Electronic Signal Research Articles

High-Fidelity Bioelectrodes with Bidirectional Ion-Electron Transduction Capability by Integrating Multiple Charge-Transfer Processes.

Bioelectronics is an exciting field that bridges the gap between physiological activities and external electronic devices, striving for high resolution, high conformability, scalability, and ease of integration. One crucial component in bioelectronics is bioelectrodes, designed to convert neural activity into electronic signals or vice versa. Previously reported bioelectrodes have struggled to meet several essential requirements simultaneously: high-fidelity signal transduction, high charge injection capability, strain resistance, and multifunctionality. This work introduces a novel strategy for fabricating superior bioelectrodes by merging multiple charge-transfer processes. The resulting bioelectrodes offer accurate ion-to-electron transduction for capturing electrophysiological signals, dependable charge injection capability for neuromodulation, consistent electrode potential for artifact rejection and biomolecule sensing, and high transparency for seamless integration with optoelectronics. Furthermore, the bioelectrode can be designed to be strain-insensitive by isolating signal transduction from electron transportation. The innovative concept presented in this work holds great promise for extending to other electrode materials and paves the way for the advancement of multimodal bioelectronics.

Three-phase coded triboelectric nanogenerator disk: A novel approach for generating diverse control instructions in human–machine interactions

Triboelectric nanogenerator (TENG) has been widely utilized in a variety of real-world applications such as the Internet of Things (IoT) and human–machine interactions (HMIs). However, current technologies are difficult to be implemented in the situations that require a large amount of control instructions, due to the limitation on the size and the cost of the TENG-based interface. In this paper, a sliding operation three-phase coded TENG based control disk HMI interface is developed by integrating three coded copper electrodes, polytetrafluoroethylene (PTFE) film, and electronic signal processing circuits. The three-phase coded TENG electrodes enable the ability to overcome the challenge of increasing the number of generatable control instructions. The proposed system successfully achieves thirty sensing transitions through the utilization of the three-phase patterned electrodes. To evaluate the performance of this system, four applications, including English letters typing, game control, smart home control, and authentication access control, are implemented in real-time. An embedded microcontroller with a Bluetooth interface is employed to process and transmit the triboelectric control signal. The proposed TENG control disk effectively supports all functionalities required for these applications. Overall, the successful implementation and support of these applications demonstrate the effectiveness and versatility of the proposed TENG control disk in real-world scenarios and potential environments.

Concurrent analysis of electronic and ionic nanopore signals: blockade mean and height

Electronic and ionic current signals detected concurrently by 2D molybdenum disulfide nanopores are analysed in view of detecting (bio)molecules electrophoretically driven through these nanopores. The passage of the molecules, giving rise to translocation events in the nanopores, can be assigned to specific drops in the current signals, the blockades. Such blockades are observed in both the electronic and the ionic signals. In this work, we analyze both signals separately and together by choosing specific features and applying both unsupervised and supervised learning. Two blockade features, the height and the mean, are found to strongly influence the clustering and the classification of the nanopore data, respectively. At the same time, the concurrent learning of both the electronic and ionic signatures enhance the predictability of the learning models, i.e. the nanopore read-out efficiency. The interpretation of these findings provides an intuitive understanding in optimizing the read-out schemes for enhancing the accuracy of nanopore sequencers in view of an error-free biomolecular sensing.

Study on the Emission of Connected Autonomous Vehicle Considering the Control of Electronic Throttle Opening

Aiming at the networked cruise control scenario of CAV (connected autonomous vehicle) queue, we propose a new networked cruise control strategy for CAV by introducing the average information of ET (electronic throttle) opening of the downstream vehicle group as a feedback signal. By performing linear stability analysis on the new model, we derive its linear stability conditions. Further, we design exhaustive numerical simulation experiments aiming to systematically investigate the effect of the multi-vehicle ahead electronic throttle opening average feedback signal on CAV traffic stability, fuel consumption, and key emission factors, such as CO, HC, and NOx, during the cruise control process. The results show that the feedback signal can not only significantly improve the operational stability of the CAV traffic flow but also significantly improve its fuel consumption and the emission levels of CO, HC, and NOx. When the number of CAV vehicles in the feedback signal is set to three, the levels of CO, HC, and NOx emissions as well as fuel consumption in the road system can reach a stable and optimized state.

Research on intelligent sensor for industrial hazardous gases monitoring based on Tc doped C3N using density functional theory

With the ongoing global industrialization, a considerable amount of hazardous gases is emitted into the atmospheric environment. Achieving intelligent monitoring of industrial hazardous gases is a crucial pathway toward realizing the modernization of electronic information. In this study, the use of Tc doped C3N nanosheet for the intelligent online monitoring of industrial hazardous gases (CO, NO2, O3) is firstly proposed. The doping and modification mechanism of Tc nanoparticle on the C3N surface are revealed. Simultaneously, the adsorption and sensing mechanisms of the three target gases on the surface of pure C3N and Tc doped C3N nanosheet is deeply elucidated through density of states, band structure, and differential charge density analysis. The results indicate that Tc particle can stably bind to the C3N surface, providing numerous active sites for the adsorption of target gases, enabling selective capture and scavenging of hazardous gases. Furthermore, the adsorption type for all three gases shifts from physical adsorption to physicochemical adsorption, with significant changes in the electronic signals during surface reactions, manifested by drastic alterations in the band structure and enhanced electron mobility. The adsorption capacity order for the three gases is O3 > NO2 > CO. The achievements of this work not only provide a theoretical foundation for the design and preparation of Tc doped C3N nanosensors, but also offer a new direction for environmental protection and intelligent detection in industrial applications.

Study of rutile TiO2(110) single crystal by transient absorption spectroscopy in the presence of Ce4+ cations in aqueous environment. Implication on water splitting

Ce4+ cations are commonly used as electron acceptors during the water oxidation to O2 reaction over Ir- and Ru-based catalysts. They can also be reduced to Ce3+ cations by excited electrons from the conduction band of an oxide semiconductor with a suitable energy level. In this work, we have studied their interaction with a rutile TiO2(110) single crystal upon band gap excitation by femtosecond transient absorption spectroscopy (TAS) in solution in the 350–900 nm range and up to 3.5 ns. Unlike excitation in the presence of water alone the addition of Ce4+ resulted in a clear ground-state bleaching (GSB) signal at the band gap energy of TiO2 (ca. 400 nm) with a time constant t = 4–5 ps. This indicated that the Ce4+ cations presence has quenched the e-h recombination rate when compared to water alone. In addition to GSB, two positive signals are observed and are attributed to trapped holes (in the visible region, 450–550 nm) and trapped electrons in the IR region (>700 nm). Contrary to expectation, the lifetime of the positive signal between 450 and 550 nm decreased with increasing concentrations of Ce4+. We attribute the decrease in the lifetime of this signal to electrostatic repulsion between Ce4+ at the surface of TiO2(110) and positively charged trapped holes. It was also found that at the very short time scale (<2–3 ps) the fast decaying TAS signal of excited electrons in the conduction band is suppressed because of the presence of Ce4+ cations. Results point out that the presence of Ce4+ cations increases the residence time (mobility) of excited electrons and holes at the conduction band and valence band energy levels (instead of being trapped). This might provide further explanations for the enhanced reaction rate of water oxidation to O2 in the presence of Ce4+ cations.

Early Identification of Rotten Potatoes Using an Electronic Nose Based on Feature Discretization and Ensemble Convolutional Neural Network.

The early identification of rotten potatoes is one of the most important challenges in a storage facility because of the inconspicuous symptoms of rot, the high density of storage, and environmental factors (such as temperature, humidity, and ambient gases). An electronic nose system based on an ensemble convolutional neural network (ECNN, a powerful feature extraction method) was developed to detect potatoes with different degrees of rot. Three types of potatoes were detected: normal samples, slightly rotten samples, and totally rotten samples. A feature discretization method was proposed to optimize the impact of ambient gases on electronic nose signals by eliminating redundant information from the features. The ECNN based on original features presented good results for the prediction of rotten potatoes in both laboratory and storage environments, and the accuracy of the prediction results was 94.70% and 90.76%, respectively. Moreover, the application of the feature discretization method significantly improved the prediction results, and the accuracy of prediction results improved by 1.59% and 3.73%, respectively. Above all, the electronic nose system performed well in the identification of three types of potatoes by using the ECNN, and the proposed feature discretization method was helpful in reducing the interference of ambient gases.

Photon counting detector computed tomography in pediatric cardiothoracic CT imaging

Abstract Photon-counting detector computed tomography (PCD-CT) is the most recent advancement in CT technology and has the potential to change clinical practice. Unlike conventional energy-integrated-detector (EID) that uses a two-step process to convert X-rays into a digital signal, PCD-CT directly converts photon energies into electronic signal. The advantages of PCD-CT over EID-CT are higher spatial resolution, electronic noise reduction, higher contrast-to-noise ratio, improved radiation dose efficiency, and intrinsic spectral imaging. Successful implementation into clinical practice requires adaptations in CT protocols. In this review, we summarize the basic principles of PCD-CT and technical scanning factors followed by a discussion of its clinical benefits in pediatric pulmonary and cardiovascular imaging.

Electronic signal for mechanical failure in two-dimensional g-SiC

It is non-trivial to identify mechanical failure using first-principles calculations as only long-wave phonons are used in these models due to size limitations. Here, we propose a new criterion to predict the mechanical failure by electronic bandgap closure in graphene-like two-dimensional silicon carbide (g-SiC) monolayer. The electronic bandgap decreases with strain and closes beyond the ultimate strain. This mechano-electronic coupling suggests that the onset of the zero bandgap and the correlation between electronic bandgap and ultimate strain could be used to predict the ideal mechanical failure of g-SiC monolayers.

Integrated molybdenum single atom array sensors with multichannels for nitrite detection in foods

Nitrite (NO2−) is present in a variety of foods, but the excessive intake of NO2− can indirectly lead to carcinogenic, teratogenic, mutagenicity and other risks to the human body. Therefore, the detection of NO2− is crucial for maintaining human health. In this study, an integrated array sensor for NO2− detection is developed based on molybdenum single atom material (IMSMo-SAC) using high-resolution electrohydrodynamic (EHD) printing technology. The sensor comprises three components: a printed electrode array, multichannels designed on polydimethylsiloxane (PDMS) and an electronic signal process device with bluetooth. By utilizing Mo-SAC to facilitate electron transfer during the redox reaction, rapid and efficient detection of NO2− can be achieved. The sensor has a wide linear range of 0.1 μM–107.8 mM, a low detection limit of 33 nM and a high sensitivity of 0.637 mA−1mM−1 cm−2. Furthermore, employing this portable array sensor allows simultaneously measurements of NO2− concentrations in six different foods samples with acceptable recovery rates. This array sensor holds great potential for detecting of small molecules in various fields.

Toward Direct Exploration of the Few-Femtosecond Dynamics of Electronic Coherence and Correlation in Quantum Materials Using Time- and Angle-Resolved Photoemission Spectroscopy

Over the last two decades, time- and angle-resolved photoemission spectroscopy (trARPES) has become a mature and established experimental technique for the study of ultrafast electronic and structural dynamics in materials. To date, most trARPES investigations have focused on the investigation of processes occurring on time scales of ≳30 fs, in particular, relaxation and thermalization, and have therefore been blind to the initial sub-10 fs dynamics related to electronic coherence and correlation effects. In this article, we illustrate how current trARPES setups reach their limits when it comes to addressing such extraordinarily short time scales and present an experimental configuration that provides the time, energy, and momentum resolutions required to monitor few-femtosecond dynamics on the relevant energy and momentum scales. We discuss the potential capabilities of such an experiment to study the electronic response of materials in the strong-field interaction regime at PHz frequencies and finally review a theoretical concept that may in the future even overcome the competing resolution limitations of trARPES experiments, as imposed by the time–bandwidth product of the probing laser pulse. Our roadmap for ultrafast trARPES indicates a path to break new experimental ground in quantum nonequilibrium electronic dynamics, from which new possibilities for ultrafast control of optical and electronic signals in quantum materials can be explored.

Environmental stress and emotional reactivity: an exploratory experience sampling method study.

Previous studies have shown a relationship between environments and mental health. However, limited studies have investigated the impact of environment stress (ES) on emotional reactivity. Our study aimed to fill this gap by examining how daily ES affects momentary emotional reactivity using experience sampling method (ESM). Participants were randomly recruited from a prospective cohort study in Hong Kong to participate in a 7-day ESM study. The participants received eight electronic signals daily assessing their ES, positive affect (PA) and negative affect (NA). Participants were categorized into depressed group or control group based on Revised Clinical Interview Schedule. Psychometric properties of the ESM assessment were evaluated. Multilevel linear regression analyzes were conducted to examine the association of ES with PA, NA and the group status of the participants (cases versus controls). A total of 15 participants with depression and 15 healthy controls were recruited, and 1307 momentary assessments were completed with a compliance rate of 77.8%. The depressed group demonstrated a significant increase in NA in response to ES, while the control group showed a decrease in PA. In addition, the depressed group reported a lower perception of control and interaction with their environment compared to the control group. Using ESM, a valid, reliable, and easy-to-use self-reporting tool, our findings provided valuable insights on the potential mechanisms underlying emotional responses to stressful environments.

Low-pressure gasoline direct injection system development and emissions analysis for a reciprocating two-stroke engine

This study presents the design and construction of an electronic low-pressure gasoline direct injection system for two-stroke engines, with the objective to study engine performance and the emission of exhaust polluting gases, maintaining the expectations of this type of engine. The investigation includes a test bench with an incorporated engine and the required control devices for this, as well as a gas analyzer Class 0, a computerized data acquisition and several tools for displaying and process all the electronic signals from the engine in real time. In order to manage this system, a custom electronic injection control unit has been designed and built, which allows to control the fuel injection timing and duration. This unit uses the signal from an inductive sensor installed in the crankshaft as a reference and synchronization point. Additionally, modifications have been made to the fuel feeder circuit and the electronic of the test engine, as well as to some parts of the mechanism in order to adapt them to this technology. The implementation of the engine tests is described, and the performance and operational points of the original system and those of the new injection system are evaluated.

Empowering high-dimensional optical fiber communications with integrated photonic processors

Mode-division multiplexing (MDM) in optical fibers enables multichannel capabilities for various applications, including data transmission, quantum networks, imaging, and sensing. However, high-dimensional optical fiber systems, usually necessity bulk-optics approaches for launching different orthogonal fiber modes into the optical fiber, and multiple-input multiple-output digital electronic signal processing at the receiver to undo the arbitrary mode scrambling introduced by coupling and transmission in a multi-mode fiber. Here we show that a high-dimensional optical fiber communication system can be implemented by a reconfigurable integrated photonic processor, featuring kernels of multichannel mode multiplexing transmitter and all-optical descrambling receiver. Effective mode management can be achieved through the configuration of the integrated optical mesh. Inter-chip MDM optical communications involving six spatial- and polarization modes was realized, despite the presence of unknown mode mixing and polarization rotation in the circular-core optical fiber. The proposed photonic integration approach holds promising prospects for future space-division multiplexing applications.

All-in-one smartphone imaging for visual immunobiosensing of cancer biomarker using electronic gyro-centrifuge and nanozyme

Integrated functionality that combines recognition elements and sensors on a single platform to provide real-time detection capabilities for fifth-generation biosensors is considered one of the dominant tools for addressing point-of-care testing in the community today. Inspired by gyroscope and smartphone-based sensors, we developed a portable and low-cost immunobiosensor for high-throughput detection of cancer-related markers. The main testing process was divided into two parts: blood sample preprocessing based on an electronic gyroscope and signal reading based on nanozyme and smartphone. The feasibility of a commercial electronic gyroscope for serum acquisition from whole blood samples was evaluated. In addition, PtCd nanoclusters (PtCd NCs) were used as excellent peroxidase-like nanozymes to trigger the target signal conversion of the immunosensor. PtCd NCs were able to catalyze the conversion of H2O2 to ·OH, which rapidly oxidized the colorless 3,3′,5,5′-tetramethylbenzidine (TMB) substrate to the blue Oxidized-TMB (oxTMB). Naked eye visible obvious color change and the RGB values of the color metrology system could also be read by smartphone. Prostate-specific antigen (PSA) as a model biomarker was used to validate the utility of an integrated immunoassay system to enable early cancer screening through localization of RGB values. This work focuses on convenient blood sample preprocessing and simplified serologic cancer screening steps to develop an efficient and cost-effective immunoassay platform for community and on-site point-of-care testing (POCT) in resource-limited settings.

Railway Signal Electronic Control System Based on BP Neural Network

Railway signal system is the core system of railway command train operation. After the installation of the system equipment is completed, a comprehensive test shall be carried out through joint debugging and joint testing, and the applicability of the system to the design requirements shall be generally evaluated according to the test results. This paper focuses on the research of railway signal electronic control system. Based on BP neural network, fault information can be quickly and accurately identified in a relatively short time, and accurate electronic signal control can be realized in a complex system environment. The final result of the study shows that the difference in delay error of railway signal transmission under BP neural network technology is small, there are some subtle differences in 5 different modes, but the impact is small, in mode 1, the target time value is 0.236s, The actual reflection time is 0.322s, it can be seen that the error is controlled within 0.2s, which is feasible. Through the analysis of delay error of railway signal electronic control system, BP neural network has certain advantages in railway signal transmission.

Revealing patterns in Be12O12-metal nanocages as a nitrosourea drug delivery system: DFT, SERS, solvent effects and the role of periods and groups

The use of targeted drugs has emphasized the potential of nanomaterials as carriers for decreasing therapeutic side effects, and cancer therapy has long been an area of study. In this work, we used density functional theory (DFT) and time dependent-DFT simulations to examine the decorating of different metals on Be12O12 as parameters for nitrosourea (NUA) delivery carriers. We looked at the electrical and adsorption characteristics, as well as spectrum analysis and docking. Drugs on nanocages have the potential to adsorb with less energy gap and hardness than the free drug, which could facilitate electron transfer and signal activity at the target location. The drug’s adsorption characteristics can be efficiently changed by charge transfer between the NUA and the nanocages. This study assessed metal-decorated BeO nanocages’ ability to deliver nitrosourea in both vacuum and aqueous settings, offering a logical framework for creating new nitrosourea drug carriers. The present work can be extended to investigate the effect of other various types of nanorings and nanocages to study doping effects and drug delivery carrier properties.

Linewidth characterization of a self-traceable grating by SEM

To achieve high-precision nanometrology, a self-traceable grating reference material has been reported and prepared using atom lithography and soft x-ray interference techniques (Liu et al 2021 Nanotechnology 32 175 301). In this work, we employ a Monte Carlo simulation method to investigate the scanning electron microscopy (SEM) image contrast and linewidth characterization of the grating linewidth. The 3D structure of mushroom-shaped grating lines made of multilayers (Pt, SiO2 and Si) is modeled according to transmission electron microscopy (TEM) images, enabling the SEM linescan profiles of secondary electron signals to be obtained for different values of structural linewidth parameters from Monte Carlo simulations. Using the principle of the model-based library method, a model database of Monte Carlo-simulated SEM linescan profiles is thus constructed by varying the incident electron beam conditions and the grating linewidths; then, the grating linewidth is successfully characterized using experimental SEM images. The comparison with the TEM measurement reveals that the measurement accuracy is verified to within 0.3% for the linewidth of ∼25 nm.

MnO/ZnO:Zn Thin-Film Frequency Adaptive Heterostructure for Future Sustainable Memristive Systems.

In recent years, advances in materials engineering based on adaptive electronics have found a new paradigm to optimize drawbacks in signal processing. A two-layer MnO/ZnO:Zn heterostructure envisioned for frequency adaptive electronic signal processing is synthesized by sputtering, where the use of internal states allows reconfigurability to obtain new operating modes at different frequency input signals. X-ray diffraction (XRD) analysis is performed on each layer, revealing a cubic structure for MnO and a hexagonal structure for ZnO:Zn with preferential growth in [111] and [002] directions, respectively. Scanning electron microscope (SEM) micrographs show that the surface of both materials is homogeneous and smooth. The thickness for each layer is determined to be approximately 106.3 nm for MnO, 119.3 nm for ZnO:Zn and 224.1 nm for the MnO/ZnO:Zn structure. An electrical characterisation with an oscilloscope and signal generator was carried out to obtain the time-response signals and current-voltage (I-V) curves, where no degradation is detected when changing frequencies within the range of 100 Hz to 1 MHz. An equivalent circuit is proposed to explain the effects in the interface. Measurements of switching speeds from high resistance state (HRS) to low resistance state (LRS) at approximately 17 ns, highlight the device's rapid adaptability, and an estimated switching ratio of approximately 2 × 104 indicates its efficiency as a memristive component. Finally, the MnO/ZnO:Zn heterojunction delivers states that are stable, repeatable, and reproducible, demonstrating how the interaction of the materials can be utilised in adaptive device applications by applying frequencies and internal states to create new and innovative design schematics, thus reducing the number of components/connections in a system for future sustainable electronics.

Electronic Information System Signal Noise for Noise Reduction using Variational Bayesian based Robust Adaptive Filter

The most significant issues for a thousand users is the unwanted or loud signals in sound files, it is impossible to eliminate or minimize these noise signals without knowledge their types and ranges. To overcome this issue, present an Electronic Information System Signal Noise for Noise Reduction using Variational Bayesian based Robust Adaptive Filter (EIS-SNR-VBRAF) is proposed. Initially, the data is collected from Adaptive Myriad Filter using Time-Varying Noise and Signal-Dependent Parameters dataset. Then, the data is given for Pre-processing section, Variational Bayesian based Robust Adaptive Filter (VBRAF) is used to reduce the signal noise from Gaussian Noise, Traffic noise and Audio signal back ground noise. The proposed technique is implemented and efficacy of EIS-SNR-VBRAF technique is assessed by support of numerous performances such as BER, Signal-to-Noise-Ratio (SNR), Mean Squared Error, Peak Signal-to-Noise Ratio (PSNR), Root Mean Square Error, Structural Similarity Index, Cross-Correlation and Computational Complexity is analyzed. The proposed EIS-SNR-VBRAF method attains 21.18%, 23.52% and 23.65% lower RMSE, 21.52%, 21.76% and 23.24% higher PSNR, 21.19%, 21.73% and 20.48% higher Structural Similarity Index are compared with existing methods like early detection of mechanical malfunctions in vehicles utilizing sound signal processing (ED-MMV-SSP),noise reduction in infrasound signals based on mask coefficient binary weighting generalized cross correlation non-negative matrix factorization algorithm (NRID-MCWG-NMFA) and Click-event sound detection in automotive industry using machine/deep learning (CE-SDSI-DL) respectively.