A review of nanocomposite-modified electrochemical sensors for water quality monitoring

Electrochemical sensors play a significant role in detecting chemical ions, molecules, and pathogens in water and other applications. These sensors are sensitive, portable, fast, inexpensive, and suitable for online and in-situ measurements compared to other methods. They can provide the detection for any compound that can undergo certain transformations within a potential window. It enables applications in multiple ion detection, mainly since these sensors are primarily non-specific. In this paper, we provide a survey of electrochemical sensors for the detection of water contaminants, i.e., pesticides, nitrate, nitrite, phosphorus, water hardeners, disinfectant, and other emergent contaminants (phenol, estrogen, gallic acid etc.). We focus on the influence of surface modification of the working electrodes by carbon nanomaterials, metallic nanostructures, imprinted polymers and evaluate the corresponding sensing performance. Especially for pesticides, which are challenging and need special care, we highlight biosensors, such as enzymatic sensors, immunobiosensor, aptasensors, and biomimetic sensors. We discuss the sensors’ overall performance, especially concerning real-sample performance and the capability for actual field application

Analysis of a Hybrid Micro-Electro-Mechanical Sensor Based on Graphene Oxide/Polyvinyl Alcohol for Humidity Measurements

In this paper, we present a redundant microsensor based on the bulk and etch silicon‑on‑insulator (BESOI) process for measuring relative humidity (RH), by using a graphene‑oxide/polyvinyl‑alcohol (GO/PVA) composite. The MEMS is a mechanical oscillator, composed of a proof mass with multilayer of nanomaterials (GO/PVA) and suspended by four crab-leg springs. The redundant approach realized concerns the use of different readout strategies in order to estimate the same measurand RH. This is an intriguing solution to realize a robust measurement system with multiple outputs, by using the GO/PVA as functional material. In the presence of RH variation, GO/PVA (1) changes its mass, and as consequence, a variation of the natural frequency of the integrated oscillator can be observed; and (2) varies its conductivity, which can be measured by using two integrated electrodes. The sensor was designed, analyzed and modeled; experimental results are reported here to demonstrate the effectiveness of our implementation

Hybrid Micro Electro Mechanical Sensor based onGraphene Oxide/Polyvinyl Alcohol for Humidity Measurements

In this paper, we present a redundant micromachined sensor based on Bulk and Etch. Silicon-on-Insulator (BESOI) process for measurements of relative humidity (RH) by using Graphene-Oxide/Polyvinyl-Alcohol (GO/PVA) composite. The microsensor is a mechanical oscillator composed of a proof mass with multilayer of nanomaterials (GO/PVA) and suspended by four crab leg springs. The realized redundant approach concerns the possibility to use different readout strategies in order to estimate the same measurand: RH. This is an intriguing solution to realize a “robust measurement system”, with multiple outputs by using the GO/PVA as functional material. In presence of RH variation: (1) it changes its mass and; as consequence; a variation of the natural frequency of the oscillator can be observed in the frequency domain; (2) it also varies the conductivity which can be measured by using two integrated electrodes. The sensor has been designed; studied; modeled and experimental results demonstrate the effectiveness of our implementation

Ultra-sensitive selective detection of HopQ protein as a biomarker for Helicobacter pylori bacteria by an electrochemical voltammetric sensor

Background Helicobacter pylori (H. pylori) is a highly contagious pathogenic bacterium that can cause gastrointestinal ulcers and may gradually lead to gastric cancer. H. pylori expresses the outer membrane HopQ protein at the earliest stages of infection. Therefore, HopQ is a highly reliable candidate as a biomarker for H. pylori detection in saliva samples. Materials and Methods: An H. pylori immunosensor is developed based on detecting HopQ as a biomarker in saliva by a screen-printed carbon electrode (SPCE) modified with MWCNT-COOH decorated with gold nanoparticles (AuNP). The HopQ antibodies are grafted on the SPCE/MWCNT/AuNP surface using EDC/S-NHS chemistry. The sensor performance is investigated by various methods and H. pylori detection performance in spiked saliva samples is evaluated by square wave voltammetry. Results: The sensor is suitable for HopQ detection with high sensitivity and excellent linearity in the 10 pg/mL - 100 ng/mL range and with a 10 pg/ml limit of detection. The sensor was tested in saliva at 10 ng/mL and returned an 107.6% recovery. The dissociation constant Kd for HopQ/HopQ antibody interaction, estimated from Hill\u27s model, is calculated with a value of an order of 4.605 × 10−10 mg/mL. Conclusions: Due to the strategical choice of biomarker, the utilization of nanocomposite material to enhance the SPCE electrical performance, the intrinsic selectivity of the antibody-antigen interaction, and effective immobilization, the fabricated platform shows high selectivity, good stability, reproducibility, and cost-effectiveness for early H. pylori detection. Additionally, we provide insight into possible future aspects the researchers are recommended to focus on

Machine Learning-Based Multi-Level Fusion Framework for a Hybrid Voltammetric and Impedimetric Metal Ions Electronic Tongue

Electronic tongues and artificial gustation for crucial analytes in the environment, such as metal ions, are becoming increasingly important. In this contribution, we propose a multi-level fusion framework for a hybrid impedimetric and voltammetric electronic tongue to enhance the accuracy of K+, Mg2+, and Ca2+ detection in an extensive concentration range (100.0 nM–1.0 mM). The proposed framework extracts electrochemical-based features and separately fuses, in the first step, impedimetric features, which are characteristic points and fixed frequency features, and the voltammetric features, which are current and potential features, for data reduction by LDA and classification by kNN. Then, in a second step, a decision fusion is carried out to combine the results for both measurement methods based on Dempster–Shafer (DS) evidence theory. The classification results reach an accuracy of 80.98% and 81.48% for voltammetric measurements and impedimetric measurements, respectively. The decision fusion based on DS evidence theory improves the total recognition accuracy to 91.60%, thus realizing significantly high accuracy in comparison to the state-of-the-art. In comparison, the feature fusion for both voltammetric and impedimetric features in one step reaches an accuracy of only 89.13%. The proposed hierarchical framework considers for the first time the fusion of impedimetric and voltammetric data and features from multiple electrochemical sensor arrays. The developed approach can be implemented for several further applications of pattern fusion, e.g., for electronic noses, measurement of environmental contaminants such as heavy metal ions, pesticides, explosives, and measurement of biomarkers, such as for the detection of cancers and diabetes

Development of an Efficient Voltammetric Sensor for the Monitoring of 4-Aminophenol Based on Flexible Laser Induced Graphene Electrodes Modified with MWCNT-PANI

Sensitive electrodes are of a great importance for the realization of highly performant electrochemical sensors for field application. In the present work, a laser-induced carbon (LIC) electrode is proposed for 4-Aminophenol (4-AP) electrochemical sensors. The electrode is patterned on a commercial low-cost polyimide (Kapton) sheet and functionalized with a multi-walled carbon nanotubes polyaniline (MWCNT-PANI) composite, realized by an in-situ-polymerization in an acidic medium. The LIC electrode modified with MWCNT-PAPNI nanocomposite was investigated by SEM, AFM, and electrochemically in the presence of ferri-ferrocyanide [Fe(CN)6]3−/4− by cyclic voltammetry and impedance spectroscopy. The results show a significant improvement of the electron transfer rate after the electrode functionalization in the presence of the redox mediators [Fe(CN)6]3−/4−, related directly to the active surface, which itself increased by about 18.13% compared with the bare LIG. The novel electrode shows a good reproducibility and a stability for 20 cycles and more. It has a significantly enhanced electro-catalytic activity towards electrooxidation reaction of 4-AP inferring positive synergistic effects between carbon nanotubes and polyaniline PANI. The presented electrode combination LIC/MWCNT-PANI exhibits a detection limit of 0.006 μM for the determination of 4-AP at concentrations ranging from 0.1 μM to 55 μM and was successfully applied for the monitoring in real samples with good recoveries

Machine Learning-Based Multi-Level Fusion Framework for a Hybrid Voltammetric and Impedimetric Metal Ions Electronic Tongue

Electronic tongues and artificial gustation for crucial analytes in the environment, such as metal ions, are becoming increasingly important. In this contribution, we propose a multi-level fusion framework for a hybrid impedimetric and voltammetric electronic tongue to enhance the accuracy of K+, Mg2+, and Ca2+ detection in an extensive concentration range (100.0 nM–1.0 mM). The proposed framework extracts electrochemical-based features and separately fuses, in the first step, impedimetric features, which are characteristic points and fixed frequency features, and the voltammetric features, which are current and potential features, for data reduction by LDA and classification by kNN. Then, in a second step, a decision fusion is carried out to combine the results for both measurement methods based on Dempster–Shafer (DS) evidence theory. The classification results reach an accuracy of 80.98% and 81.48% for voltammetric measurements and impedimetric measurements, respectively. The decision fusion based on DS evidence theory improves the total recognition accuracy to 91.60%, thus realizing significantly high accuracy in comparison to the state-of-the-art. In comparison, the feature fusion for both voltammetric and impedimetric features in one step reaches an accuracy of only 89.13%. The proposed hierarchical framework considers for the first time the fusion of impedimetric and voltammetric data and features from multiple electrochemical sensor arrays. The developed approach can be implemented for several further applications of pattern fusion, e.g., for electronic noses, measurement of environmental contaminants such as heavy metal ions, pesticides, explosives, and measurement of biomarkers, such as for the detection of cancers and diabetes

Ion-Imprinted Electrochemical Sensor Based on Copper Nanoparticles-Polyaniline Matrix for Nitrate Detection

This study reports a new chemical sensor based on ion-imprinted polymer matrix using copper nanoparticles-polyaniline nanocomposite (IIP-Cu-NPs/PANI). This sensor was prepared by electropolymerization using aniline as a functional monomer and nitrate as template onto the copper nanoparticles-modified glassy carbon (GC) electrode surface. Both ion-imprinted (IIP) and nonimprinted (NIP) electrochemical sensor surfaces were evaluated using UV-Visible spectrometry and scanning electron microscopy (SEM). The electrochemical analysis was made via cyclic voltammetry (CV), linear sweep voltammetry (LSV), and impedance spectroscopy (IS). Throughout this study various analytical parameters, such as scan rate, pH value, concentration of monomer and template, and electropolymerization cycles, were optimized. Under the optimum conditions, the peaks current of nitrate was linear to its concentration in the range of 1μM-0.1M with a detection limit of 31μM and 5μM by EIS and LSV. The developed imprinted nitrate sensor was successfully applied for nitrate determination in different real water samples with acceptable recovery rates

Highly Sensitive Detection of NO2 by Au and TiO2 Nanoparticles Decorated SWCNTs Sensors

The aim of this work is to investigate the gas sensing performance of single wall carbon nanotubes (SWCNTs)-based conductive sensors operating at low–medium temperatures (<250 °C). The investigated sensing films consists of an SWCNT network obtained by drop-casting a SWCNT suspension. Starting from this base preparation, different sensing devices were obtained by decorating the SWCNT network with materials suitable for enhancing the sensitivity toward the target gas. In particular, in this paper, nano-particles of gold and of TiO2 were used. In the paper, the performance of the different sensing devices, in terms of response time, sensitivity toward NO2 and cross-sensitivity to O2, CO and water vapor, were assessed and discussed. Sensors based on decorated SWCNT films showed high performance; in particular, the decoration with Au nano-particles allows for a large enhancement of sensitivity (reaching 10%/1 ppm at 240 °C) and a large reduction of response time. On the other hand, the addition of TiO2 nanoparticles leads to a satisfactory improvement of the sensitivity as well as a significant reduction of the response time at moderate temperatures (down to 200 °C). Finally, the suitability of using Au decorated SWCNTs-based sensors for room temperature sensing is demonstrated

Enhanced Nitrite Detection by a Carbon Screen Printed Electrode Modified with Photochemically-Made AuNPs

Excessive nitrite amounts harm the environment and put public health at high risk. Therefore, accurate and sensitive detection of nitrite in surface and groundwater is mandatory for mitigating its adverse effects. Herein, a highly sensitive electrochemical sensor based on carbon screen-printed electrodes (CSPE) surface-modified with photochemically-made gold nanoparticles (AuNPs, ~12 nm) is proposed for nitrite detection. Scanning electron microscopy, cyclic voltammetry, and electrochemical impedance spectroscopy show that AuNPs uniformly coat the CSPE, increase its surface area, and contribute to oxidizing nitrite to much lower potential (+0.5 V vs. Ag/AgCl) and faster rate. Under optimized differential pulse voltammetry conditions, the CSPE/AuNPs-PEI electrode responds linearly (R2 > 0.99) to nitrite within a wide concentration range (0.01–4.0 µM), showing a sensitivity of 0.85 µA·µM−1·cm−2 and limit of detection as low as 2.5 nM. The CSPE/AuNPs-PEI electrode successfully detects nitrite in tap water and canned water of olives, showing no influence of those matrices. In addition, the electrode’s response is highly reproducible since a relative standard deviation lower than 10% is observed when the same electrode is operated in five consecutive measurements or when electrodes of different fabrication batches are evaluated