Response Time Research Articles

Modulation of ZrO2-Ag2O-MoO3 nanocomposite into ultrasensitive hydrazine electrochemical sensor for environmental remediation

Herein, a facile single-step wet chemical approach was executed for the composition of semiconductor ternary metal oxides (TMO) i.e., ZrO2-Ag2O-MoO3 nanocomposite (NC)in an alkaline medium. For structural as well as morphological elucidation, the calcined nanocomposite was characterized through ultraviolet–visible diffuse reflectance spectroscopy (UV–Vis DRS), Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), powdered X-ray diffraction (XRD), field emission scanning electron microscopy (FESEM), energy-dispersive X-ray spectroscopy (EDS) and Brunauer-Emmett-Teller (BET) analysis. Later, the glassy carbon electrode (GCE) was modified into a highly responsive as well as selective hydrazine (HDZN) electrochemical probe (ZrO2-Ag2O-MoO3-NC/PEDOT:PSS/GCE) by the fabrication of thin layered ZrO2-Ag2O-MoO3NC onto GCE facilitated by 5 % PEDOT:PSS as conducting polymer binder. While examining the analytical parameters through novel current–potential (I-V) electrochemical approach, for the first time, the newly designed electrochemical probe, as selective hydrazine sensor, happened to own the low detection limit (LOD; 0.028 pM) with greater sensitivity (33.86 μAμM−1cm−2) and broad linear dynamic range (LDR; 0.1 M–1.0 nM) in addition to coefficient of correlation (r)/r2 square (r = 0.9941, r2 = 0.9882) and low limit of quantification (LOQ; 0.093 pM).Furthermore, reproducibility as well as prolonged stability of this newly proposed probe towards hydrazine were also assessed and found to be reliable in short response time. Hence, this work presents an inaugural report about the sensing of HDZN through the newly designed non reported ZrO2-Ag2O-MoO3-NC/PEDOT:PSS/GCE via an economical as well as novel electrochemical, current–potential (I-V),approach. Additionally, this proposed method is equally responsive towards both environmental and extracted real samples analysis on large scale.

Humidity tolerant enhanced hydrogen gas sensing using MoSe[formula omitted]-WSe[formula omitted] heterostructures: An experimental and computational insights

In recent times, air pollution’s threat to humanity highlights the urgent need for advanced sensors to monitor harmful gases, essential for industrial regulation, gas leak detection, and air quality surveillance. Two-dimensional transition metal dichalcogenides (TMDCs) has garnered noteworthy attention as potential materials for gas sensing. This paper investigates the synthesis and characterization of a heterostructure composed of molybdenum diselenide with tungsten diselenide (MoSe2-WSe2) nanomaterials using a liquid phase exfoliation technique and it’s H2 sensing performance. The material characterisations confirmed the successful exfoliation into a hexagonal sheet-like, nanocrystalline MoSe2-WSe2 nanostructure. The study further assessed the sensor’s response to H2 gas, for concentrations of 5–25 ppm at room temperature, comparing the performance of MoSe2-WSe2 sensor with a pristine WSe2 sensor. The MoSe2-WSe2 sensor outperformed the pristine WSe2 sensor with a response of 59.57%, rapid response times and recovery times (16 s and 30 s respectively), low detection limit of 5.55 ppm, good repeatability, and high durability (30 days). Additionally, the impact of humidity was evaluated at 25 ppm H2 (at relative-humidity from 40% to 90%). The hydrophobic nature of MoSe2-WSe2 (CA = 141.4°) aligns with the first principle studies, showing almost no change in bandgap when exposed to humidity. These findings emphasize the potential of MoSe2-WSe2 heterostructure sensors for detecting H2 in humid conditions, filling a gap in research and advancing gas sensing technology for environmental safety.

Structural disorder facilitates future memory decisions.

It is well known that perception and cognition are systematically biased towards the recent past. That is, a decision about the current state of a perceptual feature (e.g. orientation) can be predicted based on a recent state of the same feature. Such serial dependencies have been demonstrated across perception, memory and cognition, and have been jointly attributed to an adaptive mechanism meant to promote stability in a constantly changing environment. Here, we argue that this adaptive mechanism prioritizes past information on the most basic structural level, such that the strength of the attractive bias is modulated by the amount of structural coherence in stimuli. We presented visual patterns of varied structural disorder (randomness) prior to a recognition memory decision that required discriminating between trained and novel visual patterns. Both highly generic geometrical shapes and completely random patterns failed to elicit an effect on decisional response times. By contrast, we found recognition memory decisions to be significantly faster in trials where the irrelevant probe pattern was 'optimally' random. This result suggests that decision-making is influenced by the past's informational worth. More importantly, it suggests an optimal amount of uncertainty to facilitate future decisions.

A Novel Benzothiazole-Based Fluorescent AIE Probe for the Detection of Hydrogen Peroxide in Living Cells.

A benzothiazole-based derivative aggregation-induced emission (AIE) fluorescent 'turn-on' probe named 2-(2-((4-(4,4,5,5-tetramethyl-1,3,2-dioxaborolan-2-yl)benzyl)oxy)phenyl)benzo[d]thiazole (probe BT-BO) was developed and synthesized successfully for detecting hydrogen peroxide (H2O2) in living cells. The synthesis method of probe BT-BO is facile. Probe BT-BO demonstrates a well-resolved emission peak at 604 nm and the ability to prevent the interference of reactive oxygen species (ROS), various metal ions and anion ions, and good sensitivity. Additionally, the probe boasts impressive pH range versatility, a fast response time to H2O2 and low cytotoxicity. Finally, probe BT-BO was applied successfully to image A549 and Hep G2 cells to monitor both exogenous and endogenous H2O2.

Development of an Online Cloud Fog Monitor: Design, Laboratory, and Field Deployment at an Unoccupied Coastal Site in Eastern China

Online detection of cloud water chemistry is a pressing issue in atmospheric outfield observation, with online detection modules representing a significant development direction for cloud water observation. Addressing the common problem of time-delayed errors in manual detection, particularly in the context of cloud water acidity, has remained challenging, with limited understanding and effective solutions available. We developed an Online Cloud Fog Monitor (OCFM) featuring automatic pH and electrical conductivity (EC) detection capabilities, and conducted comprehensive laboratory and field tests. The OCFM utilizes a peristaltic pump, water pipe, and diversion chamber to direct cloud samples to distinct detection chambers, enabling real-time analysis. The diversion chamber is equipped with dual liquid level sensors to segregate and preserve samples once the volume exceeds a predetermined threshold. Calibration results indicate that the instrument's background metal elements do not affect cloud water analysis, and detection occurs within the designed response time. Field tests demonstrate that the OCFM can collect over 50 ml of cloud water, with a response accuracy exceeding 63.6%, though influenced by meteorological conditions. The time-delay error for pH was notably larger than for EC. Comparative analysis with the Caltech Active Strand Cloudwater Collector (CASCC) revealed that the OCFM’s sampling process does not introduce errors, and the online detection accuracy of pH and EC is comparable to manual methods. Additionally, water-soluble ions in samples collected by the OCFM showed no significant differences compared to those collected by CASCC. Overall, the OCFM effectively replaces manual testing, mitigating time-delay errors in chemical property testing. The introduction of this cloud water detector promises to significantly reduce labor costs and economic consumption associated with cloud water observation, thereby facilitating long-term, multi-site observation of cloud water chemistry.

Amorphous NiO nanopyramids with superior electrochromic energy storage properties

In this work, amorphous NiO nanopyramid film has been obtained by using the pulsed magnetron sputtering technique. The uniform amorphous NiO nanostructures exhibit significant electrochromic modulation efficiency in the visible and near-infrared ranges, achieving a high modulation efficiency of 60.73 % at 550 nm and 21.58 % at 1500 nm. It exhibits rapid response time (coloring takes 2.4 s, and bleaching takes 1.0 s) and significant coloring efficiency (43.23 cm2C-1). Moreover, amorphous NiO nanopyramid film displays promising properties of energy storage. The NiO nanopyramid film shows high areal capacitance (7.08 mF/cm2), along with satisfying rate capability. The alteration in the electrode color offers a convenient method for monitoring the quantity of energy stored. Furthermore, the microstructure characteristic, degree of crystallization and electrochemical performance of the NiO film are significantly influenced by both oxygen partial pressure and sputtering time. These findings highlight the potential of employing this bifunctional amorphous NiO nanopyramid film in diverse advanced nanodevices, encompassing electrochromic energy storage applications with superior performance.

Lead-time-dependent calibration of a flood forecasting model

The hydrological models used for flood forecasting purposes are usually first calibrated in simulation mode and then applied for flood forecasting in combination with some data assimilation procedure allowing to update and correct the model in real-time. Such a two-step procedure may not be the best choice to train model parameters for forecasting purposes. An alternative approach is to calibrate the hydrological model separately for each target lead time in the presence of the updating procedure. However, it is unclear whether this approach can provide the most efficient and the most robust forecasts. We compared in this paper three approaches to calibrate the parameters of a flood forecasting model: calibration in simulation mode (i.e. without data assimilation), lead-time-dependent calibration (i.e. with data assimilation), and a procedure combining both approaches. An hourly flood forecasting model (a parsimonious hydrological model combined with a state updating assimilation procedure) was used to produce forecasts for three lead times on 687 catchments and 40,411 flood events in metropolitan France. The performance of the model calibrated with the three approaches was evaluated according to catchment response times and flood rise times. An analysis of parameter robustness was also carried out. The results showed that lead-time-dependent calibration improves performance for catchments characterised by slow temporal dynamics. However, for catchments with fast temporal dynamics, it leads to degraded performance at short lead times and reduces parameter robustness. We found that the combined calibration approach is the best compromise between parameter robustness and performance at all lead times and for all catchment and flood types.

Preparation of cellulose nanofiber/polyvinyl alcohol-based composite films for metal ion detection by starch/disodium calcium ethylenediaminetetraacetate synergistic complexation effect

Heavy metal pollution causes irreversible damage to plants, animals, and humans. Therefore, it is meaningful to develop facile, fast, and efficient strategies for heavy metal ion (HMI) detection. Here, a portable composite film (CPSE) was designed for HMI detection with high sensitivity and wide detection range. The CPSE was prepared by using cellulose nanofibers (CNF)/polyvinyl alcohol (PVA) as the matrix and utilizing modified starch (HPS) to assist disodium calcium ethylenediaminetetraacetate (EDTA-Ca) to form stable complexes with HMI. The R, G and B values (the three primary colors of light) were captured using an image acquisition system to produce an HMI standard color card successfully. Specifically, the composite film can effectively distinguish Cu2+, Pb2+ and Fe3+. The response time of the composite film to HMI was 2–4 s, and the detection ranges of Cu2+ and Fe3+ were 5–700 ppm and 10–1000 ppm, respectively. Additionally, the synergistic effect of HPS and EDTA-Ca led to the increase in tensile strength (1.59–1.71 times), tear strength (3.29–3.57 times), and glass transition temperature (~ 6 °C) compared to CNF/PVA/HPS and CNF/PVA/EDTA-Ca films. This study confirms the value of CPSE films as materials for HMI detection and suggests innovative ideas for designing similar biomass detection materials in the future.

Eu(III) encapsulation strategy to construct intelligent ratiometric luminescent sensor for efficient detection of phenylglyoxylic acid biomarker in bodily fluids

Herein, a desirable MOF-based luminescent sensor of Eu3+@ZnMOF is fabricated through post-synthesis strategy. Based on response differences of the inherent monitoring signal at 442 nm and the secondary monitoring signal at 699 nm introduced by encapsulating Eu3+ ions, the prepared Eu3+@ZnMOF displays great superior as a ratiomertic luminescent sensor with high sensitive and selective, rapid response time (less than 1 min), superior detection limit (3.89 ng·mL−1), and favorable recyclable performance (at least 6 cycles) in detecting phenylglyoxylic acid (PGA) biomarker over other urine and serum species. Furthermore, Eu3+@ZnMOF also demonstrates exceptional detectability and remarkable reliability in tracing PGA levels within actual serum and urine samples. On the basis of PGA levels controlled luminescence changes of Eu3+@ZnMOF under UV light, an intelligent detection platform is developed by integrating tandem combinational “AND” logic gates to achieve more convenient and intuitive detection of PGA levels in body fluids. Besides, photoinduced electron transfer and internal filtering effect are demonstrated to be responsible for the luminescence sensing. This work not only offers a validated strategy for the design of MOFs-based ratiometric luminescent sensors, but also presents an approach in efficient, rapid, and intelligent detection of biomarkers in body fluids.

A multifunctional and tough lotus root starch-based bio-photonic hydrogel for stretchable fabric pattern color change and water rewriting.

Photonic crystal hydrogels (PCHs) are innovative materials that translate imperceptible deformations and humidity changes into visible colors, broadening the applications of photonics in bioengineering and smart materials. To overcome poor mechanical properties of traditional PCHs limited by weak intermolecular forces, we designed a PCH with a dual-network framework comprising N-isopropylacrylamide-co-acrylamide (NIPAM-co-AM) and biomass lotus root starch (LR). Since LR is rich in hydroxyl groups, it can undergo molecular linkage entanglement with the NIPAM-co-AM hydrogel matrix, forming hydrogen bonds that significantly enhance the mechanical properties of the PCH. We have prepared PCH films capable of conveying multidimensional information about the extent and distribution of transient deformation by encapsulating magnetic photonic crystal microspheres (MPCMs) within a hydrogel matrix. The PCH films were found to have ultrafast response time (< 10 s), full-color tunable range, high spatial resolution, excellent mechanical toughness (tensile up to 0.17 MPa) and sensitivity (2.52 nm %-1), and were able to sense relative humidity (RH) from 11 % to 98 %. Equipped with a dynamically reconfigurable lattice, this dual-responsive (tensile/humidity) PCH not only facilitates the creation of water-rewritable photonic films but also holds promise for integration into structural color elastic fabrics, thereby presenting novel prospects for smart textile applications.

An estimated photocurrent controlling the inductance current of DC-DC converter for rapid MPPT pursuit with less oscillations under sudden changes in the PV chain

This paper focuses on simple technique from conventional techniques for the rapid maximum power point (MPP) pursuit with a less oscillations under sudden changes. In investigations, the controllability of the conventional boost converter model shows that the converter can be controlled from the current of its inductance (inductor). To get reference current, a conventional technique known as method of short-circuit current has been transformed to clearly establish with supporting evidence an estimated photocurrent. Different test was done on MATLAB/Simulink under irradiance, temperature and load changes. Facing the P&O and short-circuit method, the proposed method presents a response time of 11.08 ms and power variations at MPP around 0.1 Watts. A test made on another converter shows that this method can be applied on DC-DC converters where the inductor current need to be controlled for proper operation.

Optimal design and experimental testing of EMPI system for plasma disruption mitigation on J-TEXT

Plasma disruptions can cause significant damage to tokamak. Currently, the primary method for mitigating disruptions is the injection of a substantial amount of impurities. The electromagnetic injection method offers a high injection speed and rapid response time, making it a promising technique for impurity injection. The first Electromagnetic Pellet Injection System (EMPI), developed by the J-TEXT team, is capable of launching pellets at high velocities and features a specialized deceleration rail that ensures safe separation of the armature and pellet. However, this system lacks an armature recovery device and a vacuum system. In this work, a second generation EMPI has been developed, which has a vacuum system and a curved recovery rail. The curved recovery rail facilitates the smooth retrieval of the armature, enhancing the safety of the recycling process. Additionally, this new system employs an augmented rail design that improves launch performance. Test results indicate that the maximum current of the new EMPI has been reduced by approximately 60%, while the maximum launch speed has increased by around 20%.

A Flexible Self-Powered Occlusal Force Sensor Array for Assisting Oral Occlusion Reconstruction

Occlusal force is increasingly being recognized as a key parameter for evaluating masticatory motor dysfunction and the effectiveness of dental management in patients. However, the evaluation of occlusal force lacks objective quantitative assessment and reliable monitoring techniques. Here, a flexible self-powered sensor array is proposed for real-time monitoring occlusal force to further assist in oral occlusion reconstruction. Employing the triboelectric nanogenerator technology, the battery-free sensor succeeds in effectively capturing static and dynamic occlusal forces from teeth and converting them into accurate and quantitative electrical signals. With an average sensitivity of 0.72 volts per Newton and a response time of 15 milliseconds, the sensor features excellent synchronicity in electro-mechanical conversion and durability. Furthermore, the sensor array, based on complementary semicircular electrodes (15 × 15 pixels), enables the construction of visualized electrical signals mapping, which can reflect the intensity and location of occlusal force. The patterned electrical signal distribution can then be analyzed by researchers, providing a quantitative reference for clinical crown restoration. We expect this self-powered sensor array to enrich the approaches of occlusal force detection and provide valuable assistance for the reconstruction of oral occlusion.

An advanced spatial decision model for strategic placement of off-site hydrogen refueling stations in urban areas

The strategic placement of hydrogen refueling stations (HRSs) is crucial for the successful adoption of hydrogen fuel cell vehicles (HFCVs) and the promotion of sustainable urban transportation. However, existing spatial decision models using Geographic Information Systems (GIS) and Multi-Criteria Decision-Making (MCDM) often stop at generating suitability maps and rely on simplistic or arbitrary site placement methods, such as fixed service radii, without optimizing spatial distribution that overlook inherent uncertainties, limiting the effectiveness of the decision-making process. This study develops an advanced spatial decision model to handle uncertainty and optimize HRS placement in Prague, Czechia. The model integrates multiple methodologies: (i) Utilizing 21 criteria across accessibility, environmental, infrastructural, and socioeconomic dimensions, with criteria weights prioritized using the Fuzzy Analytic Hierarchy Process (FAHP) to manage uncertainty in expert judgments. GIS suitability analysis identified optimal areas, with 18.13% of Prague classified as highly suitable for HRS deployment. (ii) Implementing Fuzzy C-Means (FCM) clustering to optimize site distribution and address uncertainty in HRS placement, proposing 10 optimal locations validated by a silhouette score of 0.68. (iii) Evaluating model performance through sensitivity analysis, revealing responsiveness to criteria variations. To evaluate and rank the proposed HRS locations, we integrated a Genetic Algorithm (GA) with the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), optimizing the selection process by exploring a wider solution space. Additionally, accessibility analysis assessed emergency response coverage, ensuring efficient response times. This multi-methodological framework ensures a robust, data-driven approach to site selection, optimizing accessibility, minimizing environmental impact, and promoting sustainable urban transportation. It advances strategic infrastructure planning, sets a precedent for integrating advanced analytic techniques to handle uncertainty and automate site selection in spatial decision-making, and is adaptable to diverse urban contexts.

High-performance flexible and broadband photodetectors on paper substrates using FeSnS bimetallic sulfide nanosheets

Advancements in technology have made it easier to construct flexible broadband photodetectors for wearable devices, improving light harvesting and detecting capabilities. This work described a new study that used bimetallic sulfide nanosheets (FeSnS) to produce flexible and broadband photodetectors on paper substrates using hand-print method. A simple, economical, one-step hydrothermal technique was employed to synthesise FeSnS materials, which were characterised using XRD, UV–Vis Spectroscopy, FESEM, EDS, XPS, and UPS. Photodetection tests found that 2-FeSnS (Fe at 2 wt%) outperformed similar work on paper-based devices, with a responsivity of 32.4 mA/W under a 470 nm incident wavelength, high specific detectivity, and a response time of 1.16 s. Durability and flexibility testing validated the robustness of the device. The use of a simple hydrothermal synthesis and hand-print fabrication method to create high-performance, eco-friendly, and flexible photodetectors is novel, expanding their potential applications in wearable electronics, environmental monitoring, and low-cost disposable sensing platforms.

Research on the new control strategy of the three-phase VIENNA rectifier

Abstract The VIENNA rectifier has long been used in applications such as charging piles, and the theoretical research on its control strategy is enumerated. Compared with other circuit components, the VIENNA rectifier has fewer power components and a higher power factor, so it is applied to more application scenarios. The traditional PI control has a long start-up response time and a high overshoot, while the sliding mode control (SMC) has excellent control performance for nonlinear systems. In my article, the control mode of the VIENNA rectifier is analyzed mathematically, SMC takes controls of the current inner loop, and a new exponential reaching rate is put forward the at first improve the control process. Finally, a complete system simulation model is built to prove the superiority of the VIENNA rectifier based on an optimized SMC control strategy for each control target and the corresponding control strategy. The results show that the control effect is obviously optimized by using this method.

Rapid-response, low-detection-limit, positive-negative air pressure sensing: GaN chips integrated with hydrophobic PDMS films

Despite the importance of positive and negative pressure sensing in numerous domains, the availability of a single sensing unit adept at handling this dual task remains highly limited. This study introduces a compact optical device capable of swiftly and precisely detecting positive and negative pressures ranging from −35 kPa to 35 kPa. The GaN chip, which serves as a core component of the device, is monolithically integrated with light-emitting and light-detecting elements. By combining a deformable PDMS film coated with a hydrophobic layer, the chip can respond to changes in optical reflectance induced by pressure fluctuations. The integrated sensing device has low detection limits of 4.3 Pa and −7.8 Pa and fast response times of 0.14 s and 0.22 s for positive and negative pressure variations, respectively. The device also demonstrates adaptability in capturing distinct human breathing patterns. The proposed device, characterized by its compactness, responsiveness, and ease of operation, holds promise for a variety of pressure-sensing applications.

Vietnamese College Students’ Perception Towards Using TikTok for Independent English Speaking Practice

With the rise of digital platforms, TikTok has emerged as a popular social media platform with potential applications in English language learning. Among its features, TikTok Duet, allows users to create split-screen videos with others, presenting unique opportunities for practicing speaking skills. This study explores non-majors' perceptions of using TikTok Duet to independently improve their English speaking skills. Participants were students at an elementary English level at a private college in Vietnam, including 9 interviewees and 40 students completing questionnaires. The study indicated that most students felt TikTok Duet enhances their English speaking, pronunciation, and confidence, and even grammar and vocabulary. However, some students expressed reluctance to use TikTok Duet due to privacy concerns, limited response time and technical issues. The study suggests implementing technical support, offering privacy protection measures, and providing external incentives for students to engage with this practice.

The Response Time of the High Operating Temperature and Very Long Wavelength Type-II Superlattice InAs/InAsSb Interband Cascade Photodetectors

The Response Time of the High Operating Temperature and Very Long Wavelength Type-II Superlattice InAs/InAsSb Interband Cascade Photodetectors

Double network hydrogel confined MXene/Liquid metal by dynamic hydrogen bond for high-performance wearable sensors

Double-network (DN) hydrogels, which integrate long-chain and short-chain molecular structures, exhibit significant potential in wearable sensors due to their exemplary mechanical properties. However, conventional hydrogels often suffer from poor conductivity and low sensitivity. In this study, we develop a novel DN hydrogel (comprising polyacrylamide/sodium alginate) that encapsulates MXene (Ti3C2Tx) and liquid metal (LM). This configuration leverages the conductive properties of two-dimensional MXene and zero-dimensional liquid metal embedded within the DN hydrogel networks. The Ti3C2Tx MXene sheets enhance the binding capacity with LM by serving as a conductive bridge, thereby improving interfacial interactions and reducing hysteresis. The resultant strain sensor, fabricated from this composite DN hydrogel, achieves high sensitivity (gauge factor up to 12.84), a broad detection range (0 %-1500 %), rapid response time (262 ms), and excellent repeatability and stability. We have integrated this strain sensor into wearable flexible devices, such as contact lenses, enabling real-time monitoring of human physiological pressures.