.V. All rights reserved.)

Near infrared emission spectroscopy (NIRES) has been investigated to yield a new analytical method for determination of CaO, SiO 2 , Al 2 O 3 , Fe 2 O 3 , MgO, and SO 3 in Portland cement samples. The analyses were accomplished by correlation of the second derivative NIRES spectra with reference elemental analyses made by X-ray Fluorescence (XRF), using Partial Least Square (PLS) regression models. Four different types of cements (type II, III, IV and V) were included in the models. The results show RMSEP from 0.18 to 1.67% (m/m) (which represents 8.6 to 2.8% of the mean value parameters, respectively) and precision (repeatability) from 0.12 to 1.49% (m/m). The worse performance of prediction [RMSEP = 0.18% (m/m), r 2  = 0.63] was found for Fe 2 O 3 determination due its low variability in the samples employed in the calibration and validation set, usual low content in cements, and high correlation with the weak emitting C 4 AF phase. However, the paired t-test at 95% confidence level demonstrated that the analytical results obtained by NIRES multivariate models are equivalent to measurements performed by XRF for all oxides analyzed. The cost, speed and safety aspects are improved in comparison with the XRF method. The method based on NIRES requires no sample preparation and speed up the cement analysis (6 min) about 5 times when compared with the method based on XRF presently employed by cement industries., (Copyright © 2018 Elsevier B.V. All rights reserved.)

In this paper, we present the advantages and limitations of the coupling of a ring-oven-based preconcentration technique and surface-enhanced Raman spectroscopy (SERS). Three different methods to promote analyte adsorption on gold nanoparticles using crystal violet as a probe molecule were assessed. The results showed significant improvements in sampling process, selectivity, sensitivity, repeatability (less than ± 10%), and detection limits (nanomolar level) using a sample volume as small as 300 μL. Finally, the standard addition method was successfully applied to the quantitative SERS detection of adenine and guanine in calf thymus DNA after ring-oven preconcentration with a calculated value of (G + C)/(A + T) close to the literature value. This work could therefore pave the way to quantifying a wide variety of biologically relevant compounds in real-world samples via the use of a biodegradable, low-cost and disposable paper platform for SERS., (Copyright © 2017 Elsevier B.V. All rights reserved.)

Near infrared emission spectroscopy (NIRES) allows the determination of the induction time (IT) of edible oils in accelerated oxidation experiments by monitoring the emissivity of a band at 2900 nm, which corresponds to the formation of hydroperoxides. In this work, a new near infrared emission photometer dedicated to the determination of oxidative stability is described. The photometer presents several advantages compared to the previously reported NIRES instrument, such as lower cost and extreme simplicity of design and maintenance. The results obtained in the evaluation of the proposed instrument were compared with the official Rancimat method and instrument. The significant advantages include: faster analysis, lower sample consumption and operational simplicity. It is demonstrated that the procedure for determination of oxidative stability of oils can be significantly simplified and performed by measuring the sample emission at only one spectral region centered at 2900 nm. Also, the proposed instrument and method present precision equivalent to the Rancimat method (coefficient of variation=5.0%). A significant correlation between the methods has been found (R(2)=0.81)., (Copyright © 2013 Elsevier B.V. All rights reserved.)

A low cost absorption spectrophotometer for the short wave near infrared spectral region (850-1050 nm) is described. The spectrophotometer is basically composed of a conventional dichroic lamp, a long-pass filter, a sample cell and a Czerny-Turner type polychromator coupled to a 1024 pixel non-cooled photodiode array. A preliminary evaluation of the spectrophotometer showed good repeatability of the first derivative of the spectra at a constant room temperature and the possibility of assigning some spectral regions to different C-H stretching third overtones. Finally, the spectrophotometer was successfully applied for the analysis of diesel samples and the determination of some of their quality parameters using partial least squares calibration models. The values found for the root mean square error of prediction using external validation were 0.5 for the cetane index and from 2.5 to 5.0 degrees C for the temperatures achieved during distillation when obtaining 10, 50, 85, and 90% (v/v) of the distilled sample, respectively., (2010 Elsevier B.V. All rights reserved.)

A flow-batch system was constructed and evaluated to perform coulometric titrations with biamperometric end point detection. The flow section of the system is employed for sampling by injecting a sample volume (50-300 microL) in a flow injection-like system. About 1.5 mL of a suitable carrier solution is delivered by a peristaltic pump in order to quantitatively transfer the sample to the system titration cell (2.0 mL total inner volume). The carrier contains the coulometric precursor for the titrant species. The cell contains two pairs of platinum electrodes used for coulometric generation of reagent and biamperometric detection and is actively stirred. The titrant species is generated and the titration is performed by the usual batch procedure with the excess of titrant being detected by biamperometry following the analysis of the titration curve. System operation is computer controlled and all operations are automated, including titration curve analysis and cell cleaning after the titration is ended. The system is characterized by its robustness because its operation does not depend on flow rates, and the work using coulometric methods which generate gases at the counter-electrode is not troublesome. The flow-batch system has been evaluated for determination of bromine index and bromine number (relative to the total reactive olefin content) in petrochemicals according to an ASTM procedure. Typical precision (R.S.D.) is between 0.5 and 6% for different petrochemicals whose bromine number/index vary from 1000 to 10mg of bromine per 100g of sample, respectively. Recoveries for standard additions are between 92 and 123% for 10mg of Br(2) per 100g increments and 98 to 101% for 100mg per 100g increments. Accuracy of the proposed system was evaluated against results obtained by the standard ASTM with no significant difference detected at 95% confidence level.

Monosegmented flow analysis (MSFA) has been used as a flow-batch system to produce a simple, robust, and mechanized titrator that enables true titrations to be performed without the use of standards. This paper also introduces the use of coulometry with monosegmented titration by proposing a versatile flow cell. Coulometric generation of the titrand is attractive for titrations performed in monosegmented systems, because the reagent can be added without increasing the volume of sample injected. Also, biamperomeric and potentiometric detection of titration end-points can increase the versatility of the monosegmented titrator. The cell integrates coulometric generation of the titrand with detection of end-point by potentiometry or biamperometry. The resulting titrator is a flow-batch system in which the liquid monosegment, constrained by the interfaces of the gaseous carrier stream, plays the role of a sample of known volume to be titrated. The system has been used for determination of ascorbic acid, by coulometric generation of I2 with biamperometric detection, and for determination of Fe(II), by coulometric generation of Ce(IV) with potentiometric detection of the end-point, both in feed supplements.

A spectrometer has been constructed to detect the radiation emitted by thermally excited samples in the near-infrared spectral region extending from 1500 to 3000 nm. The instrument employs an acousto-optical tunable filter (AOTF) made of TeO2 and attains maximum sensitivity by making effective use of the two diffracted beams produced by the anisotropic AOTF. The full exploitation of the transmitted power of the monochromatic beams is reported for the first time and became possible because the detector does not saturate when employed for the acquisition of the weak emission signal in the NIR region, even when exposed to the total (nondiffracted) beam. Thus, modulation and lock-in-based detection can be employed to find the intensity of the diffracted beams superimposed on the nondiffracted beam. The resolution is slighted degraded in view of the small (approximately 10 nm) difference in the wavelength diffracted in the ordinary and extraordinary beams. The instrument has been evaluated in terms of signal-to-noise ratio, effect of sample thickness, and excitation temperature and for its potential in analytical applications in monitoring high-temperature kinetics, for qualitative identification of inorganic solids, for use with a closed cell to obtain spectra of species that evaporate at the temperatures (> 150 degrees C) necessary for sample excitation, and for quantitative purposes in the determination of soybean oil content in olive oil. The feasibility of near-infrared emission spectroscopy has been demonstrated together with some of its advantages over mid-infrared emission spectroscopy, such as greater tolerance to sample thickness, suitable signal-to-noise, and its use in the investigation of kinetic phenomena and phase transitions at high temperatures.

The use of silicone for detection of aromatic hydrocarbons in water using near-infrared spectroscopy is proposed. A sensing phase of poly(dimethylsiloxane) (PDMS) was prepared, and a rod of this material was adapted to a transflectance probe for measurements from 850 to 1800 nm. Deionized water samples contaminated separately with known amounts of benzene, toluene, ethylbenzene, and m-xylene were used for evaluation of the PDMS sensing phase, and measurements were made in a closed reactor with constant stirring. Equilibrium states were obtained after 90, 180, 360, and 405 min for benzene, toluene, ethylbenzene, and m-xylene, respectively. The PDMS sensing phase showed a reversible response, presenting linear response ranges up to 360, 290, 100, and 80 mg L(-1), with detection limits of 8.0, 7.0, 2.6, and 3.0 mg L(-1) for benzene, toluene, ethylbenzene, and m-xylene, respectively. Reference spectra obtained with different rods showed a relative standard deviation of 0.5%, indicating repeatability in the sensing phase preparation. A relative standard deviation of 6.7% was obtained for measurements performed with six different rods, using a 52 mg L(-1) toluene aqueous solution. The sensing phase was evaluated for identification of sources of contamination of water in simulated studies, employing Brazilian gasoline type A (without ethanol), gasoline type C (with 25% of anhydrous ethanol), and diesel fuel. Principal component analysis was able to classify the water in distinct groups, contaminated by gasoline A, gasoline C, or diesel fuel.

A simple device is described to couple a fast-scanning acoustooptic tunable filter-based NIR spectrophotometer to a distillation apparatus for monitoring the condensed vapor in real time. The device consists of a small funnel whose glass neck (2-mm diameter) is bent into an "U" format to produce a flow cell of approximately 150-microL inner volume. A pair of optical fibers is used to deliver the monochromatic light and to collect the fraction passing through the glass tube. The end of the condenser of the distillation head touches the wall of the small funnel. The condensed liquid flows uncoupled from pressure changes in the interior of the distillation head. Absorbance spectra were obtained, during the distillation, as averages of 50 scans (4 s) every 5 s in the spectral range 950-1800 nm with nominal resolution of 2.0 nm. In the first experiments, the distillations were performed at constant power supplied to the sample (25 mL) in a microdistillation apparatus working without any type of reflux column. The usefulness of the real-time monitoring of distillation is demonstrated using some prepared binary mixtures and by comparing the distillation behavior of adulterated and regular gasoline samples. Data analysis and interpretation are facilitated by employing principal component analysis. The system accesses the composition of the condensate, which can separate and concentrate one or more compounds present in the original sample.