Ultrasound-electrochemistry assisted liquid-phase co-exfoliation of phosphorene decorated by Au-Ag bimetallic nanoparticles as nanozyme for smartphone-based portable sensing of 4-nitrophenol.

The stability of black phosphorene (BP) and its preparation and modification for developing and applying devices have become a hot topic in the interdisciplinary field. We propose ultrasound-electrochemistry co-assisted liquid-phase exfoliation as an eco-friendly one-step method to prepare gold-silver bimetallic nanoparticles (Au-AgNPs)-decorated BP nanozyme for smartphone-based portable sensing of 4-nitrophenol (4-NP) in different water sources. The structure, morphology, composition, and properties of Au-AgNPs-BP nanozyme are characterized by multiple instrumental analyses. Bimetallic salts are induced to efficiently occupy oxidative sites of BP to form highly stable Au-AgNPs-BP nanozyme and guarantee the integrity of the lamellar BP. The electrochemistry shortens the exfoliation time of the BP nanosheet and contributes to the loading efficiency of bimetallic nanoparticles on the BP nanosheet. Au-AgNPs-BP-modified screen-printed carbon electrode coupled with palm-sized smartphone-controlled wireless electrochemical analyzer as a portable wireless intelligent sensing platform was applied to the determination of 4-NP in a linear range of 0.6-10 µM with a limit of detection of 63 nM. It enables on-site determination of 4-NP content in lake water, river water, and irrigation ditch water. This work will provide a reference for an eco-friendly one-step preparation of bimetallic nanoparticle-decorated graphene-like materials as nanozymes and their smartphone-based portable sensing application outdoors.

AuNPs-BP-MWCNTs-COOH-based electrochemical immunosensor for the determination of deoxynivalenol in wheat flour.

Deoxynivalenol (DON) has drawn considerable attention for its obvious pathogenicity and wide use in agro-products, which cause a potential threat to human health. In this work, an electrochemical immunosensor is developed for the highly sensitive and selective detection of DON in wheat flour using AuNPs-BP-MWCNTs-COOH and antibodies. The AuNPs-BP-MWCNTs-COOH nanocomposite was prepared via an in situ reduction reaction and ultrasonic-assisted liquid-phase exfoliation. The nanocomposite exhibits a larger surface area, decent stability, excellent electron transfer capability, good protein binding capability and prominent specificity. The plentiful carboxyl group on the nanocomposite can bind to the amino group of the antibody, and AuNPs have an affinity for the sulfhydryl group of the antibody, which makes it feasible for the nanocomposite to load the antibody. The peak currents are plotted against the logarithm of DON concentration from 0.002 to 80 ng mL-1 with a limit of detection (LOD) of 0.5 pg mL-1. This approach establishes an effective label-free immunosensor platform for the detection of DON with high sensitivity and selectivity in various food and agricultural products.

Novel RNA genosensor based on highly stable gold nanoparticles decorated phosphorene nanohybrid with graphene for highly sensitive and low-cost electrochemical detection of coconut cadang-cadang viroid.

Coconut cadang-cadang viroid (CCCVd) is an infectious single-stranded RNA (ssRNA) pathogen, which leads directly to the death of a large number of coconut palm trees and heavy economic loss to coconut farmers. Herein, a novel electrochemical impedance RNA genosensor is presented based on highly stable gold nanoparticles (AuNPs) decorated phosphorene (BP) nanohybrid with graphene (Gr) for highly sensitive, low-cost, and label-free detection of CCCVd. BP-AuNPs are environmentally friendly prepared by ultrasonic-assisted liquid-phase exfoliation of black phosphorus, accompanying direct reduction of chloroauric acid. Gr/BP-AuNPs are facilely prepared by the in situ growth of AuNPs onto the BP surface and its nanohybrid with Gr to improve environmental stability of BP. Gr/BP-AuNP-based RNA genosensor is fabricated by immobilizing the thiol-functionalized single-stranded DNA (ssDNA) oligonucleotide probe onto the surface of Gr/BP-AuNP-modified glassy carbon electrode via gold-thiol interactions, which served as an electrochemical genosensing platform for the label-free impedance detection of CCCVd by hybridization between the functionalized ssDNA probe and the complementary CCCVd ssRNA sequence in a wide linear range from 1.0 × 10-11 to 1.0 × 10-7 M with a low limit of detection of 2.8 × 10-12 M. This work supplies an experimental support and theoretical direction for the fabrication of RNA biosensors based on graphene-like materials and potential application for a specific diagnosis of plant RNA viral disease in Arecaceae planting industry.

Recent advances in metal-organic framework (MOF)-based agricultural sensors for metal ions: a review.

Metal ions have great significance for agricultural development, food safety, and human health. In turn, there exists an imperative need for the development of novel, sensitive, and reliable sensing techniques for various metal ions. Agricultural sensors for the diagnosis of both agricultural safety and nutritional health can establish quality and safety traceability systems of both agro-products and food to guarantee human health, even life safety. Metal-organic frameworks (MOFs) are utilized widely for the design of diversified sensors due to their distinctive structural characteristics and extraordinary optical and electrical properties. To serve agricultural sensors better, this review is dedicated to providing a brief overview of the synthesis of MOFs, the modification of MOFs, the fabrication of MOF-based film electrodes, the applications of MOF-based agricultural sensors for metal ions, which are centered on electrochemical sensors and optical sensors, and current challenges of MOF-based agricultural sensors. In addition, this review also provides potential future opportunities for the development and practical application of agricultural sensors.

Machine learning-guided the fabrication of nanozyme based on highly-stable violet phosphorene decorated with phosphorus-doped hierarchically porous carbon microsphere for portable intelligent sensing of mycophenolic acid in silage.

Violet phosphorene (VP) have been proved to be more stable than black phosphorene, but few reports for its application in electrochemical sensors. In this study, a highly-stable VP decorated with phosphorus-doped hierarchically porous carbon microsphere (PCM) with multiple enzyme-like activities as a nanozyme sensing platform for portable intelligent analysis of mycophenolic acid (MPA) in silage with machine learning (ML) assistance is successfully fabricated. The pore size distribution on the PCM surface is discussed using N2 adsorption tests, and morphological characterization indicates that the PCM is embedded in the layers of lamellar VP. The affinity of the VP-PCM nanozyme obtained under the guidance of the ML model reaches Km = 12.4 µmol/L for MPA. The VP-PCM/SPCE for the efficient detection of MPA exhibits high sensitivity, a wide detection range of 2.49 µmol/L - 71.14 µmol/L with a low limit of detection of 18.7 nmol/L. The proposed ML model with high prediction accuracy (R2 = 0.9999, MAPEP = 0.0081) assists the nanozyme sensor for intelligent and rapid quantification of MPA residues in corn silage and wheat silage with satisfactory recoveries of 93.33%-102.33%. The excellent biomimetic sensing properties of the VP-PCM nanozyme are driving the development of a novel MPA analysis strategy assisted by ML in the context of production requirements of livestock safety.

Magnetic Fe3O4 nanoparticles decorated phosphorus-doped biochar-attapulgite/bismuth film electrode for smartphone-operated wireless portable sensing of ultra-trace multiple heavy metal ions.

Pollution caused by both forestry wastes and heavy metals has increasingly drawn attention owing to environmental safety concerns. After essential oil is extracted from Cinnamomum camphoras (L.), the branches are used as forestry wastes to prepare a phosphorus-doped biochar-attapulgite/bismuth film electrode decorated with magnetic Fe3O4 nanoparticles (MBA-BiFE). The smartphone-operated wireless portable sensor is employed for the simultaneous ultratrace voltammetric detection of multiple heavy metal ions (Cd2+, Pb2+, and Hg2+). Cd2+, Pb2+, and Hg2+ exhibit excellent electrochemical responses in linear ranges of 0.1 nM-5 µM, 0.01 nM-7 µM, and 0.1 nM-3 µM with limits of detection equal to 0.036, 0.003, and 0.011 nM, respectively. The recoveries of MBA-BiFE for Cd2+, Pb2+, and Hg2+ are 93.6-109.9%, 86.0-107.5%, and 94.8-104.6%, respectively, and the RSD values for repeated measurements of Cd2+, Pb2+, and Hg2+ are 4.2%, 2.8%, and 3.3%, respectively. A machine learning model based on an artificial neural network algorithm is constructed to enable a smart determination of ultratrace hazardous multiple metal ions. The portable sensor based on the screen-printed integrated three-electrode sensor modified using MBA-BiFE demonstrates advantages and practicability in outdoor detection, compared with conventional sensors based on MBA-BiFE. This study provides a smartphone-operated wireless portable sensing technique for high-potential applications in environmetallomics or agrometallomics using forestry waste-derived biochar as substrate for electrode preparation. HIGHLIGHTS: • Fe3O4 decorated phosphorus-doped biochar-attapulgite/bismuth film electrode. • A smartphone-operated sensor for analysis of multiple heavy metal ions. • An Artificial neural network model for smart analysis of Cd2+, Pb2+, and Hg2+.

Intelligent analysis of carbendazim in agricultural products based on a ZSHPC/MWCNT/SPE portable nanosensor combined with machine learning methods.

A nano-ZnS-decorated hierarchically porous carbon (ZSHPC) was mixed with MWCNTs to obtain ZSHPC/MWCNT nanocomposites. Then, ZSHPC/MWCNTs were used to modify a screen-printed electrode, and a portable electrochemical detection system combined with machine learning methods was used to investigate carbendazim (CBZ) residues in rice and tea. The electrochemical performance of the constructed electrode showed that the electrode had good electrocatalytic ability, large effective surface area, strong stability and anti-interference ability. Support Vector Machine (SVM), Least Square Support Vector Machine (LS-SVM) and Back Propagation-Artificial Neural Network (BP-ANN) were used to establish the prediction model for CBZ residues in rice and tea, and the traditional linear regression was developed. The investigated results showed that the LS-SVM model had the best prediction performance and the lowest prediction error compared with the traditional linear regression, BP-ANN and SVM models. The R2, RMSE, and MAE for the training set samples were 0.9969, 0.3605 and 0.2968, respectively. The R2, RMSE, MAE and RPD for the prediction set samples were 0.9924, 0.6190, 0.5360 and 10.3097, respectively. The average recovery range of CBZ in tea and rice was 98.77-109.32% and that of RSD was 0.47-2.58%, indicating that the rapid analysis of CBZ pesticide residues in agricultural products based on a portable electrochemical detection system combined with machine learning was feasible.

Halloysite nanotube/black phosphorene nanohybrid modified screen-printed carbon electrode as an ultra-portable electrochemical sensing platform for smartphone-capable detection of maleic hydrazide with machine learning assistance.

With the assistance of machine learning (ML), black phosphorene (BP) stabilized by silver nanoparticles (AgNPs) is used to modify halloysite nanotube (HNT) to obtain highly conductive nanomaterials, HNT/BP-AgNPs, which are morphologically characterized and elementally analyzed. Artificial neural network (ANN) and least squares support vector machine (LS-SVM) are adopted for the intelligent and rapid analysis of maleic hydrazide (MH). An ultra-portable electrochemical sensor bases on HNT/BP-AgNPs modifying screen-printed carbon electrode (SPCE), smartphone and mini-palm potentiostat for detection of MH in the linear range 0.7-55 µM with limit of detection (LOD) of 0.3 µM. For comparison, a traditional electrochemical sensor is fabricated by glass carbon electrode (GCE), desktop computer and large electrochemical potentiostat, and the linear range is 0.3-600 µM with low LOD of 0.1 µM. The ultra-portable electrochemical sensor combined with ML for the detection of MH in sweat potato and carrot gain satisfactory recoveries.

Lotus seedpods biochar decorated molybdenum disulfide for portable, flexible, outdoor and inexpensive sensing of hyperin.

Biomass waste, a good candidate for advanced carbon materials for sustainable electrodes, is receiving more and more attention for high value-added materials because of its promising contribution to economic growth and sustainable development. We proposed a green co-hydrothermal approach to prepare lotus seedpods biochar (BC) decorated molybdenum disulfide (MoS2) from waste lotus seedpods and precursors of MoS2, and a portable, flexible, outdoor and inexpensive sensing platform for hyperin on the integrated flexible three-electrode using U-disk potentiostat with smartphone was successfully developed. Structure and properties of MoS2-BC were characterized, it was proved that BC improves microstructure and morphology, electronic conductivity, electrode stability and electrocatalytic properties of MoS2. Attributing to these impressive features, the detection signal of hyperin was significantly amplified by the MoS2-BC modified glass carbon electrode (GCE) in detection range of 0.01-21 µΜ with detection limit (LOD) of 5 nM. It was worth mentioning that the MoS2-BC modified screen-printed electrode (SPE) performs hyperin detection in range of 100 nM - 3 µM with LOD 50 nM (S/N = 3). The practicability of the proposed method confirmed that the portable, on-site, low-cost, and outdoor detection of hyperin was feasible and practical in comparison with traditional both electrochemical sensing and HPLC methods.

Green synthesis of kudzu vine biochar decorated graphene-like MoSe2 with the oxidase-like activity as intelligent nanozyme sensing platform for hesperetin.

It is an urgent need to exploit a potentially green, cost efficient and eco-friendly strategy for the utilization of waste kudzu vine. We developed a one-step green preparation of kudzu vine biochar (BC) decorated graphene-like molybdenum selenide (MoSe2) with the oxidase-like activity as intelligent nanozyme sensing platform for voltametric detection of hesperetin (HP) in orange peel using the in-situ hydrothermal synthesis method. The structure and properties of MoSe2-BC was characterized, and found that BC significantly improved electrochemical cycle stability, electronic conductivity, electrochemical active area, and electrocatalytic activity of MoSe2. The oxidase-like activity of MoSe2-BC was confirmed by the oxidization of the colorless substrate 3,3',5,5'-tetramethylbenzidine (TMB) to form blue products and the change of absorbance intensity of UV-vis absorption spectra. The MoSe2-BC exhibited excellent electrochemical sensing performance for the detection of HP in wide linear ranges from 10 nM to 9.5 µM with a low limit of detection of 2 nM using differential pulse voltammetric method. An emerging machine learning technique is used to realize the intelligent sensing of HP, and the performance evaluation of regression analysis was selected to evaluate this technique. This work will provide a guidance for the preparation and application of biochar decorated graphene-like nanomaterials with the oxidase-like activity and the development of intelligent nanozyme sensing platform.

Synthesis and characterization of Ag-ion-exchanged zeolite/TiO2 nanocomposites for antibacterial applications and photocatalytic degradation of antibiotics.

This paper investigates the synthesis, antibacterial, and photocatalytic properties of silver ion-exchanged natural zeolite/TiO2 photocatalyst nanocomposite. Zeolite is known to have a porous surface structure, making it an ideal substrate and framework in different nanocomposites. Moreover, natural zeolite has a superior thermal and chemical stability, with hardly any reactivity with chemicals. Finding an effective and low-cost method to remove both antibiotics and bacteria from water resources has become a vital global issue due to the worldwide excessive use of chemicals and antibiotics. This research aims to propose a facile method to synthesize Ag-ion-exchanged zeolite/TiO2 catalyst for anti-bacterial purposes and photocatalytic removal of atibiotics from wastewaters. TiO2 particles were deposited on the surface of natural zeolite. Ag ion exchanging was performed via a liquid ion-exchange method using 0.1 M AgNO3 solution. X-ray diffractometry (XRD), scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), and Fourier-transform infrared spectroscopy (FTIR) were used to evaluate the structure of synthesized powders. Antibacterial activities of samples were assessed, using Staphylococcus aureus ATCC 25923 and Escherichia coli ATCC 25922 by disc diffusion method. It was shown that Ag-containing nanocomposite samples have an improved antibacterial performance in both cases. Results showed that the synthesized catalyst has promising potentials in wastewater treatment.

A portable wireless intelligent electrochemical sensor based on layer-by-layer sandwiched nanohybrid for terbutaline in meat products.

The aim of this study is to develop a portable wireless intelligent nanosensor (PWIN) for rapid cost-effective on-site determination of terbutaline (TRA) residue in meat products outdoors in comparison with traditional nanosensor and high-performance liquid chromatography (HPLC). The layer-by-layer sandwiched nanohybrid fabricated by platinum-palladium nanoparticles, carboxylated graphene and graphene-like molybdenum disulfide displayed a wide linear range of 0.55-14.9 µmol/L using the portable potentiostat with smartphone, and the result was almost close to the linear range (0.4-14 µmol/L) using the traditional potentiostat with desktop computer for TRA. The limit of detections were identified as 0.44 µmol/L and 0.18 µmol/L, respectively. PWIN displayed satisfactory recovery (91%-98.43%) of TRA in samples by the standard addition method and in comparison with both traditional sensor (93.79%-98%) and HPLC (93.4%-98.6%), revealing that PWIN for rapid cost-effective on-site analysis in the food safety field is feasible.

Detection and electrocatalytic mechanism of zearalenone using nanohybrid sensor based on copper-based metal-organic framework/magnetic Fe3O4-graphene oxide modified electrode.

A novel and simple strategy was proposed for the determination of ZEA in breakfast cereal, maize powder and rice flour using an electrochemical nanohybrid sensor based on copper-based metal-organic framework (Cu-MOF)/magnetic Fe3O4-graphene oxide (Fe3O4-GO) modified electrode fabricated by the layer-by-layer assembled technique. The synthesized Cu-MOF with high porosity favorably improved the effective surface area and the analytical performance of nanohybrid sensing electrode. The crafted sensor has large surface area, high electron transfer, and satisfactory efficiency. ZEA was electrochemically detected in a wide linear range from 159.2 to 2865.2 ng mL-1 with LOD of 23.14 ng mL-1 under the optimal conditions. Moreover, the electrocatalytic mechanism of ZEA oxidation was proposed by density functional theory (DFT). A favorable energetic interaction was presented when Cu-MOF adsorbed on Fe3O4-GO, and a small new band appeared on the Fermi level energy (Ef) that facilitated the electron transfer between bands.

Nano-ZnS decorated hierarchically porous carbon electrocatalyst with multiple enzyme-like activities as a nanozyme sensing platform for simultaneous detection of dopamine, uric acid, guanine, and adenine.

The simultaneous detection of multiple biological small molecules is critical for human health evaluation and disease prevention. In this study, a nano-ZnS decorated hierarchically porous carbon (ZSHPC) electrocatalyst with multiple enzyme-like activities as a nanozyme sensing platform for simultaneous derivative voltametric detection of four important biological small molecules, dopamine (DA), uric acid (UA), guanine (G), and adenine (A), is successfully synthesized via an in situ hydrothermal reaction using leaves of Cinnamomum camphora (L.) after the extraction of essential oil as a carbon source, ZnCl2 as both zinc source and an activator, sulfuric acid as a sulfur source, and silica gel as a hard template. Activator together with the introduction of silica gel is beneficial for tuning pore structure. The in situ synthesized ZnS nanoparticles and sulfur doping improve the conductivity and cycling stability of the material. The ZSHPC electrode with multiple enzyme-like activities and oxidase-like characteristics was employed for the simultaneous detection of multiple target molecules in linear ranges of 0.3-500 µM with detection limits of 0.12 µM for DA, 0.26 µM for UA, 0.07 µM for G, and 0.075 µM for A. A derivative technique was selected for enhancing the peak resolution of the partial overlapped voltammograms and eliminating human error. Both the coefficient of determination and residual prediction deviation were used to evaluate this technique.

Intelligent analysis of maleic hydrazide using a simple electrochemical sensor coupled with machine learning.

A simple electrochemical sensing platform based on a low-cost disposable laser-induced porous graphene (LIPG) flexible electrode for the intelligent analysis of maleic hydrazide (MH) in potatoes and peanuts coupled with machine learning (ML) was successfully designed. The LIPG electrode was patterned by a simple one-step laser-induced procedure on commercial polyimide film using a computer-controlled direct laser writing micromachining system and displayed excellent flexibility, 3D porous structure, large specific surface area, and preferable conductivity. A data partitioning technique was proposed for the optimal MH concentration ranges by selecting the size of datasets, including the size of the training set and the size of the test set combined with the performance metrics of ML models. Different algorithms such as artificial neural networks (ANN), random forest (RF), and least squares support vector machine (LS-SVM) were selected to build the ML models. Three ML models were evaluated, and the LS-SVM model displayed unique superiority. Both the recoveries and RSD of practical application were further measured to assess the feasibility of the selected LS-SVM model. This will have important theoretical and practical significance for the intelligent analysis of harmful residuals in agro-product safety using an electrochemical sensing platform.

Portable wireless intelligent sensing of ultra-trace phytoregulator α-naphthalene acetic acid using self-assembled phosphorene/Ti3C2-MXene nanohybrid with high ambient stability on laser induced porous graphene as nanozyme flexible electrode.

The harm of pesticide residues to human health via environmental pollution in agriculture has recently become a significant livelihood issue. Herein, a new strategy for smart ultra-trace analysis of phytoregulator α-naphthalene acetic acid (NAA) residues in farmland environments and agro-products via machine learning (ML) using a nanozyme flexible electrode fabricated by two-dimensional phosphorene (BP) nanohybrid with graphene-like titanium carbide MXene (Ti3C2-MXene) on the flexible substrate surface of laser-induced porous graphene (LIPG) is proposed. Highly ambient-stable BP nanohybrid with Ti3C2-MXene is prepared by ultrasonic-assisted liquid-phase exfoliation in organic solvent containing grinding black phosphorus, cuprous chloride and, Ti3C2-MXene that is obtained by selectively etching Al layers of Ti3AlC2. Nanozyme flexible electrode is fabricated by drop-coating Ti3C2-MXene/BP that is formed through electrostatic self-assembly between positively charged BP and negatively charged Ti3C2-MXene onto LIPG that is obtained by direct laser writing on commercial polyimide and patterned via a computer-aided design system as a flexible substrate. The ML model via artificial neural network algorithm for smart output of NAA is discussed. NAA is electrochemically detected in a wide linear range of 0.02-40 µM with a low limit of detection (LOD) of 1.6 nM using a portable mini-workstation. Large and rough surfaces, excellent electrochemical response, and satisfactory practicability demonstrated the feasibility and detectability of the proposed method. This will provide a portable wireless intelligent nanozyme flexible sensing platform for cost-effective, simple, fast and, ultra-trace detection of hazardous substances in the safety of environments, products, and food in agriculture.

A highly-sensitive and selective antibody-like sensor based on molecularly imprinted poly(L-arginine) on COOH-MWCNTs for electrochemical recognition and detection of deoxynivalenol.

A new strategy to mimic antibody for electrochemical recognition and detection of deoxynivalenol (DON) using a highly-sensitive and selective antibody-like sensor based on molecularly imprinted poly(l-arginine) (P-Arg-MIP) on carboxylic acid functionalized carbon nanotubes (COOH-MWCNTs) was proposed. l-arginine as functional monomer was screened to prepare imprinted electrode via its electro-polymerization in the presence of DON onto the surface of COOH-MWCNTs electrode coupled with theoretical calculation. Surface morphology, structural characteristics, and electrochemical properties of P-Arg-MIP/COOH-MWCNTs were characterized by SEM, EDS, FTIR, and CV, respectively. P-Arg-MIP/COOH-MWCNTs displayed relatively high conductivity, high effective surface area, antibody-like molecular recognition and affinity, and a good response towards DON in a linear range from 0.1 to 70 µM with LOD of 0.07 µM in wheat flour samples with satisfactory recovery and feasible practicability in comparison with HPLC. This method provides a promising biomimetic sensing platform for the determination of mycotoxins in food and agro-products.

Rapid detection of chlorpyrifos pesticide residue in tea using surface-enhanced Raman spectroscopy combined with chemometrics.

Surface enhanced Raman spectroscopy based on rapid pretreatment combined with Chemometrics was used to determine chlorpyrifos residue in tea. Au nanoparticles were used to as enhance substrate. Different dosages of PSA and NBC were investigated to eliminate the tea substrate influence. Competitive adaptive reweighted sampling (CARS) was used to optimize the characteristic peaks, and compared to full spectra variables and the experiment selected variables. The results showed that PSA of 80 mg and NBC of 20 mg was an excellent approach for rapid detecting. CARS - PLS had better accuracy and stability using only 1.7% of full spectra variables. SVM model achieved better performance with R2p = 0.981, RMSEP = 1.42 and RPD = 6.78. Recoveries for five unknown concentration samples were 98.47 ~ 105.18% with RSD - 1.53% ~ 5.18%. T-test results showed that t value was 0.720, less than t0.05,4 = 2.776, demonstrating that no clear difference between the real value and predicted value. The detection time of a single sample is completed within 15 min. This study demonstrated that SERS coupled with Chemometrics and QuEChERS may be employed to rapidly examine the chlorpyrifos residue in tea towards its quality and safety monitoring.

Multiwalled Carbon Nanotube-N-Doped Graphene/Poly(3,4-ethylenedioxythiophene):Poly(styrenesulfonate) Nanohybrid for Electrochemical Application in Intelligent Sensors and Supercapacitors.

In this study, we reported the preparation of a conducting polymeric/inorganic nanohybrid consisting of multiwalled carbon nanotubes (MWCNT), N-doped graphene (NGr), and poly(3,4-ethylenedioxythiophene):poly(styrenesulfonate) (PEDOT:PSS), and its electrochemical application in intelligent sensors and supercapacitors. The multilayer thin film of the PEDOT:PSS-supported MWCNT-NGr nanohybrid was prepared by a facile layer-by-layer assembly strategy. The obtained conducting polymeric/inorganic nanohybrid modified electrode displayed superior electron transfer ability and a high specific surface area, which was used for electrochemical applications in intelligent sensors and supercapacitors. Remarkably, the fabricated amaranth sensor exhibited a broad linear range of 0.05-10 µM with a limit of detection of 0.015 µM under the optimal conditions. With the help of the response surface methodology, multivariate optimization was used as a substitute for the traditional single variable optimization to reflect the complete real effects of multivariate optimization in a sensing platform. Machine learning implemented by hybrid genetic algorithm-artificial neural network was used as an intelligent analysis model to replace the traditional regression analysis model for realizing intelligent analysis and output of sensing system. The MWCNT-NGr/PEDOT:PSS modified electrode exhibited a considerable specific capacitance of 6.5 mF cm-2 at a current density of 2.0 mA cm-2. The proposed results provided a new thought for a nanosensing platform equipped with a supercapacitor as a self-powered electrochemical energy storage system and machine learning as an intelligent analysis and output system in the near future.

Nanobody-based electrochemical competitive immunosensor for the detection of AFB1 through AFB1-HCR as signal amplifier.

A novel nanobody (Nb)-based voltammetric immunosensor coupled with horseradish peroxidase concatemer-modified hybridization chain reaction (HRP-HCR) signal amplifying system is described to realize the rapid and ultrasensitive detection of AFB1. To design such an immunoassay, anti-AFB1 Nbs with smaller molecular size were coated densely onto the surface of Au nanoparticle-tungsten disulfide-multi-walled carbon nanotubes (AuNPs/WS2/MWCNTs) functional nanocomposites as an effective molecular recognition element, whereas AFB1-streptavidin (AFB1-SA) conjugates were ingeniously bound with biotinylated HCR dsDNA nanostructures as the competitor, amplifier, and signal report element. In the presence of AFB1 targets, a competitive immunoreaction was performed between the analyte and AFB1-SA-labeled HCR (AFB1-HCR) platform. Upon the addition of SA-modified polyHRP (SA-polyHRP), AFB1-HCR nanostructures containing abundant biotins were allowed to cross-link to a quantity of HRP by streptavidin-biotin chemistry for signal amplification and signal conversion. Under optimal conditions, the immunosensor displayed a good linear correlation toward AFB1 ranging from 0.5 to 10 ng mL-1 with a sensitivity of 2.7 µA • (mL ng-1) and an ultralow limit of detection (LOD) of 68 fg mL-1. The specificity test showed that the AFB1 immunosensor had no obvious cross-reaction with OTA, DON, ZEN, and FB1. The signal of this sensor decreased by 10.18% in 4 weeks indicating satisfactory stability, and its intra- and inter-laboratory reproducibility was 3.42~10.35% and 4.03%~12.11%, respectively. This biosensing system will open up new opportunities for the detection of AFB1 in food safety and environmental analysis and extend a wide range of applications in the analysis of other small molecules. Graphical abstract.