Vertical organic electrochemical transistors for complementary circuits.

Organic electrochemical transistors (OECTs) and OECT-based circuitry offer great potential in bioelectronics, wearable electronics and artificial neuromorphic electronics because of their exceptionally low driving voltages (<1 V), low power consumption (<1 µW), high transconductances (>10 mS) and biocompatibility1-5. However, the successful realization of critical complementary logic OECTs is currently limited by temporal and/or operational instability, slow redox processes and/or switching, incompatibility with high-density monolithic integration and inferior n-type OECT performance6-8. Here we demonstrate p- and n-type vertical OECTs with balanced and ultra-high performance by blending redox-active semiconducting polymers with a redox-inactive photocurable and/or photopatternable polymer to form an ion-permeable semiconducting channel, implemented in a simple, scalable vertical architecture that has a dense, impermeable top contact. Footprint current densities exceeding 1 kA cm-2 at less than ±0.7 V, transconductances of 0.2-0.4 S, short transient times of less than 1 ms and ultra-stable switching (>50,000 cycles) are achieved in, to our knowledge, the first vertically stacked complementary vertical OECT logic circuits. This architecture opens many possibilities for fundamental studies of organic semiconductor redox chemistry and physics in nanoscopically confined spaces, without macroscopic electrolyte contact, as well as wearable and implantable device applications.

Stretchable Electronics with Strain-Resistive Performance.

Stretchable electronics have attracted tremendous attention amongst academic and industrial communities due to their prospective applications in personal healthcare, human-activity monitoring, artificial skins, wearable displays, human-machine interfaces, etc. Other than mechanical robustness, stable performances under complex strains in these devices that are not for strain sensing are equally important for practical applications. Here, a comprehensive summarization of recent advances in stretchable electronics with strain-resistive performance is presented. First, detailed overviews of intrinsically strain-resistive stretchable materials, including conductors, semiconductors, and insulators, are given. Then, systematic representations of advanced structures, including helical, serpentine, meshy, wrinkled, and kirigami-based structures, for strain-resistive performance are summarized. Next, stretchable arrays and circuits with strain-resistive performance, that integrate multiple functionalities and enable complex behaviors, are introduced. This review presents a detailed overview of recent progress in stretchable electronics with strain-resistive performances and provides a guideline for the future development of stretchable electronics.

Eddy Current Array for Defect Detection in Finely Grooved Structure Using MSTSA Network.

In this paper, we focus on eddy current array (ECA) technology for defect detection in finely grooved structures of spinning cylinders, which are significantly affected by surface texture interference, lift-off distance, and mechanical dither. Unlike a single eddy current coil, an ECA, which arranges multiple eddy current coils in a specific configuration, offers not only higher accuracy and efficiency for defect detection but also the inherent properties of space and time for signal acquisition. To efficiently detect defects in finely grooved structures, we introduce a spatiotemporal self-attention mechanism to ECA testing, enabling the detection of defects of various sizes. We propose a Multi-scale SpatioTemporal Self-Attention Network for defect detection, called MSTSA-Net. In our framework, Temporal Attention (TA) and Spatial Attention (SA) blocks are incorporated to capture the spatiotemporal features of defects. Depth-wise and point-wise convolutions are utilized to compute channel weights and spatial weights for self-attention, respectively. Multi-scale features of space and time are extracted separately in a pyramid manner and then fused to regress the bounding boxes and confidence levels of defects. Experimental results show that the proposed method significantly outperforms not only traditional image processing methods but also state-of-the-art models, such as YOLOv3-SPP and Faster R-CNN, with fewer parameters and lower FLOPs in terms of Recall and F1 score.

Image Registration for Visualizing Magnetic Flux Leakage Testing under Different Orientations of Magnetization.

The Magnetic Flux Leakage (MFL) visualization technique is widely used in the surface defect inspection of ferromagnetic materials. However, the information of the images detected through the MFL method is incomplete when the defect (especially for the cracks) is complex, and some information would be lost when magnetized unidirectionally. Then, the multidirectional magnetization method is proposed to fuse the images detected under different magnetization orientations. It causes a critical problem: the existing image registration methods cannot be applied to align the images because the images are different when detected under different magnetization orientations. This study presents a novel image registration method for MFL visualization to solve this problem. In order to evaluate the registration, and to fuse the information detected in different directions, the mutual information between the reference image and the MFL image calculated by the forward model is designed as a measure. Furthermore, Particle Swarm Optimization (PSO) is used to optimize the registration process. The comparative experimental results demonstrate that this method has a higher registration accuracy for the MFL images of complex cracks than the existing methods.

Multi-wave and hybrid imaging techniques: a new direction for nondestructive testing and structural health monitoring.

In this article, the state-of-the-art multi-wave and hybrid imaging techniques in the field of nondestructive evaluation and structural health monitoring were comprehensively reviewed. A new direction for assessment and health monitoring of various structures by capitalizing the advantages of those imaging methods was discussed. Although sharing similar system configurations, the imaging physics and principles of multi-wave phenomena and hybrid imaging methods are inherently different. After a brief introduction of nondestructive evaluation (NDE) , structure health monitoring (SHM) and their related challenges, several recent advances that have significantly extended imaging methods from laboratory development into practical applications were summarized, followed by conclusions and discussion on future directions.

Measurement of current distribution using infrared thermography.

Current distribution measurement methods are widely used in medical examinations, predicting faults in semiconductor devices and assessing structural integrity. Several methods for measuring current distribution are available, such as electrode arrays, coils, and magnetic sensors. However, these measurement methods are unable to obtain images of current distribution with high spatial resolution. Therefore, there is a need to develop a non-contact method to measure current distribution that is capable of capturing images with high spatial resolution. In this study, a non-contact current distribution measurement method based on infrared thermography is proposed. The method uses thermal variations to quantify the current amplitude and reconstructs the current direction based on the passivity of the electric field. For quantification of low frequency current amplitude, the experimental results show that the method can provide accurate current measurement results, for example, at the power frequency (50 Hz), in the range of 1.05-3.45 A, its relative error can be improved to ±3.66% when the calibration fitting method is used. For the high-frequency current, an effective estimate of the current amplitude is obtained using the first-order derivative of temperature variation. When applied to the eddy current detection (256 KHz), it achieves a high-resolution image of the current distribution, and the effectiveness of the method is verified through simulation experiments. The experimental results show that the proposed method not only measures the current amplitude accurately but also improves the spatial resolution in acquiring two-dimensional current distribution images.

Flexible and Stretchable Organic Electrochemical Transistors for Physiological Sensing Devices.

Flexible and stretchable bioelectronics provides a biocompatible interface between electronics and biological systems and has received tremendous attention for in situ monitoring of various biological systems. Considerable progress in organic electronics has made organic semiconductors, as well as other organic electronic materials, ideal candidates for developing wearable, implantable, and biocompatible electronic circuits due to their potential mechanical compliance and biocompatibility. Organic electrochemical transistors (OECTs), as an emerging class of organic electronic building blocks, exhibit significant advantages in biological sensing due to the ionic nature at the basis of the switching behavior, low driving voltage (<1 V), and high transconductance (in millisiemens range). During the past few years, significant progress in constructing flexible/stretchable OECTs (FSOECTs) for both biochemical and bioelectrical sensors has been reported. In this regard, to summarize major research accomplishments in this emerging field, this review first discusses structure and critical features of FSOECTs, including working principles, materials, and architectural engineering. Next, a wide spectrum of relevant physiological sensing applications, where FSOECTs are the key components, are summarized. Last, major challenges and opportunities for further advancing FSOECT physiological sensors are discussed.

The effects of rumen-protected tryptophan (RPT) on production performance and relevant hormones of dairy cows.

Tryptophan is an essential amino acid that cannot be synthesized in mammals. Therefore, the dietary supply of tryptophan is critical for the health and production performance (e.g., milk) of mammals. In the present study, 36 lactating Holstein cows were used, of which 24 cows were in the rumen-protected tryptophan (RPT) feeding groups with different doses at 14 g/d and 28 g/d, respectively and 12 cows were in the control group. This approach could avoid dietary tryptophan being degraded by the rumen microorganisms and improve its bioavailability for cows. The results showed that RPT increased milk protein percentage, milk protein yield, milk solid non-fat (SNF), and milk yield. In response to RPT treatment, the levels of melatonin (MT), prolactin (PRL), and insulin-like growth factor-1 (IGF-1) were significantly increased in the serum of cows compared to the controls. RPT feeding improved nutrient utilization efficiency and lactation performance of dairy cows, which enhanced the quality of milk.

Resonant Magnetometer for Ultralow Magnetic Field Detection by Integrating Magnetoelastic Membrane on Film Bulk Acoustic Resonator.

Here, we report on a composite nanomechanical resonant magnetometer with magnetoelastic thin film integrated on the surface of a film bulk acoustic resonator (FBAR). By exploiting the delta-E effect of magnetoelastic thin film and resonance characteristic in piezoelectric thin film, we theoretically and experimentally demonstrate the capability to realize ultrahigh resonance frequency and excellent magnetic field sensitivity in such composite configuration, thereby greatly improving the limit of detection of weak magnetic field. The proposed FBAR-based resonant magnetometer achieves maximum magnetic sensitivity of 137 kHz/Oe in a proof-of-concept device without structural optimization, corresponding to a noise equivalent power as low as 7 nT/Hz1/2. Further study indicates that by optimizing the thicknesses of the magnetic sensitive layer and piezoelectric layer, an unprecedented sensitivity of 5 GHz/Oe with an exceptional limit of detection of weak magnetic field down to 190 [Formula: see text]/Hz1/2 could be potentially achieved. Our work provides a forward new and exciting route toward ultralow magnetic field detection in civilian and military applications.

A high voltage capacitance measurement method based on alternating coupled signal injection.

As high voltage pulse power capacitors, ceramic capacitors are widely used in high voltage pulse generators, trigger circuits, laser generators, and other fields. The capacitance of ceramic capacitors is closely related to the direct current (DC) bias voltage. However, the current capacitance measurement methods can only achieve a DC bias of 1 kV, which cannot meet the measurement requirements in high voltage environments. This paper proposes a capacitance measurement method that can accurately measure the capacitance under a DC bias of 3 kV. This method decouples the high DC bias voltage and high frequency alternating small signals and realizes low voltage calibration and high voltage isolation. The experimental results show that the proposed method measures the capacitance under a DC bias of 3 kV with a relative error within ±1%, which makes it possible to accurately quantify the capacitance hysteresis deviation in the process of increasing and decreasing back the voltage.

Asynchronous Frequency-Dependent Fault Detection for Nonlinear Markov Jump Systems Under Wireless Fading Channels.

In this article, the asynchronous fault detection (FD) strategy is investigated in frequency domain for nonlinear Markov jump systems under fading channels. In order to estimate the system dynamics and meet the fact that not all the running modes can be observed exactly, a set of asynchronous FD filters is proposed. By using statistical methods and the Lynapunov stability theory, the augmented system is shown to be stochastic stable with a prescribed l2 gain even under fading transmissions. Then, a novel lemma is developed to capture the finite frequency performance. Some solvable conditions with less conservatism are subsequently deduced by exploiting novel decoupling techniques and additional slack variables. Besides, the FD filter gains could be calculated with the aid of the derived conditions. Finally, the effectiveness of the proposed method is shown by an illustrative example.

Temperature Monitorable Kinetics Study of Human Blood Coagulation by Utilizing a Dual-Mode AlN-Based Acoustic Wave Resonator.

In this study, we reported an acoustic wave resonator for temperature monitorable kinetic analysis of human blood coagulation. The resonator is operated in both Lamb wave mode at 860 MHz and Rayleigh wave mode at 444 MHz. The electrical parameter variation of the resonator induced by the increased plasma viscosity can be used to monitor the coagulation process. The Lamb mode of the resonator is sensitive to both plasma viscosity and plasma temperature, while the Rayleigh mode responds only to the temperature which is not affected by viscosity. These unique characteristics of the two modes are due to different spatial distributions of the acoustic energy. Taking advantage of the aforementioned features, an acoustic wave resonator to study the human blood coagulation is designed to simultaneously monitor the temperature and plasma viscosity. The coagulation time and plasma temperature were provided by fitting the time-frequency curves. Our design holds great promise for biological reaction monitoring with possible temperature changes.

Improvement of the grid-connect current quality using novel proportional-integral controller for photovoltaic inverters.

Precise control of the grid-connected current is a challenge in photovoltaic inverter research. Traditional Proportional-Integral (PI) control technology cannot eliminate steady-state error when tracking the sinusoidal signal from the grid, which results in a very high total harmonic distortion in the grid-connected current. A novel PI controller has been developed in this paper, in which the sinusoidal wave is discretized into an N-step input signal that is decided by the control frequency to eliminate the steady state error of the system. The effect of periodical error caused by the dead zone of the power switch and conduction voltage drop can be avoided; the current tracking accuracy and current harmonic content can also be improved. Based on the proposed PI controller, a 700 W photovoltaic grid-connected inverter is developed and validated. The improvement has been demonstrated through experimental results.

Frequency feature based quantification of defect depth and thickness.

This study develops a frequency feature based pulsed eddy current method. A frequency feature, termed frequency to zero, is proposed for subsurface defects and metal loss quantification in metallic specimens. A curve fitting method is also employed to generate extra frequency components and improve the accuracy of the proposed method. Experimental validation is carried out. Conclusions and further work are derived on the basis of the studies.

Back propagation neural network based control for the heating system of a polysilicon reduction furnace.

In this paper, the Back Propagation (BP) neural network based control strategy is proposed for the heating system of a polysilicon reduction furnace. It is applied to obtain the control signal I(d), which is used to adjust the heating power through operations of the silicon core temperature, furnace temperature, silicon core voltage, and resistance of the current control cycle. With the control signal I(d) the polycrystalline silicon can be heated from room temperature to the required temperature smoothly and steadily. The proposed BP network applied in this paper can obtain the accurate control signal I(d) and achieve the precise control purpose. This paper presents the principle of the BP network and demonstrates the effectiveness of the BP network in the heating system of a polysilicon reduction furnace by combining the simulation analysis with experimental results.

A comparative study of principal component analysis and independent component analysis in eddy current pulsed thermography data processing.

Eddy Current Pulsed Thermography (ECPT), an emerging Non-Destructive Testing and Evaluation technique, has been applied for a wide range of materials. The lateral heat diffusion leads to decreasing of temperature contrast between defect and defect-free area. To enhance the flaw contrast, different statistical methods, such as Principal Component Analysis and Independent Component Analysis, have been proposed for thermography image sequences processing in recent years. However, there is lack of direct and detailed independent comparisons in both algorithm implementations. The aim of this article is to compare the two methods and to determine the optimized technique for flaw contrast enhancement in ECPT data. Verification experiments are conducted on artificial and thermal fatigue nature crack detection.