Speed Signal Research Articles

Sensors on Flapping Wings (SOFWs) Using Complementary Metal–Oxide–Semiconductor (CMOS) MEMS Technology

This article presents a framework of using MEMS sensors to investigate unsteady flow speeds of a flapping wing or the new concept of sensors on flapping wings (SOFWs). Based on the implemented self-heating flow sensor using U18 complementary metal–oxide–semiconductor (CMOS) MEMS foundry provided by the Taiwan Semiconductor Research Institute (TSRI), the compact sensing region of the flow sensor was incorporated for in situ diagnostics of biomimetic flapping issues. The sensitivity of the CMOS MEMS flow sensor, packaged with a parylene coating of 10 μm thick to prolong the lifetime, was observed as −3.24 mV/V/(m/s), which was below the flow speed of 6 m/s. A comprehensive investigation was conducted on integrating CMOS MEMS flow sensors on the leading edge of the mean aerodynamic chord (m.a.c.) of the flexible 70-cm-span flapping wings. The interpreted flow speed signals were checked and demonstrated similar behavior with the (net) thrust force exerted on the flapping wing, as measured in the wind tunnel experiments using the force gauge. The experimental results confirm that the in situ measurements using the concept of SOFWs can be useful for measuring the aerodynamic forces of flapping wings effectively, and it can also serve for future potential applications.

Features of Generation, Propagation and Application of Special Ultrasonic Impulses in Viscous Liquids

An exact numerical and approximate analytical description of solitary acoustic pulses with a large difference in spatial gradients of parameters in different directions has been obtained in viscous liquids using this small parameter. The method of special initial-boundary conditions obtained during analyzing the hydrodynamic equations has been applied to describe the peculiarities of this nonlinear phenomenon. Waves of this type exist in the presence of two- or three-dimensional inhomogeneity of the initial disturbances and retain a spatial structure along the direction of propagation when traveling long distances. At the same time, it is possible to regulate the pressure drop and the speed of the acoustic signal, which creates unique conditions for a special force effect or information transmission. The efficiency of their use in such processes as metal dissolution, solvent extraction and mass transfer under the conditions of resonance exposure of ultrasound was evaluated. Fine details of exciting the nonlinear impulse with the necessary properties have been analyzed to demonstrate a possible way to a new technology of successfully treating any different specimens, materials and constructions for a long distance between the source of radiation and the position of the treatment. The use of such pulses opens up new opportunities for remote acoustic force impact on various objects, as well as for the transmission of information.

State estimation of magnetorheological suspension of all-terrain vehicle based on a novel adaptive Sage–Husa Kalman filtering

Abstract For the magnetorheological suspension control system of all-terrain vehicles (ATVs), state estimation is an effective method to obtain system feedback signals that cannot be directly measured by sensors. However, when confronted with modeling errors and sudden changes in sensor noise during complex road driving, conventional estimation methods with fixed parameters encounter challenges in accurately estimating the states of ATV suspension system. To address this issue, this paper introduces a novel adaptive Sage–Husa Kalman filter (ASHKF) algorithm to estimate the sprung and unsprung velocity of ATV suspension system. The algorithm uses exponential weighting function and gradient detection function to adaptively adjust the attenuation coefficient according to the driving conditions of the ATV, thereby realizing real-time correction of the covariance matrix of the prediction error. Ultimately, through simulation and real-vehicle testing, it is demonstrated that the designed ASHKF is able to effectively improve the state estimation accuracy of the speed signal of the suspension system under off-road driving conditions with low-frequency noise and outlying disturbances, and the accuracy is improved by 62.70% compared with that of the conventional Sage–Husa Kalman filter (SHKF).

Model predictive control for energy efficient AC motor drives: An overview

AbstractState‐of‐the‐art model‐based predictive control techniques for AC motor drives are reviewed in this paper. A plethora of MPC algorithms with vast number of complex ideas has emerged in the last decade and this work makes an attempt to present those concepts in an intuitive, comprehensive and hierarchical manner. More emphasis is laid on finite control set model predictive control (FCS‐MPC) methods, especially predictive torque control (PTC) and predictive current control (PCC) because of their emergence as the prime focus of ongoing research in energy efficient drive control. The main focus of this review is to analyse the most recent work, signpost the future research directions, identify the core challenges and consolidate the ideas into a coherent and concise reference. A comprehensive classification based on actuation signals is presented and reviewed in detail. Then, the important challenges in MPC implementation, such as computational complexity reduction and delay compensation, weighting factor selection for multi‐objective cost functions, steady state performance and ripple reduction, parameter variations/model mismatching and achieving extended prediction horizons, are surveyed and most relevant solutions are reviewed. A detailed analysis of the last five years related work is given at the end and it is concluded that the future course seems to be diverting towards voltage vector selection with optimised phase, magnitude and duty ratios. Computational burden is still one of the main hurdle towards MPC proliferation and adaptation in AC drive control at the industrial level. However, with advent of high speed and cheaper signal processors and development of efficient algorithms, MPC is rapidly becoming the control method of choice for energy‐efficient drive control.

A link-based flow model with turn-level queue transmission and time-varying free-flow speed for urban road networks

Macroscopic link-based flow models are efficient for simulating flow propagation in urban road networks. Existing link-based flow models described traffic states of a link with two state variables of link inflow and outflow and assumed homogeneous traffic states within a whole link. Consequently, the turn-level queue length change within the link cannot be captured accurately, resulting in underrepresented queue spillback. Moreover, a constant link free-flow speed was assumed to formulate models, restricting their applicability in modeling phenomena involving time-varying free-flow speed. This study proposed a new link-based flow model by introducing an additional state variable of link queue inflow and adapting the link outflow to be free-flow speed-dependent. In our model, the vehicle propagation within each link is described by the link inflow, queue inflow, and outflow, which depends on the link free-flow speed changes and signal control. A node model is further defined to capture the presence of potential queue spillback, which estimates the constrained flow propagation between adjacent road segments. Simulation experiments were conducted on a single intersection and on networks to verify the proposed model performance. Results demonstrate the predictive power of the proposed model in simulating traffic proppagations for networks with multiple turning movements and time-varying free-flow speed. Our model outperforms the baseline link-based flow model while preserving the computational tractability property of link-based flow models.

Fault detection of RV reducer cycloidal gear under robot working conditions based on optimization improved envelope spectrum sideband energy ratio

Abstract Under industrial robot operating conditions, the cycloidal gear in the rotary vector (RV) reducer in the robot joint runs in a compound rotation motion with a low-speed and incomplete cycle, which complicates the fault detection for the cycloidal gear. Until now, no effective detection method for the cycloidal gear tooth fault under industrial robot operating conditions has been reported. Consequently, a method based on optimization improved envelope spectrum (IES) sideband energy ratio is proposed in this paper. Firstly, encoder signals are acquired and used to estimate the instantaneous angular speed signals, which are then separated into two sets of data based on rotation directions. Then, the data corresponding to the approximately stable speed is truncated and connected to form a constructed signal. Next, the coherence of the constructed signal is calculated using the fast spectral coherence algorithm. Subsequently, the IES sideband energy ratio is used as the objective value, and a global optimization algorithm is employed to determine the integration frequency band of the IES. Finally, the IES of this frequency band is calculated to obtain the fault-related order characteristics. An RV reducer test rig was used for the experiment, and the analysis results from the proposed approach, cyclic spectral coherence, and IES via feature optimization-gram were contrasted. Experiment results show that the proposed method is valid for the detection of tooth faults in the cycloidal gear of the RV reducer in robot operating conditions.

A novel extraction method for combustion feature of CI engine in electric hybrid power based on engine instantaneous speed

Hybrid power systems represent a crucial avenue for the advancement of vehicle power, offering a novel framework and context for the intelligent evolution of internal combustion engines. The governance of internal combustion engines stands as the cornerstone of power intelligence, with in-cylinder combustion control serving as a pivotal research focus within the realm of internal combustion engine regulation. The accurate assessment of cylinder state in hybrid power systems forms the foundation for effective in-cylinder combustion control. This paper introduces an approach to extract cylinder combustion state (cylinder work and CA50) based on instantaneous speed signals. First, the instantaneous speed signal undergoes processing using synthetic speed algorithms, followed by an evaluation of algorithm effectiveness. Subsequently, the theoretical derivation of the relationship between synthesized speed signals and cylinder state is established based on conservation of energy principles, leading to a method for extracting cylinder state. Finally, experimental validation is conducted at 270 steady-state operating points (varied speeds and load ratios) and 2 dynamic processes to verify prediction accuracy using the proposed method. The results demonstrate precise prediction capabilities for both cylinder work and CA50, with prediction errors falling within ≤10 % for CA50 and ≤9 % for cylinder work; moreover, 97 % of steady-state operating points exhibit error ranges within 5 % or less and the average error of dynamic process is 5 %.

A New Method of Intelligent Fault Diagnosis of Ship Dual-Fuel Engine Based on Instantaneous Rotational Speed

Ship engine misfire faults not only pose a serious threat to the safe operation of ships but may also cause major safety accidents or even lead to ship paralysis, which brings huge economic losses. Most traditional fault diagnosis methods rely on manual experience, with limited feature extraction capability, low diagnostic accuracy, and poor adaptability, which make it difficult to meet the demand for high-precision diagnosis. To this end, a fusion intelligent diagnostic model—ResNet–BiLSTM—is proposed based on a residual neural network (ResNet) and a bidirectional long short-term memory network (BiLSTM). Firstly, a multi-scale decomposition of the instantaneous rotational speed signal of a ship’s engine is carried out by using the continuous wavelet transform (CWT), and features containing misfire fault information are extracted. Subsequently, the extracted features are fed into the ResNet–BiLSTM model for learning. Finally, the intelligent diagnosis of ship dual-fuel engine misfire faults is realized by the classifier. The model combines the advantages of ResNet18 in image feature extraction and the capability of BiLSTM in temporal information processing, which can efficiently capture the time-frequency features and dynamic changes in the fault signal. Through comparison experiments with fusion models AlexNet–BiLSTM, VGG–BiLSTM, and the existing AlexNet–LSTM and VGG–LSTM models, the results show that the ResNet–BiLSTM model outperforms the other models in terms of diagnostic accuracy, robustness, and generalization ability. This model provides an effective new method for intelligent diagnosis of ship dual-fuel engine misfire faults to solve the traditional diagnostic methods’ limitations.

Vibration analysis of push-the-bit rotary steerable bottom hole assembly

With the development of oil and gas fields to the deep-sea, the rotary steerable system is widely used. Downhole vibration is an important factor affecting the performance of rotary steerable system. Currently, the lack of research on vibration during operation of rotary steerable system has affected the development of deep-sea oil and gas field development technology. In this paper, the dynamic model of the push-pull rotary steerable system is established based on the similarity principle. The model includes Bit-rock interaction model, Drillstring-borehole contact model and guiding force model of rotary steerable system, the trajectory and vibration of drill bit under different guiding forces are simulated. Then, the actual drilling experiment of the full-scale Push-The-Bit Rotary Steerable System (PTB-RSS) in the horizontal section is carried out. The acceleration and speed signals of the push-pull rotary steerable system in the process of applying guiding force are collected and verified with the calculation results of the dynamic model. It is found that the vibration frequency and amplitude of the Bottom Hole Assembly (BHA) gradually increase with the increase of the guiding force of the PTB-RSS during the drilling stage, which induce high-frequency torsional vibration to a certain extent. In addition, the dynamic simulation shows that when the guiding force of the rotary steerable system is increased to a certain extent, the vibration of the BHA gradually stabilizes, but the vibration amplitude does not decrease.

Encoding of Global Visual Motion in the Avian Pretectum Shifts from a Bias for Temporal-to-Nasal Selectivity to Omnidirectional Excitation across Speeds.

The pretectum of vertebrates contains neurons responsive to global visual motion. These signals are sent to the cerebellum, forming a subcortical pathway for processing optic flow. Global motion neurons exhibit selectivity for both direction and speed, but this is usually assessed by first determining direction preference at intermediate velocity (16-32°/s) and then assessing speed tuning at the preferred direction. A consequence of this approach is that it is unknown if and how direction preference changes with speed. We measured directional selectivity in 114 pretectal neurons from 44 zebra finches (Taeniopygia guttata) across spatial and temporal frequencies, corresponding to a speed range of 0.062-1,024°/s. Pretectal neurons were most responsive at 32-64°/s with lower activity as speed increased or decreased. At each speed, we determined if cells were directionally selective, bidirectionally selective, omnidirectionally responsive, or unmodulated. Notably, at 32°/s, 60% of the cells were directionally selective, and 28% were omnidirectionally responsive. In contrast, at 1,024°/s, 20% of the cells were directionally selective, and nearly half of the population was omnidirectionally responsive. Only 15% of the cells were omnidirectionally excited across most speeds. The remaining 85% of the cells had direction tuning that changed with speed. Collectively, these results indicate a shift from a bias for directional tuning at intermediate speeds of global visual motion to a bias for omnidirectional responses at faster speeds. These results suggest a potential role for the pretectum during flight by detecting unexpected drift or potential collisions, depending on the speed of the optic flow signal.

Fuzzy PID control based on variable universe for PMSM

Abstract This paper aims to design a speed controller for PMSM so that the motor can track the given speed signal. Based on vector control strategy, united with SVPWM (Space Vector Pulse Width Modulation) technology, an on-off of inverter switches was regularly controlled to form the vector voltage to drive PMSM. Finally, the PMSM double closed-loop vector control system was built. Specifically, by the design of the speed controller method, a fuzzy PID control, according to the variable universe, was proposed to realize the high precision control requirements of the PMSM speed control system. Firstly, on the ground of the traditional PID controller, a fuzzy controller was introduced to realize the self-tuning of control parameters, and then a new function variable domain module was built to reach the self-adjustment of the fuzzy controller domain and to achieve self-tuning of control rules, improving control accuracy and response speed.

Evaluation of ultrasonic and mechanical methods for assessing dentin demineralization in children's permanent teeth in vitro

Relevance. With the advent of advanced methods for functional diagnostics, dentists have gained new opportunities for detecting carious lesions. However, the diagnostic sensitivity of these methods requires further investigationPurpose. To evaluate the condition of intact and demineralized dentin in children's permanent teeth using both ultrasonic and mechanical methods.Materials and methods. Divided cross-section" models were created from premolars extracted from children for orthodontic purposes. After a 20-day exposure to a demineralizing buffer solution with a pH of 4.5, both the intact and demineralized dentin cross-sections were tested using ultrasonic and mechanical methods.Results. Statistically significant differences were observed in the mean ultrasonic signal speed C between two independent sample groups: intact dentin (Group 1) and demineralized dentin (Group 2), based on Mann-Whitney U-test calculations (p = 0.01). In Group 2, the mean value of C was 27% lower compared to Group 1. Additionally, significant differences were found in the mean ultimate strength σ between two independent groups: intact dentin (Group 3) and demineralized dentin (Group 4), with Group 4 showing a 29.5% reduction in the mean σ value, according to Mann-Whitney U-test calculations (p = 0.01).Conclusion. Demineralization leads to significant changes in both the ultrasonic and mechanical properties of dentin. Statistical analysis of the laboratory test results using the "divided cross-section" model supports the effectiveness and diagnostic sensitivity of the methods applied for evaluating the extent of dentin demineralization.

Evaluation of the Antibacterial Activity of Antibiotics with different Antibacterial Mechanisms using Electrochemical Signals of Heat‐Treated Escherichia Coli

AbstractElectrochemistry with purines as indicators may be a promising new method for antibiotic activity testing. However, the traditional electrochemical detection method (S‐LSV) requires a long accumulation time for purines and has low signal intensity. High‐temperature treatment of bacterial samples may significantly enhance the signal intensity and speed of detection. However, this process may also impact the structure and metabolism of bacteria. Further research is necessary to determine how electrochemical signals respond to antibiotic antibacterial activity. In this paper, the electrochemical detection method based on heat‐treated Escherichia coli (E. coli, H‐LSV) was used to investigate the effects of 11 antibiotics with four different antibacterial mechanisms on the electrochemical behavior of E. coli. The results showed that compared to the S‐LSV, the electrochemical signal of E. coli detected by the H‐LSV increased by 362%, and showed a strong linear relationship with bacterial counts up to 1.88×108 CFU/mL, with a detection limit of 1.15×106 CFU/mL. The electrochemical signal consistently correlated with changes in viable E. coli counts following treatment with the four different antibacterial mechanisms. HPLC analysis further confirmed that the changes in purine contents in bacteria after antibiotic treatment were consistent with the trends in electrochemical signals. The evaluation of antibiotic antibacterial ability by H‐LSV showed good consistency with results from plate counting and turbidity methods, but was closer to the results of plate counting. The inhibition rates of antibiotics on E. coli detected by H‐LSV and S‐LSV also showed high consistency, indicating that short‐term high‐temperature treatment of E. coli did not affect the response of the bacterium to the inhibitory activity of antibiotics.

Noise reduction method for mine wind speed sensor data based on CEEMDAN-wavelet threshold

The mine wind speed sensor is an important intelligent sensing equipment in the mine intelligent ventilation system that can provide accurate and key wind speed parameters for the intelligent ventilation system. The turbulent pulsation characteristics of the airflow in the underground tunnel are a major factor for the inaccurate measurement of mine wind speed. Therefore, according to the random non-stationary characteristics of a turbulent pulsation signal, a denoising method based on adaptive complete ensemble empirical mode decomposition (CEEMDAN) combined with the wavelet threshold is proposed for suppressing the turbulent pulsation noise in the wind speed signal. First, the CEEMDAN algorithm is used for decomposing the wind speed signal into a series of IMF components. Second, the continuous mean square error criterion is used for determining the high-frequency IMF components with more noise. The wavelet threshold denoising method is used for denoising the high-frequency IMF components with more noise. Finally, the denoised IMF components and remaining low-frequency IMF components are reconstructed for obtaining the denoised signal. The results of the denoising analysis of measured turbulent pulsation signals, comparative analysis of denoising of simulated turbulent pulsation signals by different joint denoising methods, and denoising analysis of actual mine wind speed sensor data indicate that the joint denoising method proposed in this study has a higher signal-to-noise ratio and lower root mean square error of the wind speed signal after denoising. Compared with the EMD-wavelet threshold and EEMD-wavelet threshold denoising methods, the denoising method proposed in this study is better and has higher denoising accuracy, which provides a new method for processing actual mine wind speed sensor data.

Research for an enhanced fault-tolerant solution against the current sensor fault types in induction motor drives

Introduction. Recently, three-phase induction motor drives have been widely used in industrial applications; however, the feedback signal failures of current sensors can seriously degrade the operation performance of the entire drive system. Therefore, the motor drives require a proper solution to prevent current sensor faults and improve the reliability of the motor drive systems. The novelty of the proposed research includes integrating the current sensor fault-tolerant control (FTC) function according to enhanced technique into the field-oriented control loop for speed control of the motor drive system. Purpose. This research proposes a hybrid method involving a third difference operator and signal comparison algorithm to diagnose various types of current sensor faults as a positive solution to enhance the stability of the induction motor drive system. Methods. A hybrid method involving a third difference operator for the measured speed signals and a comparison algorithm between measured and estimated current signals are proposed to diagnose the current sensors’ health status in the fault-tolerant process. After determining the faulty sensor, the estimated current signals based on the Luenberger observer are used immediately to replace the defective sensor signal. Results. The current sensor is simulated with various failure types, from standard to rare failures, to evaluate the performance of the FTC method implemented in the MATLAB/Simulink environment. Simultaneously, a fault flag corresponding to a defective sensor should be presented as an indicator to execute the repair process for faulty sensors at the proper time. Practical value. Positive results have proven the feasibility and effectiveness of the proposed FTC integrated into the speed controller to improve reliability and ensure the stable operation of the induction motor drive system even under current sensor fault conditions. References 29, tables 3, figures 10.

Dynamic Network-Level Traffic Speed and Signal Control in Connected Vehicle Environment.

The advent of connected vehicles holds significant promise for enhancing existing traffic signal and vehicle speed control methods. Despite this potential, there has been a lack of concerted efforts to address issues related to vehicle fuel consumption and emissions during travel across multiple intersections controlled by traffic signals. To bridge this gap, this research introduces a novel technique aimed at optimizing both traffic signals and vehicle speeds within transportation networks. This approach is designed to contribute to the improvement of transportation networks by simultaneously addressing issues related to fuel consumption and pollutant emissions. Simulation results vividly illustrate the pronounced the effectiveness of the proposed traffic signal and vehicle speed control methods of alleviating vehicle delay, reducing stops, lowering fuel consumption, and minimizing CO2 emissions. Notably, these benefits are particularly prominent in scenarios characterized by moderate traffic density, emphasizing the versatility and positive impact of the method across varied traffic conditions.

MRI findings and clinical testing for preoperative diagnosis of long head of the biceps pathology.

Determine whether combining magnetic resonance imaging (MRI) observations and clinical tests could substantially improve sensitivity for diagnosis of long head of the biceps tendon (LHBT) pathology. The authors retrospectively assessed a consecutive series of 140 patients who underwent arthroscopic rotator cuff repair for isolated supraspinatus tears. The presence of LHBT pathology was assessed preoperatively on MRI using three criteria and four clinical tests specific to shoulder injuries. Binary outcomes of MRI observations and four clinical tests were combined to identify combinations resulting in the best sensitivity using intra-operative arthroscopic findings as reference. The study cohort comprised 100 shoulders (58 men and 42 women) aged 56.6 ± 9.4 years (range, 30-76) at index surgery. A total of 29 combinations were tested to obtain the best diagnostic algorithm for LHBT pathologies. Only four combinations reached a sensitivity ≥0.75, but had a specificity <0.45. The 'Speed or Signal' combination achieved the highest sensitivity (Se: 0.88; 95% confidence interval [CI]: 0.73%-0.96%; Sp: 0.20; 95% CI: 0.10%-0.33%). The most important findings of this study were that, for the diagnosis of LHBT pathology using clinical tests alone, the Speed test had the highest sensitivity (Se, 0.74), and using MRI observations alone, the signal intensity had the highest sensitivity (Se, 0.68). Combination of 'Speed test or Signal intensity' substantially improved the sensitivity (Se, 0.88) but yielded the lowest specificity (Sp, 0.20). The clinical relevance of these findings is that using the combination 'Speed or Signal' for preoperative diagnosis, 88% of pathologic LHBTs would be correctly diagnosed, while 80% of healthy LHBTs could be misdiagnosed as pathologic. Diagnostic study, Level IV.

Improved Performance of the Permanent Magnet Synchronous Motor Sensorless Control System Based on Direct Torque Control Strategy and Sliding Mode Control Using Fractional Order and Fractal Dimension Calculus

This article starts from the premise that one of the global control strategies of the Permanent Magnet Synchronous Motor (PMSM), namely the Direct Torque Control (DTC) control strategy, is characterized by the fact that the internal flux and torque control loop usually uses ON–OFF controllers with hysteresis, which offer easy implementation and very short response times, but the oscillations introduced by them must be cancelled by the external speed loop controller. Typically, this is a PI speed controller, whose performance is good around global operating points and for relatively small variations in external parameters and disturbances, caused in particular by load torque variation. Exploiting the advantages of the DTC strategy, this article presents a way to improve the performance of the sensorless control system (SCS) of the PMSM using the Proportional Integrator (PI), PI Equilibrium Optimizer Algorithm (EOA), Fractional Order (FO) PI, Tilt Integral Derivative (TID) and FO Lead–Lag under constant flux conditions. Sliding Mode Control (SMC) and FOSMC are proposed under conditions where the flux is variable. The performance indicators of the control system are the usual ones: response time, settling time, overshoot, steady-state error and speed ripple, plus another one given by the fractal dimension (FD) of the PMSM rotor speed signal, and the hypothesis that the FD of the controlled signal is higher when the control system performs better is verified. The article also presents the basic equations of the PMSM, based on which the synthesis of integer and fractional controllers, the synthesis of an observer for estimating the PMSM rotor speed, electromagnetic torque and stator flux are presented. The comparison of the performance for the proposed control systems and the demonstration of the parametric robustness are performed by numerical simulations in Matlab/Simulink using Simscape Electrical and Fractional-Order Modelling and Control (FOMCON). Real-time control based on an embedded system using a TMS320F28379D controller demonstrates the good performance of the PMSM-SCS based on the DTC strategy in a complete Hardware-In-the-Loop (HIL) implementation.

Core-shell architecture and channel suppression: unleashing the potential of SC_RCS_DGJLFET

In this investigation, a suppressed channel-rectangular core–shell double gate junctionless field effect transistor (SC_RCS_DGJLFET) is simulated to enhance the junctionless device’s performance. This study leverages a core–shell architecture and channel suppression technique to improve the gate controllability over the channel region which helps in substantial depletion of the shells in the OFF state of the device. When compared to conventional double gate JLFETs (C_DGJLFET) and rectangular core–shell double gate JLFETs (RCS_DGJLFET), the performance of the SC_RCS_DGJLFET is superior in terms of IOFF, ION/IOFF ratio, DIBL and subthreshold slope (SS). The SC_RCS_DGJLFET achieves an ultra-low IOFF of 7.033 × 10−16 A, indicating a low leakage current with an impressive ION/IOFF = 5.092 × 1011 . Other performance parameters such as subthreshold slope and DIBL has also been improved for the SC_RCS_DGJLFET device. Subthreshold slope has been decresesd by 4.76% whereas the DIBL decreased by 33.82% when compared to existing RCS_DGJLFET. Additionally, to analyze the effect of doping on the device performance, the core doping in SC_RCS_DGJLFET is varied for fixed shell doping. The study found that fixing core doping to an appropriate value is a crucial parameter to achieve good device performance. The impact of variation of oxide extension towards the source and drain LextS/LextD in SC_RCS_DGJLFET is also studied for the first time in the core–shell architecture which has further improved the device’s performance. Finally, a CMOS inverter is designed using the proposed device that provides valuable insights into its suitability for digital circuit applications and verifies its performance benefits compared to existing transistor technologies. The SC_RCS_DGJLFET based CMOS inverter shows a sharp transition in voltage transfer characteristics (VTC), indicating fast switching speed and precise signal processing capabilities when compared to a CMOS inverter based on a conventional double gate junctionless field effect transistor (C_DGJLFET). Moreover, the transient characteristics of the SC_RCS_DGJLFET based CMOS inverter exhibit an improved output voltage swing, suggesting enhanced dynamic behaviour and stability during logic state transitions.

Navigating Complex Process and Design Challenges in Hybrid Bonding for Advanced Semiconductor Integration: A Comprehensive Analysis

Abstract In advanced electronic systems, achieving top-tier interconnect interfaces with fine-pitch integration is of paramount importance. Among interconnect options, hybrid bonding is the preeminent choice given its exceptional capacity for accommodating a high input/output (I/O) count, which facilitates high-density memory integration, increased power delivery, and enhanced signal speed. One key technique for ensuring utmost quality in hybrid bonding involves embedding Cu interconnects within the dielectric layer. Equally pivotal is surface planarization, accomplished through chemical mechanical polishing (CMP), which encompasses a meticulous two-step procedure, commencing with copper bulk CMP and culminating in barrier CMP. The latter step is particularly critical, yielding the indispensable surface finish required for a successful hybrid bonding process. Several crucial surface properties significantly influence overall bond yield, including a copper recess (“dishing”) in the vias, erosion and roughness of the dielectric layer, and surface topography changes from high-density to low-density copper vias. To optimize these parameters, a comprehensive understanding of the interconnect layer's design is essential. Here, we delve into the ramifications of via scaling, ranging from 5 to 1 µm, on dishing and roll-off, and the effects of copper via density variation, spanning from 16% to 13%, on topography. Furthermore, we explore how incorporation of dummy vias impacts the final surface finish, potentially leading to improved bond yie