Active Area Research Articles

Equally Efficient Perovskite Solar Cells and Modules Fabricated via N-Ethyl-2-Pyrrolidone Optimized Vacuum-Flash.

Efficiency reduction in perovskite solar cells (PSCs) during the magnification procedure significantly hampers commercialization. Vacuum-flash (VF) has emerged as a promising method to fabricate PSCs with consistent efficiency across scales. However, the slower solvent removal rate of VF compared to the anti-solvent method leads to perovskite films with buried defects. Thus, this work employs low-toxic Lewis base ligand solvent N-ethyl-2-pyrrolidone (NEP) to improve the nucleation process of perovskite films. NEP, with a mechanism similar to that of N-methyl-2-pyrrolidone in FA-based perovskite formation, enhances the solvent removal speed owing to its lower coordination ability. Based on this strategy, p-i-n PSCs with an optimized interface attain a power conversion efficiency (PCE) of 24.19% on an area of 0.08 cm2. The same nucleation process enables perovskite solar modules (PSMs) to achieve a certified PCE of 23.28% on an aperture area of 22.96 cm2, with a high geometric fill factor of 97%, ensuring nearly identical active area PCE (24%) in PSMs as in PSCs. This strategy highlights the potential of NEP as a ligand solvent choice for the commercialization of PSCs.

Homogenizing the Electron Extraction via Eliminating Low‐Conductive Contacts Enables Efficient Perovskite Solar Cells with Reduced Up‐Scaling Losses

AbstractMaintaining the power conversion efficiency (PCE) of perovskite solar cells (PSCs) while enlarging the active area is necessary for their industrialization, where the key part is the uniform carrier extraction. Here, a conformal electron transport layer (ETL) is reported with eliminated low‐conductive contacts through a tailored deposition that combines chemical bath deposition and modified spin‐coating on a light‐managing textured substrate. The KPFM and C‐AFM are utilized to prove the uniform and optimized electrical properties. This study further employs the 2D measurements of PL and TRPL mapping to focus on revealing the enhanced uniformity of electron extraction. The uniform ETL conductivity and electron extraction contribute to a substantial decrease in device up‐scaling losses, making the δPCE ( between 0.08 cm2‐device and 1 cm2‐device decrease from 5.02% to 2.97%, while the perovskite film is deposited using two‐step method. When using one‐step method to deposit perovskite film, PCEs of 25.13% and 23.93% for the active area of 0.08 cm2 and 1 cm2 are achieved, and the δPCE decreases from 7.89% to 4.77%, validating the significant effects on reducing up‐scaling losses. This work provides a new perspective to maintain high efficiency while device up‐scaling, providing more opportunities to push forward the PSCs industrialization.

Innovative use of shrimp shell powder in carbon paste electrode for the electrochemical detection of dopamine and paracetamol: Valorization, characterization and application

The present study outlines the design of an innovative, cost-effective, and environmentally friendly electrochemical sensor, based on a carbon paste electrode (CPE) modified by shrimp shell waste (SSW). The developed electrode was used to facilitate the electrocatalytic detection of two compounds, namely dopamine (DA) and paracetamol (PAR). The use of SSW as an electrode material is ground breaking. The results have shown that the addition of shrimp shell (SS) in the CPE has led to a significant increase in the active surface area (0.504 cm2) and has improved electron transfer by decreasing the charge transfer resistance (17.45 Ω.cm2) at the electrode/solution interface. The SSW was characterized by scanning electron microscopy (SEM), energy-dispersive X-ray spectroscopy (EDS), X-ray diffractometry (XRD), and fourier transform infra-red (FTIR). The results show a fibrous and porous structure with high calcium content and other chemical elements including carbon, oxygen, sulphur, phosphorus and nitrogen. The electrochemical behavior of DA and PAR on the CPE-SS electrode was studied using cyclic voltammetry (CV), chronoamperometry (CA), electrochemical impedance spectroscopy (EIS), and square wave voltammetry (SWV) techniques. Additionally, CPE and CPE-SS electrodes were examined by SEM/EDS and FTIR. The effect of scan rate shows that the electrochemical process is diffusion controlled for DA and PAR. The CPE-SS electrode provide a wide linear range, good selectivity, repeatability, precision (≤5%), and low detection limits 3.6 µM and 5.54 µM for DA and PAR, respectively. In addition, the developed sensor was applied to detect DA and PAR in urine, tap water, and pharmaceutical tablets with apparent recoveries.

Experimental investigation of degradation mechanism in proton exchange membrane water electrolyzer under prolonged and severe bubble accumulation condition

Proton exchange membrane water electrolyzer (PEMWE) exhibits significant potential as a technology for hydrogen production driven by sustainable energy sources. In this study, the performance degradation characteristics of PEMWE under severe bubble accumulation condition lasting 100 h were investigated through in-situ and ex-situ characterization techniques. The results show that an increasing performance disparity with higher voltage, notably at lower temperatures, reaching a 58.2 % current density degradation rate at 50 °C and 2.0 V. Electrochemical impedance spectroscopy (EIS) analysis suggests that electrolyzer performance degradation is mainly due to increased charge transfer impedance, especially at the anode. In addition, the degraded electrolyzer exhibits a significant delay in reaching a stable current density during the abrupt voltage loading process, and its Tafel slope and electrochemically active surface area (ECSA) increased and decreased by 12.8 % and 13.5 %, respectively. Based on scanning electron microscopy (SEM) images, post-experiment analysis reveals pronounced thinning and noticeable cracks in both cathode and anode catalyst layers near the outlet, particularly on the anode side. Additionally, energy dispersive spectroscopy (EDS) mappings and transmission electron microscopy (TEM) images confirm substantial Pt/C and IrO2 catalyst particle dissolution, migration, and agglomeration. The findings of this study contribute to enhancing understanding of the performance degradation mechanisms in PEMWE.

Beyond 99.5% Geometrical Fill Factor in Perovskite Solar Minimodules with Advanced Laser Structuring

AbstractPerovskite solar cells, known for high efficiency and compatibility with various photovoltaic (PV) applications, have garnered significant attention from academia and industry. Scaling up these cells conventionally involves fabricating modules with series‐connected cells using a monolithic interconnection based on the P1‐P2‐P3 scheme, a common approach for thin‐film PV modules. The Geometrical Fill Factor (GFF), representing the ratio between active area and aperture area, typically ranges from 90% to 95%. This study introduces an advanced laser manufacturing process to minimize interconnection area by reducing scribe width and minimizing distances between them, achieving an interconnection width of 45 µm with a GFF of 99.1%. Additionally, a discontinuous P2 design further reduces the dead area to an average of 19.5 µm, resulting in a record GFF of 99.6%. Using this interconnection in a highly efficient p‐i‐n stack, the study demonstrates the feasibility of the discontinuous P2 by fabricating 2.6 cm2 minimodules with an aperture area efficiency of 20.7%. The research highlights how proper design can minimize intrinsic losses during the scaling process from cell to module to a negligible level. Experimental studies, coupled with cell‐to‐module loss simulations and electroluminescence mapping for layer deposition uniformity, provide insights into the potential of the new P2 design.

TinyM 2 Net-V2: A Compact Low-power Software Hardware Architecture for M ulti m odal Deep Neural Networks

With the evaluation of Artificial Intelligence (AI), there has been a resurgence of interest in how to use AI algorithms on low-power embedded systems to broaden potential use cases of the Internet of Things (IoT). To mimic multimodal human perception, multimodal deep neural networks (M-DNN) have recently become very popular with the classification task due to their impressive performance for computer vision and audio processing tasks. This article presents TinyM 2 Net-V2 —a compact low-power software hardware architecture for m ulti m odal deep neural networks for resource-constrained tiny devices. To compress the models to implement on tiny devices, cyclicly sparsification and hybrid quantization (4-bits weights and 8-bits activations) methods are used. Although model compression techniques are an active research area, we are the first to demonstrate their efficacy for multimodal deep neural networks, using cyclicly sparsification and hybrid quantization of weights/activations. TinyM 2 Net-V2 shows that even a tiny multimodal deep neural network model can improve the classification accuracy more than that of any unimodal counterparts. Parameterized M-DNN model architecture was designed to be evaluated in two different case-studies: vehicle detection from multimodal images and audios and COVID-19 detection from multimodal audio recordings. The most compressed TinyM 2 Net-V2 achieves 92.5% COVID-19 detection accuracy (6.8% improvement from the unimodal full precision model) and 90.6% vehicle classification accuracy (7.7% improvement from the unimodal full precision model). A parameterized and flexible FPGA hardware accelerator was designed as well for TinyM 2 Net-V2 models. To the best of our knowledge, this is the first work accelerating multimodal deep neural network models on low-power Artix-7 FPGA hardware. We achieved energy efficiency of 9.04 GOP/s/W and 15.38 GOP/s/W for case-study 1 and case-study 2, respectively, which is comparable to the state-of-the-art results. Finally, we compared our tiny FPGA hardware implementation results with off-the-shelf resource-constrained devices and showed our implementation is faster and consumed less power compared to the off-the-shelf resource-constrained devices.

Geostatistical Analysis of Lineament Domains: The Study Case of the Apennine Seismic Province of Italy

Regional-scale swarms of subparallel linear topographic features, known as lineament domains, are a common feature of planetary surfaces. Lineament domains are superficial manifestations of the crustal stress field trajectory. Notably, one of the effects of active tectonics is seismicity. Italy is one of the most seismically active regions in the Mediterranean, with many destructive earthquakes that have occurred in past centuries. Here, we assess the seismic meaning of the main lineament domain in the tectonically active region of Central Italy. We describe the use of an automated analysis of satellite imagery coupled with spatial grid analysis to identify three lineament domains of the Central Apennines. Spatial and azimuthal comparisons of the main lineament domain (i.e., the Apennine Domain), with the known locations of earthquakes (moment magnitude of Mw > 5.5) that occurred during the past century, revealed the most seismically active tectonic areas and their spatial distributions. Further, we present a conceptual seismo-geodynamic model for the Central Apennines, which is characterized by regional arching and explains the presence of an extensional tectonic regime in the upper crustal layer of the active Apennines fold-and-thrust belt.

Prerequisites-based course recommendation: recommending learning objects using concept prerequisites and metadata matching

The recommendation is an active area of scientific research; it is also a challenging and fundamental problem in online education. However, classical recommender systems usually suffer from item cold-start issues. Besides, unlike other fields like e-commerce or entertainment, e-learning recommendations must ensure that learners have the adequate background knowledge to cognitively receive the recommended learning objects. For that reason, when designing an efficient e-learning recommendation method, these challenges should be considered. To address those issues, in this paper, we first propose extracting pairs concept prerequisites using Linked Open Data (LOD). Then, we evaluate the proposed list of prerequisite relationships using machine learning predictive models. Then, we present the recommendation approach based on matching concept’s prerequisites relation and courses metadata through a similarity score. The experimental result of prerequisite identification was evaluated using four well-known machine learning algorithms while achieving an accuracy of 90%. Moreover, using three known evaluation metrics, the final prerequisite-based recommendation demonstrates very good results (NDCG@10 = 86%). This solution will enhance recommendations on online learning platforms. Additionally, it will overcome the cold-start issue and accomplish the needed prerequisites and background knowledge for learners to attain their learning objectives.

A “Leaf‐Vein” Flow Channel Design for the Improvement of Oxygen Transporting in a Large‐Scale Proton Exchange Membrane Electrolysis Cell

In a proton exchange membrane electrolysis cell (PEMEC), the oxygen generated on the anode side diffuses into the flow channel and forms a gas–liquid two‐phase flow with liquid water. In order to increase the production of hydrogen, larger sized PEMEC would be favorable other than series connection of smaller ones, which can save cost, though the corresponding flow channel design is lacked. Herein, a “leaf‐vein” bionic flow channel for large‐scale PEMEC (the activation area is 1350 cm2) is proposed. A 3D mixture and steady model of the PEMEC is developed to characterize the two‐phase flow in the flow field. Detailed analyses of geometric parameters are conducted through orthogonal test to determine the optimal channel geometry. The numerical results show that the optimized design of PEMEC increases medium and low oxygen gas content, and reduces pressure drop compared to traditional flow channels. An interdigitated leaf‐vein flow field is applied, which effectively alleviates gas blockage problems. This article will provide a theoretical basis for large‐scale PEMEC manufacturing.

Utilizing InSAR for Surface Stability Monitoring in Mining Sites: A Case Study of Sukari Gold Mine in Egypt

Abstract. The monitoring of mining sites is crucial as a result of the safety and environmental issues linked to mining activities. Traditional surveying and monitoring tools exhibit limitations in terms of spatial coverage and are associated with various concerns regarding time and cost efficiency. Hence, the mining industry has shown increased interest in the time-series analysis of interferometric synthetic aperture radar (InSAR). This is primarily due to its precision and wide spatial coverage advantages. This study employed an InSAR technology, persistent scatterer interferometry (PSI), to identify potential geohazards within the Sukari gold mine (SGM), located in Egypt. A total of 23 images were collected from the ascending orbit of Sentinel-1 sensor between January 7, 2022, and November 3, 2022, for the SGM mining location. Results revealed relatively stable measurements in non-mining areas of the site, with a surface displacement within ±10mm per year in the line-of-sight (LOS) direction. However, several active mining operation areas showed significant surface motion. Various sections of the open pit of the SGM exhibited displacement, including the southwestern edge (-16.8mm) and the northeastern edge (35.7mm), and the highest velocity was detected at a section of the western edge, which demonstrated an annual displacement of -64mm in the LOS. Additionally, notable surface motion was observed in some parts of the two tailings storage facilities at the site. The results of this study illustrate the importance of InSAR techniques in mining site-wide coverage stability monitoring.

Porous cobalt phosphide nanoflakes supported on ordered mesoporous carbon for superior electrochemical performance supercapacitor and hydrogen evolution reaction

In this study, we synthesized cobalt phosphate flake-like nanostructures anchored to the OMC matrix using a simple and cost-effective hydrothermal process followed by an environmentally friendly phosphidation process. The physicochemical characterization of the CoP@OMC composite indicated that the porous CoP nanoflakes made up of bundles of ultrathin nanosheets with an approximate thickness of 30 nm are anchored on rod-like hexagonal OMC with a diameter of 110–140 nm, allowing remarkable enhancement of mesoporosity and active surface area. The CoP@OMC composite was employed as a new material for modification of electrode surface used in supercapacitor and hydrogen evolution reaction (HER). Interestingly, CoP@OMC acquired a specific capacitance of 3182 Fg−1 at current density of 1 A g−1, in 6 M KOH. Asymmetrical CoP@OMC//CB cell showed a capacity of 194 Fg−1 at the current density of 1 A g−1 with a maximum energy density of 77.9 Wh kg−1 and a power density of 17 kW kg−1. CoP@OMC composite also showed an excellent HER performance with only 111 mV overpotential to drive a current density of 10 mA cm−2 and a low Tafel slope of 43.8 mV dec−1 in 1 M KOH. Therefore, CoP(OMC) as an environmentally friendly material with high efficiency and significant catalytic / electronic properties is expected to be a good candidate for future energy storage & conversion systems.

Interface engineering of 2D/2D MoS2/In2S3 heterostructure for highly sensitive NO2 detection at room temperature gas sensor

Rapid industrial growth and technological advancements in recent decades have led to an urbanized society at the expense of the environment due to toxic gas emissions. Therefore, it is imperative to detect trace concentrations of harmful gas with reliable techniques. NO2 is essentially being targeted for detection among all other gases due to its enormous abundance and serious health risks. Recently, 2D-MoS2 with enormous adsorption sites and high chemical reactivity have been employed selectively to detect NO2 at room temperature (RT). Herein, uniform and high surface area MoS2/In2S3 nanosheets (NSs) heterostructures were synthesized by hydrothermal method. HR-TEM analysis confirmed the 2D/2D heterostructures of MoS2/In2S3 nanosheets (NSs), and the increase in surface area of MoS2 from 10 m2/g to 27.2 m2/g upon addition of In2S3, measured through BET analysis. The MoS2/In2S3 sensor demonstrated excellent sensing capability with a response of 185% towards 50 ppm of NO2 at RT (30 ℃). Additionally, the sensor exhibited stable detection for about 42 days, repeatability over 5 cycles, and a detection limit of 450 ppb towards NO2. The synergistic influence of 2D/2D heterostructure with significant active sites and surface area is responsible for the considerable improvement in sensing performance. Therefore, the MoS2/In2S3 nanocomposites demonstrate a facile approach for developing high-performance potentially hazardous gas detectors for RT applications.

A 60 dB gain range programmable gain current amplifier for ultrasound sensing

This article presents a programmable gain current amplifier (CA) for ultrasound sensing applications. The design proposed consists of a current divider and a close-loop current amplifier. The CA utilizes switches to adjust the resistance of the shunt resistors and feedback resistors to achieve variable gain, thus realizing the time gain compensation (TGC) function. The proposed CA implemented in 180-nm BCD technology occupies an active area of 0.059 mm2. Measurement results show that the CA achieves a maximum gain of 36.6 dB and a gain range of 60 dB. The average input-referred noise spectral density is 0.32 pA/√Hz at maximum gain condition while consuming a power of 1.07 mW.

Novel high-efficiency 2D position-sensitive ZnS:Ag/6LiF scintillator detector for neutron diffraction

Scintillator-based ZnS:Ag/6LiF neutron detectors have been under development at ISIS for more than three decades. Continuous research and development aim to improve detector capabilities, achieve better performance and meet the increasingly demanding requirements set by neutron instruments. As part of this program, a high-efficiency 2D position-sensitive scintillator detector with wavelength-shifting fibres has been developed for neutron-diffraction applications. The detector consists of a double scintillator-fibre layer to improve detection efficiency. Each layer is made up of two orthogonal fibre planes placed between two ZnS:Ag/6LiF scintillator screens. Thin reflective foils are attached to the front and back scintillators of each layer to minimize light cross-talk between layers. The detector has an active area of 192 × 192 mm with a square pixel size of 3 × 3 mm. As part of the development process of the double-layer detector, a single-layer detector was built, together with a prototype detector in which the two layers of the detector could be read out separately. Efficiency calculations and measurements of all three detectors are discussed. The novel double-layer detector has been installed and tested on the SXD diffractometer at ISIS. The detector performance is compared with the current scintillator detectors employed on SXD by studying reference crystal samples. More than a factor of 3 improvement in efficiency is achieved with the double-layer wavelength-shifting-fibre detector. Software routines for further optimizations in spatial resolution and uniformity of response have been implemented and tested for 2D detectors. The methods and results are discussed in this manuscript.

Single-photon detection using large-scale high-temperature MgB2 sensors at 20 K

Ultra-fast single-photon detectors with high current density and operating temperature can benefit space and ground applications, including quantum optical communication systems, lightweight cryogenics for space crafts, and medical use. Here we demonstrate magnesium diboride (MgB2) thin-film superconducting microwires capable of single-photon detection at 1.55 μm optical wavelength. We used helium ions to alter the properties of MgB2, resulting in microwire-based detectors exhibiting single-photon sensitivity across a broad temperature range of up to 20 K, and detection efficiency saturation for 1 μm wide microwires at 3.7 K. Linearity of detection rate vs incident power was preserved up to at least 100 Mcps. Despite the large active area of up to 400 × 400 μm2, the reset time was found to be as low as ~ 1 ns. Our research provides possibilities for breaking the operating temperature limit and maximum single-pixel count rate, expanding the detector area, and raises inquiries about the fundamental mechanisms of single-photon detection in high-critical-temperature superconductors.

Spatio-temporal pattern analysis of coastal zone in Nansha based on remote sensing technology

Among the most important and active areas of coastal cities is the coastal zone. Examining the changes in the coastal zone of Nansha District is helpful in identifying the spatiotemporal evolution pattern and driving force of this area, as well as serving as a guide for the preservation and exploitation of its resources. This is due to the fact that remote sensing's ability to collect and analyze coastlines can show minute variations in the way the water and land interact. The article uses drone orthophotos and Landsat and Quickbird paired with eight different sceneries from 1987 to 2021 to extract the coastline using remote sensing (RS) and geographic information system (GIS) techniques. The spatiotemporal features of the evolution of the Nansha shoreline are examined in order to guarantee correctness. and the motivating elements are talked about. The findings indicate that: 1) Over the previous 30 years, there has been a consistent upward tendency along Nansha District's shoreline. Among these, the percentage of artificial shoreline is growing annually, growing by about 56%, while the natural coastline is decreasing annually, decreasing by 70%. 2) There is a shift in the type of shoreline from natural to sea-reclamation, engineering construction, and aquaculture. 3) The modifications to the coastline have occurred in three phases: the first was the agricultural phase; the second was the port petrochemical phase; and the third was the reasonable restraint phase (quality construction). Wanqingsha, Longxue Island, and Nansha Bay's coastlines are all close to significant expansion areas of coastline. 4) The primary causes of the changes in the Nansha District shoreline are human activity, regional policy, and natural elements.

Electric Susceptibility at Partial Coverage of a Circular One-Side Access Capacitive Sensor with Rigid Polyurethane Foams.

The capability of dielectric measurements was significantly increased with the development of capacitive one-side access physical sensors. Complete samples give no opportunity to study electric susceptibility at a partial coverage of the one-side access sensor's active area; therefore, partial samples are proposed. The electric susceptibility at the partial coverage of a circular one-side access sensor with cylinders and shells is investigated for polyurethane materials. The implementation of the relative partial susceptibility permitted us to transform the calculated susceptibility data to a common scale of 0.0-1.0 and to outline the main trends for PU materials. The partial susceptibility, relative partial susceptibility, and change rate of relative partial susceptibility exhibited dependence on the coverage coefficient of the sensor's active area. The overall character of the curves for the change rate of the relative partial susceptibility, characterised by slopes of lines and the ratio of the change rate in the centre and near the gap, corresponds with the character of the surface charge density distribution curves, calculated from mathematical models. The elaborated methods may be useful in the design and optimization of capacitive OSA sensors of other configurations of electrodes, independent of the particular technical solution.

Evaluating the Durability of Perfluorosulfonic Acid Membranes in Fuel Cells Using Combined Open-Circuit Voltage-Accelerated Stability Testing.

This study evaluates the chemical and mechanical durability of membranes used in proton exchange membrane fuel cells, highlighting the essential role of electrochemical tests in understanding the relationship between durability and performance. Our methodology integrates various electrochemical evaluation techniques to assess the degradation of perfluorosulfonic acid (PFSA) membranes. The results highlight the considerable improvement in the chemical and mechanical durability of annealed 3M PFSA-reinforced composite membranes (RCMs) compared with their non-annealed counterparts and other membrane types, indicating their superior resilience under challenging conditions. Moreover, the results of using a combined open-circuit voltage-accelerated stability testing protocol demonstrate that annealed 3M PFSA RCMs exhibit enhanced resilience, reaching 18,000 cycles before failure, considerably outperforming NR 211 (5000 cycles) and other membranes. In addition, membrane deterioration over time can be precisely measured by interpreting electrochemical indicators (electrochemically active surface area, circuit resistance, high-frequency resistance, and proton resistance). This approach provides a clear relationship between electrochemical data and durability, offering a comprehensive understanding of how different membranes withstand operational stresses.

Preparation of electrocatalytic KC-GR/GF membrane cathode and its application in electro-Fenton

ABSTRACT Tetracycline is a common antibiotic that threatens the water environment and requires more stable and efficient ways to degrade it. In this paper, a novel filtered cathode material was prepared by proportionally loading Ketjen Black Carbon (KC) and Graphene (GR) onto Graphite Felt(GF) by coating method, and applied to remove tetracycline from water by electro-Fenton system. The results showed that the highest hydrogen peroxide yield of up to 28.86 mg/L was achieved at the electrodes prepared with a carbon loading of 0.228 g, m (KC):m(polytetrafluoroethylene) = 1:9, and m (KC):m (GR) = 2:2. By characterisation, the contact angle of the loaded graphite felt electrode increased from 71.5° to 126.3°, with faster current responsiveness and larger electrochemically active area than the unloaded electrode. Furthermore, in the application of electro-Fenton: when I = 100 mA, Air = 0.45 L/min, pH = 3 and Fe2+ = 0.3 mol/L, the optimal removal rate of 50 mg/L tetracycline was 99.1%, and the energy consumption was only 8.49 kWh/kg. This electrode has a great advantage in treating the low concentration of tetracycline, and 99.4% of tetracycline can be removed within 30 min. After 8 cycles of tests, the removal rate of tetracycline by this electrode was above 95%. The article demonstrated that the reactor coupled with electrochemical advanced oxidation technology and membrane filtration technology has the effect of enhanced mass transfer, and the Ketjen Black Carbon-Graphene/Graphite Felt (KC-GR/GF) electrocatalytic membrane cathode has the potential and practical significance to be applied for the removal of tetracycline under the electro-Fenton system.

Fabrication of an electrochemical sensing platform based on MWCNT-CONH-66-UiO and PEDOT:PSS for highly sensitive and rapid detection of sunset yellow

The out-of-range, overdose and illegal usage of sunset yellow azo dye in food will cause great damage to food safety and consumer health. In this work, a novel electrochemical sensing platform toward sunset yellow detection was prepared based on the amidated MWCNT-CONH-66-UiO and poly(3,4-ethylenedioxythiophene):poly(styrene sulfonate) (PEDOT:PSS). In MWCNT-CONH-66-UiO, the –NHCO- is produced by the amidation reaction between zirconium 2-amino terephthalate (UiO-66-NH2) and carbonylated multi-walled carbon nanotubes (MWCNT-COOH), which play significant role for the enhancement of the sensing properties of MWCNT-CONH-66-UiO/PEDOT:PSS composite. PEDOT:PSS acts as a conducting film coated on MWCNT-CONH-66-UiO and alleviates the electrooxidation of –NHCO-. The large specific surface area, good conductivity, and outstanding synergistic effect of the composite trigger off prominent sensing properties of MWCNT-CONH-66-UiO/PEDOT:PSS toward sunset yellow detection with the lowest detection limit as 3.3 nM and a sensitivity as 6.6 mA mM−1 cm−2 (active area of 0.15 cm2). Additionally, this sensor shows satisfactory results for sunset yellow detection in plain cake and marinating meat via DPV in comparison to the high-performance liquid chromatography method. The research results in this work will provide technical support for the rapid and efficient detection of azo dyes in food, animal feeds, and industrial wastewater.