Sensing and extraction of hazardous metals by di-phosphonates of heterocycles: a combined experimental and theoretical study.

In this study, pyridine and phenanthroline diphosphonate ligands were investigated for the first time from the context of solvent extraction and potentiometric sensing of Co(II), Ni(II), Cu(II), Zn(II), Cd(II), and Pb(II) cations. The extraction efficiency under the same conditions for phenanthroline-diphosphonates is considerably higher than that for pyridine ligands. At the same time, the pyridine-diphosphonates show pronounced selectivity towards lead in this metal series. The extraction systems with phenanthroline diphosphonates provided the most efficient extraction of Cd(II) and Pb(II) cations (D > 90). The newly developed pyridine and phenanthroline diphosphonate ligands have proven to be highly effective components in plasticized polymeric membranes. These ligands can be utilized to construct potentiometric ion sensors that exhibit a notable response specifically towards Pb(II) cations. Among the previously reported tetradentate ligands, the phenanthroline diphosphonate ligand, when incorporated into plasticized polymeric membranes, demonstrated the highest sensitivity towards d-metals and Pb(II). The structure of the single crystal complex of Pb(II) and Cd(II) with pyridine-diphosphonates was studied by X-ray diffraction analysis (XRD). The geometry of Cu(II), Zn(II), Cd(II) and Pb(II) complexes and the energy effect of the complex formation, including pseudo-oligomerization reactions, were determined by DFT calculations. The high sensing and extraction efficiency of diphosphonates with respect to Pb(II) is consistent with the minimum values of complex formation energies. The variation in sensory and extraction properties observed among the studied diphosphonate ligands is influenced by the ability to form polynuclear complexes with Pb(II) cations, whereas such properties are absent in the case of Cd(II) cations.

Combination of Total-Reflection X-Ray Fluorescence Method and Chemometric Techniques for Provenance Study of Archaeological Ceramics.

The provenance study of archaeological materials is an important step in understanding the cultural and economic life of ancient human communities. One of the most popular approaches in provenance studies is to obtain the chemical composition of material and process it with chemometric methods. In this paper, we describe a combination of the total-reflection X-ray fluorescence (TXRF) method and chemometric techniques (PCA, k-means cluster analysis, and SVM) to study Neolithic ceramic samples from eastern Siberia (Baikal region). A database of ceramic samples was created and included 10 elements/indicators for classification by geographical origin and ornamentation type. This study shows that PCA cannot be used as the primary method for provenance purposes, but can show some patterns in the data. SVM and k-means cluster analysis classified most of the ceramic samples by archaeological site and type with high accuracy. The application of chemometric techniques also showed the similarity of some samples found at sites located close to each other. A database created and processed by SVM or k-means cluster analysis methods can be supplemented with new samples and automatically classified.

Quantification of elements in spent nuclear fuel using intrinsic radioactivity for sample excitation and chemometric data processing.

Quantitative analysis of spent nuclear fuel (SNF) is a very challenging task. High radioactivity, complex chemical composition and personnel safety requirements severely limit the number of analytical tools suitable for this problem. There is an urgent need for the methods that would provide for remote on-line quantification of elements in spent nuclear fuel and its reprocessing technological solutions. Here we propose a novel approach based on the registration of X-ray fluorescence radiation from SNF samples induced by fission products radioactivity. In this case the X-ray excitation conditions will obviously vary from sample to sample; moreover the resulting spectra will be a complex superposition of numerous signals from soft gamma emitters and X-ray fluorescence of various nature. These complex spectra can be effectively treated with chemometric data processing for quantification of particular elements. We have demonstrated the validity of this approach for direct analysis of U, Zr and Mo in SNF raffinate.

Predicting the Potentiometric Sensitivity of Membrane Sensors Based on Modified Diphenylphosphoryl Acetamide Ionophores with QSPR Modeling.

While potentiometric, plasticized membrane sensors are known as convenient, portable and inexpensive analytical instruments, their development is time- and resource-consuming, with a poorly predictable outcome. In this study, we investigated the applicability of the QSPR (quantitative structure-property relationship) method for predicting the potentiometric sensitivity of plasticized polymeric membrane sensors, using the ionophore chemical structure as model input. The QSPR model was based on the literature data on sensitivity, from previously studied, structurally similar ionophores, and it has shown reasonably good metrics in relating ionophore structures to their sensitivities towards Cu2+, Cd2+ and Pb2+. The model predictions for four newly synthesized diphenylphosphoryl acetamide ionophores were compared with real potentiometric experimental data for these ionophores, and satisfactory agreement was observed, implying the validity of the proposed approach.

A Simple Contactless High-Frequency Electromagnetic Sensor: Proof of Concept.

We report on the development of a very simple and inexpensive sensor device based on an inductance coil connected to a high-frequency electric field generator. The working principle of this sensor is as follows: liquid sample in a plastic tube is placed inside the inductance coil as its core and this core changes the properties of high-frequency electric current passing through the coil; these changes depend on sample conductivity, dielectric constant, magnetic properties, and capacitance. The electric signal registered after the coil represents a kind of a spectrum that can be effectively treated with chemometric tools. Our studies have shown that such a sensor can be used to distinguish between substances with different physical and chemical properties; different concentrations of ions in aqueous solutions with a linear response in a broad concentration range from 10-3 M to 10-1 M; can quantify the fat content in milk and cream samples with about 2% accuracy; and can distinguish between bacterial cultures and cell line cultures. The measurements are very fast and contactless, and the results show good promise for developing a number of applications of this sensor system.

Quantification of phosphatides in sunflower oils using a potentiometric e-tongue.

Consisting of two fatty acyl groups, phospholipids are a vital part of vegetable oils and the source of essential fatty acids. Moreover, phospholipids influence oxidative and flavor stability and color evolution of vegetable oils, and their quantification has a significant role in the quality assessment of oils. In this study, we proposed a new highly efficient, affordable, environmentally friendly, and simple approach for the evaluation of phospholipid concentrations based on potentiometric multisensor systems coupled with chemometric data processing. Support vector machines, partial least squares, and multiple linear regressions were used to predict phosphatide concentrations based on potentiometric multisensor system responses. Application of multivariate regression tools yielded the following root mean square errors of prediction: 0.005 mg/100 g of oil in the range 0.0-59.4 mg/100 g for refined oils; 0.008 mg/100 g in the range 0.0-100 mg/100 g for low phosphatide oils and 0.24 mg/100 g in the range 100-2270 mg/100 g for high phosphatide oils. This approach can be considered as a rapid and straightforward method to quantify the phosphatides in sunflower oils.

Sensitivity and generalized analytical sensitivity expressions for quantitative analysis using convolutional neural networks.

In recent years, convolutional neural networks and deep neural networks have been used extensively in various fields of analytical chemistry. The use of these models for calibration tasks has been highly effective; however, few reports have been published on their properties and characteristics of analytical figures of merit. Currently, most performance measures for these types of networks only incorporate some function of prediction error. While useful, these measures are incomplete and cannot be used as an objective comparison among different models. In this report, a new method for calculating the sensitivity of any type of neural network is proposed and studied on both simulated and real datasets. Generalized analytical sensitivity is defined and calculated for neural networks as an additional figure of merit. Moreover, the dependence of convolutional neural networks on regularization dataset size is studied and compared with other conventional calibration methods.

Development of QDs-based nanosensors for heavy metal detection: A review on transducer principles and in-situ detection.

Heavy metal pollution has severe threats to the ecological environment and human health. Thus, it is urgent to achieve the rapid, selective, sensitive and portable detection of heavy metal ions. To overcome the defects of traditional methods such as time-consuming, low sensitivity, high cost and complicated operation, QDs (Quantum dots)-based nanomaterials have been used in sensors to significantly improve the sensing performance. Due to their excellent physicochemical properties, high specific surface area, high adsorption and reactive capacity, nanomaterials could act as potential probes or offer enhanced sensitivity and create a promising nanosensors platform. In this review, the rapidly advancing types of QDs for heavy metal ions detection are first summarized. Modified with ligands, nanomaterials, or biomaterials, QDs are assembled on sensors by the interaction of electrostatic adsorption, chemical bonding, steric hindrance, and base-pairing. The stability of QDs-based nanosensors is improved by doping the elements to QDs, providing the reference substance, optimizing the assemble strategies and so on. Then, according to transducer principles, the two most typical sensor categories based on QDs: optical and electrochemical sensors are highlighted to be discussed. In the meanwhile, portable devices combining with QDs to adapt the practical detection in complex situations are summarized. The deficiencies and future challenges of QDs in toxicity, specificity, portability, multi-metal co-detection and degradation during the detection are also pointed out. In the end, the development trends of QDs-based nanosensors for heavy metal ions detection are discussed. This review presents an overall understanding, recent advances, current challenges and future outlook of QDs-based nanosensors for heavy metal detection.

A multi-channel handheld automatic spectrometer for wide range and on-site detection of okadaic acid based on specific aptamer binding.

Okadaic acid (OA) is one of the marine toxins that are widely distributed and harmful to humans. However, the current detection methods for OA involve complex procedures, need long detection time, and rely on large-scale laboratory equipment. In this work, a multi-channel handheld automatic spectrometer (MHAS) based on a spectral sensor was developed with the advantages of small size, simple operation and low cost. It could achieve rapid detection within 30 s and a wide spectral detection range of 470-780 nm with a broadband LED as the light source and a microplate containing 8 wells as a sample cell. Moreover, through the combination of gold nanoparticles (AuNPs) and aptamer-OA34, a highly sensitive and rapid system for OA detection was established with a LOD of 1.80 µg L-1 and a wide detection range of 20-10 000 µg L-1, which is comparable to a microplate reader. Compared with other studies, the proposed MHAS realized rapid on-site detection of OA with a wider detection range, shorter detection time and higher portability. Therefore, the MHAS promises to be a stable and efficient optical detection instrument for on-site detection in the fields of food safety, disease diagnosis and environmental monitoring.

Multiplexed all-solid-state ion-sensitive light-addressable potentiometric sensor (ISLAPS) system based on silicone-rubber for physiological ions detection.

Light-addressable potentiometric sensor (LAPS) has been widely used in biomedical applications since its advent. As a member of the potentiometric sensors, ion-sensitive LAPS (ISLAPS) can be obtained by modifying ion selective sensing membrane on the sensor surface. Compared with the conventional ion-selective electrodes (ISEs) with liquid contact, the all-solid-state ISEs have more advantages such as easy maintenance, more convenient for miniaturization and practical applications. However, the commonly used ion-sensitive membrane (ISM) matrix like PVC has many limitations such as poor adhesion to silicone-based sensor and easy overflow of the plasticizer from the membrane. In this work, LAPS was combined with a variety of ionophore-doped all-solid-state silicone-rubber ISMs for the first time, to establish a program-controlled multiplexed ISLAPS system for physiological ions (Na+, K+, Ca2+ and H+) detection. The silicone-rubber ISMs have better adhesion to silicon-based sensors without containing plasticizers, which can avoid the plasticizer pollution and improve the long-term stability. A layer of poly(3-octylthiophene-2,5-diyl) (P3OT) was pre-modified on the sensor surface to inhibit the formation of an aqueous layer and improve the sensor lifetime. With the aid of a translation stage, the light spot automatically illuminated the detection sites in sequence, and the response of the four ions could be obtained in one measurement within 1 min. The proposed multiplexed ISLAPS has good sensitivity with micromolar limit of detection (LOD), good selectivity and long-term stability (more than 3 months). The results of the real Dulbecco's Modified Eagle Medium (DMEM) sample detection proved that the ISLAPS system can be used for the physiological ions detection, and is promising to realize a multi-parameter microphysiometer.

Developing non-invasive bladder cancer screening methodology through potentiometric multisensor urine analysis.

We report on the feasibility study exploring the potential of a simple electrochemical multisensor system as a tool for distinguishing between urine samples from patients with confirmed bladder cancer (36 samples) and healthy volunteers (51 samples). The potentiometric sensor responses obtained in urine samples were employed as the input data for various machine learning classification algorithms (logistic regression, random forest, extreme gradient boosting classifier, support vector machine, and voting classifier). The performance metrics of the classifiers were evaluated via Monte-Carlo cross-validation. The best model combining all the acquired data from the people aged 19-88 with different tumor grades and malignancies, including patients with recurrent bladder cancer, yielded 72% accuracy, 71% sensitivity, and 58% specificity. It was found that these metrics can be improved to 76% accuracy, 80% sensitivity, and 75% specificity when only a limited age group (50-88 years of age) is considered. Taking into account the simplicity of the proposed screening method, this technique appears to be a promising tool for further research.

A Pencil-Drawn Electronic Tongue for Environmental Applications.

We report on the development of a simple and cost-effective potentiometric sensor array that is based on manual "drawing" on the polymeric support with the pencils composed of graphite and different types of zeolites. The sensor array demonstrates distinct sensitivity towards a variety of inorganic ions in aqueous media. This multisensor system has been successfully applied to quantitative analysis of 100 real-life surface waters sampled in Mahananda and Hooghly rivers in the West Bengal state (India). Partial least squares regression has been utilized to relate responses of the sensors to the values of different water quality parameters. It has been found that the developed sensor array, or electronic tongue, is capable of quantifying total hardness, total alkalinity, and calcium content in the samples, with the mean relative errors below 18%.

Application of Chemometrics in Biosensing: A Review.

The field of biosensing is rapidly developing, and the number of novel sensor architectures and different sensing elements is growing fast. One of the most important features of all biosensors is their very high selectivity stemming from the use of bioreceptor recognition elements. The typical calibration of a biosensor requires simple univariate regression to relate a response value with an analyte concentration. Nevertheless, dealing with complex real-world sample matrices may sometimes lead to undesired interference effects from various components. This is where chemometric tools can do a good job in extracting relevant information, improving selectivity, circumventing a non-linearity in a response. This brief review aims to discuss the motivation for the application of chemometric tools in biosensing and provide some examples of such applications from the recent literature.

Quality Control of Heparin Injections: Comparison of Four Established Methods.

Heparin is an anticoagulant medication that is usually injected subcutaneously. The quality of a set of commercial heparin injections from different producers was examined by NMR, IR, UV-Vis spectroscopies and potentiometric multisensor system. The type of raw material regarding heparin animal origin and producer, heparin molecular weight and activity values were derived based on the non-targeted analysis of 1H NMR fingerprints. DOSY NMR spectroscopy was additionally used to study homogeneity and additives profile. UV-Vis and IR, being cheaper than NMR, combined with multivariate statistics were successfully applied to study excipients composition as well as semi-estimation of activity values. Potentiometric multisensor measurements were found to be an important additional source of information about inorganic composition of finished heparin formulations. All investigated instrumental techniques are useful for finished heparin injections and should be selected according to availability as well as the information and confidence required for a specific sample.

Prostate cancer screening using chemometric processing of GC-MS profiles obtained in the headspace above urine samples.

The development of screening methods for various types of cancer is of utmost importance as the early diagnostics of these diseases significantly increases the chances for patient's successful medical treatment and recovery. In this study we have developed the procedure for chromatographic profiling of urine samples based on solid-phase microextraction and GC-MS. 50 urine samples (20 from the patients with biopsy conformed prostate cancer and 30 from control group) were studied in the optimized experimental conditions. Application of chemometric classification algorithms such as k-nearest neighbors and partial least squares-discriminant analysis allowed construction of predictive models yielding very high sensitivity, specificity and accuracy values all close to 100%. This gives a good promise for further validation of this approach with a broader sample sets.

Calibration Transfer for LED-Based Optical Multisensor Systems.

Multivariate calibration transfer is widely used to expand the applicability of the existing regression model to new analytical devices of the same or similar type. The present research proves the feasibility of calibration model transfer between a full-scale laboratory spectrometer and an optical multisensor system based on only four light-emitting diodes with different wavelengths. The model transfer between two multisensor systems of this kind has also been studied. Both possibilities were successfully performed without any significant loss of precision using a designed set of training and transfer samples. Direct standardization and slope and bias correction protocols for model transfer were tested and compared. The best model transfer between two optical multisensor systems was obtained using direct standardization.

Distinguishing paracetamol formulations: Comparison of potentiometric "Electronic Tongue" with established analytical techniques.

Fast and inexpensive analytical tools for identification of the origin of pharmaceutical formulations are important to ensure consumers safety. This study explores the potential of potentiometric multisensor systems ("electronic tongues") in this type of application. 72 paracetamol samples purchased in different countries and produced by various companies were studied via infrared spectroscopy (IR), near infrared spectroscopy (NIR), nuclear magnetic resonance spectroscopy (NMR) and multisensor system (ET). A variety of chemometric tools was applied to explore and compare the information yielded by these methods. It was found that ET is capable of distinguishing paracetamol formulations from different producers. The chemical information derived from potentiometric sensor responses has something in common with that derived from NIR and IR; however, it is orthogonal to that from NMR. ET can be a valuable tool in express quality assessment of drugs.

Real-Time Water Quality Monitoring with Chemical Sensors.

Water quality is one of the most critical indicators of environmental pollution and it affects all of us. Water contamination can be accidental or intentional and the consequences are drastic unless the appropriate measures are adopted on the spot. This review provides a critical assessment of the applicability of various technologies for real-time water quality monitoring, focusing on those that have been reportedly tested in real-life scenarios. Specifically, the performance of sensors based on molecularly imprinted polymers is evaluated in detail, also giving insights into their principle of operation, stability in real on-site applications and mass production options. Such characteristics as sensing range and limit of detection are given for the most promising systems, that were verified outside of laboratory conditions. Then, novel trends of using microwave spectroscopy and chemical materials integration for achieving a higher sensitivity to and selectivity of pollutants in water are described.

Plutonium (IV) Quantification in Technologically Relevant Media Using Potentiometric Sensor Array.

The quantification of plutonium in technological streams during spent nuclear fuel (SNF) reprocessing is an important practical task that has to be solved to ensure the safety of the process. Currently applied methods are tedious, time-consuming and can hardly be implemented in on-line mode. A fast and simple quantitative plutonium (IV) analysis using a potentiometric sensor array based on extracting agents is suggested in this study. The response of the set of specially designed PVC-plasticized membrane sensors can be related to plutonium content in solutions simulating real SNF-reprocessing media through multivariate regression modeling, providing 30% higher precision of plutonium quantification than optical spectroscopy.