ß-arrestin1 protects intestinal tight junction through promoting mitofusin 2 transcription to drive parkin-dependent mitophagy in colitis.

Background: Intestinal barrier defect is an essential inflammatory bowel disease (IBD) pathogenesis. Mitochondrial dysfunction results in energy deficiency and oxidative stress, which contribute to the pathogenesis of IBD. ß-arrestin1 (ARRB1) is a negative regulator that promotes G protein-coupled receptors desensitization, endocytosis, and degradation. However, its role in maintaining the intestinal barrier remains unclear. Methods: Dextran sulfate sodium-induced colitis was performed in ARRB1 knockout and wild-type mice. Intestinal permeability and tight junction proteins were measured to evaluate the intestinal barrier. Mitochondria function and mitophagic flux in mice and cell lines were detected. Finally, the interaction between ARRB1 and mitofusin 2 was investigated by co-immunoprecipitation and dual luciferase assay. Results: We identified that ARRB1 protected the intestinal tight junction barrier against experimental colitis in vivo. ARRB1 deficiency was accompanied by abnormal mitochondrial morphology, lower adenosine triphosphate (ATP) production, and severe oxidative stress. In vitro, the knockdown of ARRB1 reduced ATP levels and mitochondrial membrane potential while increasing reactive oxygen species levels and oxidative stress. Upon ARRB1 ablation, mitophagy was inhibited, accompanied by decreased LC3BII, phosphatase and tension homologue-induced protein kinase1 (PINK1), and parkin, but increased p62 expression. Mitophagy inhibition via PINK1 siRNA or mitochondrial division inhibitor 1 impaired ARRB1-mediated tight junction protection. The interaction of ARRB1 with E2F1 activated mitophagy by enhancing the transcription of mitofusin 2. Conclusions: Our results suggest that ARRB1 is critical to maintaining the intestinal tight junction barrier by promoting mitophagy. These results reveal a novel link between ARRB1 and the intestinal tight junction barrier, which provides theoretical support for colitis treatment.

Bio-Plausible Multimodal Learning with Emerging Neuromorphic Devices.

Multimodal machine learning, as a prospective advancement in artificial intelligence, endeavors to emulate the brain's multimodal learning abilities with the objective to enhance interactions with humans. However, this approach requires simultaneous processing of diverse types of data, leading to increased model complexity, longer training times, and higher energy consumption. Multimodal neuromorphic devices have the capability to preprocess spatio-temporal information from various physical signals into unified electrical signals with high information density, thereby enabling more biologically plausible multimodal learning with low complexity and high energy-efficiency. Here, this work conducts a comparison between the expression of multimodal machine learning and multimodal neuromorphic computing, followed by an overview of the key characteristics associated with multimodal neuromorphic devices. The bio-plausible operational principles and the multimodal learning abilities of emerging devices are examined, which are classified into heterogeneous and homogeneous multimodal neuromorphic devices. Subsequently, this work provides a detailed description of the multimodal learning capabilities demonstrated by neuromorphic circuits and their respective applications. Finally, this work highlights the limitations and challenges of multimodal neuromorphic computing in order to hopefully provide insight into potential future research directions.

Visceral adipose tissue area predicts major adverse kidney events in patients with acute necrotizing pancreatitis.

BACKGROUND: Given the previously reported harmful effects of abdominal fat burden on kidney function, we aim to investigate the relationship between major adverse kidney events within 30 days (MAKE30) and abdominal obesity in acute necrotizing pancreatitis (ANP) patients and explore the underlying risk factors. METHODS: A retrospective cohort study of all patients admitted within 72 h after the first episode of ANP to a tertiary center between June 2015 and June 2019 was conducted. Automatic image analysis software was used to calculate the area of subcutaneous adipose tissue (SAT), visceral adipose tissue (VAT) and skeletal muscle from computed tomography scans at the umbilical level. The potential risk factors of MAKE30 were analyzed by logistic regression. RESULTS: A total of 208 eligible ANP patients were enrolled, with an incidence of 23% for MAKE30. VAT area was more closely associated with the development of MAKE30, with an area under the ROC curve of 0.69 (cutoff value 200 cm2, 63.8% sensitivity and 66.7% specificity). Multivariate logistic regression analysis demonstrated that VAT area [OR 1.01 (1.01-1.02); p < 0.001] was an independent risk factor in predicting MAKE30. Patients with a VAT area > 200 cm2 had more requirements of renal replacement therapy (32% vs. 12%, P < 0.001), and a significantly higher incidence of other poor clinical outcomes (all p < 0.05). CONCLUSION: Early assessment of the VAT area may help identify ANP patients at high risk of MAKE30, suggesting that it could be a potential indicator for adverse kidney events.

A rolling-mode triboelectric nanogenerator with multi-tunnel grating electrodes and opposite-charge-enhancement for wave energy harvesting.

In light of the crucial role of marine ecosystems and the escalating environmental conservation challenges, it is essential to conduct marine monitoring to help implement targeted environmental protection measures efficiently. Energy harvesting technologies, particularly triboelectric nanogenerators (TENGs), have great potential for prolonging the lifespan and enhancing the reliability of sensors in remote areas. However, the high internal resistance, low current, and friction-induced abrasion issues of TENGs limit their performance in practical applications. This work presents a rolling mode triboelectric nanogenerator that utilizes multi-tunnel grating electrodes and the opposite-charge-enhancement mechanism to harvest wave energy efficiently. The device achieves significant instantaneous and root mean square power density of 185.4 W/(m3·Hz) and 10.92 W/(m3·Hz), respectively. By utilizing stacked devices and an exclusively designed power management module, a self-powered ocean sensing system including computing and long-range wireless communication (0.8 km) capabilities was developed. Laboratory and in-situ ocean tests were conducted to assess and validate the system. This work offers a potential solution for the challenging deployment of marine self-powered sensing nodes.

High-Performance Coaxial Counter-Rotating Triboelectric Nanogenerator with Lift-Drag Hybrid Blades for Wind Energy Harvesting.

Wind energy holds potential for in-situ powering large-scale distributed wireless sensor nodes (WSNs) in the Internet of Things (IoT) era. To achieve high performance in wind energy harvesting, a coaxial counter-rotating triboelectric nanogenerator with lift-drag hybrid blades, termed CCR-TENG, has been proposed. The CCR-TENG, which can work in non-contact and soft-contact modes, realizes low-speed wind energy harvesting through a combination of counter-clockwise rotating lift-type blades and clockwise rotating drag-type blades. Non-contact CCR-TENG realizes low-speed wind energy harvesting at wind speeds as low as 1 m/s. The output of a CCR-TENG, working in soft-contact mode, achieves 41% promotion with a maximum short-circuit current of 0.11 mA and a peak surface power density of 6.2 W/m2 with two TENGs connected in parallel. Furthermore, the power density per unit of wind speed achieves 746 mW/m3·s/m. Consequently, two fluorescent lamps were successfully illuminated and six temperature sensors were continuously lit by the CCR-TENG. The reported CCR-TENG significantly improves low-speed environmental wind energy utilization and demonstrates broad application prospects for in-situ power supply of distributed wireless transmission devices and sensors in the era of the IoT.

A Flexible, Adaptive, and Self-Powered Triboelectric Vibration Sensor with Conductive Sponge-Silicone for Machinery Condition Monitoring.

Vibration sensors for continuous and reliable condition monitoring of mechanical equipment, especially detection points of curved surfaces, remain a great challenge and are highly desired. Herein, a highly flexible and adaptive triboelectric vibration sensor for high-fidelity and continuous monitoring of mechanical vibration conditions is proposed. The sensor is entirely composed of flexible materials. It consists of a conductive sponge-silicone layer and a fluorinated ethylene propylene film. It can detect vibration acceleration of 5 to 50 m s-2 and vibration frequency of 10 to 100 Hz. It has strong robustness and stability, and the output performance barely changes after the durability test of 168 000 working cycles. Additionally, the flexible sensor can work even when the detection point of the mechanical equipment is curved, and the linear fit of the output voltage and acceleration is very close to that when the detection point is flat. Finally, it can be applied to monitoring the working condition of blower and vehicle engine, and can transmit vibration signal to mobile phone application through Wi-Fi module for real-time monitoring. The flexible triboelectric vibration sensor is expected to provide a practical paradigm for smart, green, and sustainable wireless sensor system in the era of Internet of Things.

Coaxial Flexible Fiber-Shaped Triboelectric Nanogenerator Assisted by Deep Learning for Self-Powered Vibration Monitoring.

Self-powered vibration sensor is highly desired for distributed and continuous monitoring requirements of Industry 4.0. Herein, a flexible fiber-shaped triboelectric nanogenerator (F-TENG) with a coaxial core-shell structure is proposed for the vibration monitoring. The F-TENG exhibits higher adaptability to the complex surfaces, which has an outstanding application prospect due to vital compensation for the existing rigid sensors. Initially, the contact characteristics between the dielectric layers, that related to the perceiving performance of the TENG, are theoretically analyzed. Such a TENG with 1D structure endows high sensitivity, allowing for accurately responding to a wide range of vibration frequencies (0.1 to 100 Hz). Even applying to the real diesel engine, the error in detecting the vibration frequencies is only 0.32% compared with the commercial vibration sensor, highlighting its potential in practical application. Further, assisted by deep learning, the recognition accuracy in monitoring nine operating conditions of the system achieves 97.87%. Overall, the newly designed F-TENG with the merits of high-adaptability, cost-efficiency, and self-powered, has offered a promising solution to fulfill an extensive range of vibration sensing applications in the future.

Underwater Biomimetic Lateral Line Sensor Based on Triboelectric Nanogenerator for Dynamic Pressure Monitoring and Trajectory Perception.

Developing desirable sensors is crucial for underwater perceptions and operations. The perceiving organs of marine creatures have greatly evolved to react accurately and promptly underwater. Inspired by the fish lateral line, this study proposes a triboelectric dynamic pressure sensor for underwater perception. The biomimetic lateral line sensor (BLLS) has high sensitivity to the disturbance amplitude/frequency, good adaptability to underwater environments and (relative) low cost. The sensors are deployed at the bottom of the test basin to perceive various moving objects, such as a robotic fish, robotic seal, etc. By analyzing the electrical signal of the sensor, the motion parameters of the objects passed over can be obtained. By monitoring signal variations across multiple sensors, the ability to sense different disturbance movement trajectories, including linear and angular trajectories, is achievable. The study will prove significant in forming an unconventional underwater perceiving method, which can back-up the sonic/optical sensors when are impaired in complex underwater environments.

Study on the prevalence and subtypes of human papillomavirus infection among women in the Xuhui District, Shanghai City, China.

Background: Human papillomavirus (HPV) can cause various gynecological diseases, create a long-term inflammatory immune microenvironment, and induce the occurrence of cervical tumors. However, the prevalence of HPV is species-specific in different eras or in different countries and regions. This paper aimed to investigate the characteristics of HPV infection in the Xuhui District, Shanghai City, China. Methods: We collected HPV data from 6,760 female testers, focusing on the younger population for data analysis. We focused more on the HPV subtypes to which young women were susceptible, performed t-Distributed Stochastic Neighbor Embedding (TSNE) analysis to screen for characteristic subtypes, and compared the prevalent subtypes lacking effective vaccine protection. Results: HPV infection exhibited a trend of affecting a younger population, and eight subtypes were more likely to occur in young people. HPV43, 51, 53, and 59 showed a higher incidence and lacked vaccine protection. We performed TSNE dimensionality reduction analysis to organize the HPV data. The results indicated that HPV16, 18, and 51 are characteristic subtypes in the younger population. The Thinprep cytologic test (TCT) also revealed that the infection with HPV43, 51, 53, and 59 also triggers significant pathological phenotypes. Conclusions: HPV51 is a subtype that occurs more frequently in young women, can induce a variety of significant pathological features, and lacks effective vaccine protection. This study inspires us to take measures to deal with HPV rejuvenation and conduct research on vaccines for specific HPV subtypes.

In-depth understanding of boosting salinity gradient power generation by ionic diode.

Ionic diodes constructed with asymmetric channel geometry and/or charge layout have shown outstanding performance in ion transport manipulation and reverse electrodialysis (RED) energy collection, but the working mechanism is still indistinct. Herein, we systematically investigated RED energy conversion of straight nanochannel-based bipolar ionic diode by coupling the Poisson-Nernst-Planck and Navier-Strokes equations. The effects of nanochannel structure, charging polarity, and symmetricity as well as properties of working fluids on the output voltage and output power were investigated. The results show that as high-concentration feeding solution is applied, the bipolar ionic diode-based RED system gives higher output voltage and output power compared to the unipolar channel RED system. Under optimal conditions, the voltage output of the bipolar channel is increased by ∼100% and the power output is increased by ∼260%. This work opens a new route for the design and optimization of high-performance salinity energy harvester as well as for water desalination.

A Novel Thermal Tactile Sensor Based on Micro Thermoelectric Generator for Underwater Flow Direction Perception.

Underwater vehicles can operate independently in the exploitation of marine resources. However, water flow disturbance is one of the challenges underwater vehicles must face. The underwater flow direction sensing method is a feasible way to overcome the challenges but faces difficulties such as integrating the existing sensors with underwater vehicles and high-cost maintenance fees. In this research, an underwater flow direction sensing method based on the thermal tactility of the micro thermoelectric generator (MTEG) is proposed, with the theoretical model established. To verify the model, a flow direction sensing prototype is fabricated to carry out experiments under three typical working conditions. The three typical flow direction conditions are: condition No. 1, in which the flow direction is parallel to the x-axis; condition No. 2, in which the flow direction is at an angle of 45° to the x-axis; and condition No. 3, which is a variable flow direction condition based on condition No. 1 and condition No. 2. According to the experimental data, the variations and orders of the prototype output voltages under three conditions fit the theoretical model, which means the prototype can identify the flow direction of three conditions. Besides, experimental data show that in the flow velocity range of 0~5 m/s and the flow direction variation range of 0~90°, the prototype can accurately identify the flow direction in 0~2 s. The first time utilizing MTEG on underwater flow direction perception, the underwater flow direction sensing method proposed in this research is cheaper and easier to be applied on the underwater vehicles than traditional underwater flow direction sensing methods, which means it has great application prospects in underwater vehicles. Besides, the MTEG can utilize the waste heat of the underwater vehicle battery as the energy source to achieve self-powered work, which greatly enhances its practical value.

Reconfigurable Neuromorphic Computing: Materials, Devices, and Integration.

Neuromorphic computing has been attracting ever-increasing attention due to superior energy efficiency, with great promise to promote the next wave of artificial general intelligence in the post-Moore era. Current approaches are, however, broadly designed for stationary and unitary assignments, thus encountering reluctant interconnections, power consumption, and data-intensive computing in that domain. Reconfigurable neuromorphic computing, an on-demand paradigm inspired by the inherent programmability of brain, can maximally reallocate finite resources to perform the proliferation of reproducibly brain-inspired functions, highlighting a disruptive framework for bridging the gap between different primitives. Although relevant research has flourished in diverse materials and devices with novel mechanisms and architectures, a precise overview remains blank and urgently desirable. Herein, the recent strides along this pursuit are systematically reviewed from material, device, and integration perspectives. At the material and device level, one comprehensively conclude the dominant mechanisms for reconfigurability, categorized into ion migration, carrier migration, phase transition, spintronics, and photonics. Integration-level developments for reconfigurable neuromorphic computing are also exhibited. Finally, a perspective on the future challenges for reconfigurable neuromorphic computing is discussed, definitely expanding its horizon for scientific communities.

Research on an Optimized Quarter-Wavelength Resonator-Based Triboelectric Nanogenerator for Efficient Low-Frequency Acoustic Energy Harvesting.

Sound wave is an extensively existing mechanical wave, especially in marine and industrial plants where low-frequency acoustic waves are ubiquitous. The effective collection and utilization of sound waves provide a fresh new approach to supply power for the distributed nodes of the rapidly developing Internet of Things technology. In this paper, a novel acoustic triboelectric nanogenerator (QWR-TENG) was proposed for efficient low-frequency acoustic energy harvesting. QWR-TENG consisted of a quarter-wavelength resonant tube, a uniformly perforated aluminum film, an FEP membrane, and a conductive carbon nanotube coating. Simulation and experimental studies showed that QWR-TENG has two resonance peaks in the low-frequency range, which effectively extends the response bandwidth of acoustic-electrical conversion. The structural optimized QWR-TENG has excellent electrical output performance, and the maximum output voltage, short-circuit current and transferred charge are 255 V, 67 µA, and 153 nC, respectively, under the acoustic frequency of 90 Hz and sound pressure level of 100 dB. On this basis, a conical energy concentrator was introduced to the entrance of the acoustic tube, and a composite quarter-wavelength resonator-based triboelectric nanogenerator (CQWR-TENG) was designed to further enhance the electrical output. Results showed that the maximum output power and the power density per unit pressure of CQWR-TENG reached 13.47 mW and 2.27 WPa-1m-2, respectively. Application demonstrations indicated that QWR/CQWR-TENG has good capacitor charging performance and is expected to realize power supply for distributed sensor nodes and other small electrical devices.

Association between pretreatment lymphocyte count and efficacy of immune-enhancing therapy in acute necrotising pancreatitis: a post-hoc analysis of the multicentre, randomised, placebo-controlled TRACE trial.

Background: Immune-enhancing thymosin alpha 1 (Tα1) therapy may reduce infected pancreatic necrosis (IPN) in acute necrotising pancreatitis (ANP). However, the efficacy might be impacted by lymphocyte count due to the pharmacological action of Tα1. In this post-hoc analysis, we tested the hypothesis that pre-treatment absolute lymphocyte count (ALC) determines whether patients with ANP benefit from Tα1 therapy. Methods: A post-hoc analysis of data from a multicentre, double-blind, randomised, placebo-controlled trial testing the efficacy of Tα1 therapy in patients with predicted severe ANP was performed. Patients from 16 hospitals of China were randomised to receive a subcutaneous injection of Tα1 1.6 mg every 12 h for the frst 7 days and 1.6 mg once a day for the following 7 days or a matching placebo during the same period. Patients who discontinued the Tα1 regimen prematurely were excluded. Three subgroup analyses were conducted using the baseline ALC (at randomisation), and the group allocation was maintained as intention-to-treat. The primary outcome was the incidence of IPN 90 days after randomisation. The fitted logistic regression model was applied to identify the range of baseline ALC where Tα1 therapy could exert a maximum effect. The original trial is registered with ClinicalTrials.gov, NCT02473406. Findings: Between March 18, 2017, and December 10, 2020, a total of 508 patients were randomised in the original trial, and 502 were involved in this analysis, with 248 in the Tα1 group and 254 in the placebo group. Across the three subgroups, there was a uniform trend toward more significant treatment effects in patients with higher baseline ALC. Within the subgroup of patients with baseline ALC≥0.8 × 10ˆ9/L (n = 290), the Tα1 therapy significantly reduced the risk of IPN (covariate adjusted risk difference, -0.12; 95% CI, -0.21,-0.02; p = 0.015). Patients with baseline ALC between 0.79 and 2.00 × 10ˆ9/L benefited most from the Tα1 therapy in reducing IPN (n = 263). Interpretation: This post-hoc analysis found that the efficacy of immune-enhancing Tα1 therapy on the incidence of IPN may be associated with pretreatment lymphocyte count in patients with acute necrotising pancreatitis. Funding: National Natural Science Foundation of China.

Deep-Learning-Assisted Underwater 3D Tactile Tensegrity.

The growth of underwater robotic applications in ocean exploration and research has created an urgent need for effective tactile sensing. Here, we propose an underwater 3-dimensional tactile tensegrity (U3DTT) based on soft self-powered triboelectric nanogenerators and deep-learning-assisted data analytics. This device can measure and distinguish the magnitude, location, and orientation of perturbations in real time from both flow field and interaction with obstacles and provide collision protection for underwater vehicles operation. It is enabled by the structure that mimics terrestrial animals' musculoskeletal systems composed of both stiff bones and stretchable muscles. Moreover, when successfully integrated with underwater vehicles, the U3DTT shows advantages of multiple degrees of freedom in its shape modes, an ultrahigh sensitivity, and fast response times with a low cost and conformability. The real-time 3-dimensional pose of the U3DTT has been predicted with an average root-mean-square error of 0.76 in a water pool, indicating that this developed U3DTT is a promising technology in vehicles with tactile feedback.

A Novel Method Based on Hydrodynamic Cavitation for Improving Nitric Oxide Removal Performance of NaClO2.

In the removal of nitric oxide (NO) by sodium chlorite (NaClO2), the NaClO2 concentration is usually increased, and an alkaline absorbent is added to improve the NO removal efficiency. However, this increases the cost of denitrification. This study is the first to use hydrodynamic cavitation (HC) combined with NaClO2 for wet denitrification. Under optimal experimental conditions, when 3.0 L of NaClO2 with a concentration of 1.00 mmol/L was used to treat NO (concentration: 1000 ppmv and flow rate: 1.0 L/min), 100% of nitrogen oxides (NOx) could be removed in 8.22 min. Furthermore, the NO removal efficiency remained at 100% over the next 6.92 min. Furthermore, the formation of ClO2 by NaClO2 is affected by pH. The initial NOx removal efficiency was 84.8-54.8% for initial pH = 4.00-7.00. The initial NOx removal efficiency increases as the initial pH decreases. When the initial pH was 3.50, the initial NOx removal efficiency reached 100% under the synergistic effect of HC. Therefore, this method enhances the oxidation capacity of NaClO2 through HC, realizes high-efficiency denitrification with low NaClO2 concentration (1.00 mmol/L), and has better practicability for the treatment of NOx from ships.

Recent Advances in Mechanical Vibration Energy Harvesters Based on Triboelectric Nanogenerators.

With the development of autonomous/smart technologies and the Internet of Things (IoT), tremendous wireless sensor nodes (WSNs) are of great importance to realize intelligent mechanical engineering, which is significant in the industrial and social fields. However, current power supply methods, cable and battery for instance, face challenges such as layout difficulties, high cost, short life, and environmental pollution. Meanwhile, vibration is ubiquitous in machinery, vehicles, structures, etc., but has been regarded as an unwanted by-product and wasted in most cases. Therefore, it is crucial to harvest mechanical vibration energy to achieve in situ power supply for these WSNs. As a recent energy conversion technology, triboelectric nanogenerator (TENG) is particularly good at harvesting such broadband, weak, and irregular mechanical energy, which provides a feasible scheme for the power supply of WSNs. In this review, recent achievements of mechanical vibration energy harvesting (VEH) related to mechanical engineering based on TENG are systematically reviewed from the perspective of contact-separation (C-S) and freestanding modes. Finally, existing challenges and forthcoming development orientation of the VEH based on TENG are discussed in depth, which will be conducive to the future development of intelligent mechanical engineering in the era of IoT.

Modulations in Superconductors: Probes of Underlying Physics.

The importance of modulations is elevated to an unprecedented level, due to the delicate conditions required to bring out exotic phenomena in quantum materials, such as topological materials, magnetic materials, and superconductors. Recently, state-of-the-art modulation techniques in material science, such as electric-double-layer transistor, piezoelectric-based strain apparatus, angle twisting, and nanofabrication, have been utilized in superconductors. They not only efficiently increase the tuning capability to the broader ranges but also extend the tuning dimensionality to unprecedented degrees of freedom, including quantum fluctuations of competing phases, electronic correlation, and phase coherence essential to global superconductivity. Here, for a comprehensive review, these techniques together with the established modulation methods, such as elemental substitution, annealing, and polarization-induced gating, are contextualized. Depending on the mechanism of each method, the modulations are categorized into stoichiometric manipulation, electrostatic gating, mechanical modulation, and geometrical design. Their recent advances are highlighted by applications in newly discovered superconductors, e.g., nickelates, Kagome metals, and magic-angle graphene. Overall, the review is to provide systematic modulations in emergent superconductors and serve as the coordinate for future investigations, which can stimulate researchers in superconductivity and other fields to perform various modulations toward a thorough understanding of quantum materials.

Nonsingular Integral Terminal Sliding Mode Control for Resonant Frequency Tracking of Electromagnetic Acoustic Transducers (EMATs) Based on Fixed-Time Strategy.

Resonant frequency tracking control of electromagnetic acoustic transducers (EMATs) remains a challenge in terms of drifting working frequency and reduced conversion efficiency caused by working environment changes. This paper presents a fixed-time nonsingular integral terminal sliding mode (FT-NITSM) control strategy for resonant frequency tracking of EMATs to realize precise and high robustness resonant frequency tracking performance. Specifically, a FT-NITSM control method with fast convergence feature is developed and a resonant frequency tracking controller for EMATs is further designed to improve the convergence speed and tracking accuracy. Fixed time stability of the proposed frequency tracking control system is proved through Lyapunov function analysis. Moreover, numerical simulations demonstrate that the FT-NITSM control strategy can ensure precise tracking of the system's operating frequency to its natural resonant frequency in less than 3 s with a tracking error of less than 0.01 × 104 Hz. With the maximum overshoot variation between -20 and 20 and error range in -5 and 5° at the steady state, the FT-NITSM control strategy can ensure the control system impedance angle θ being consistent and eventually bounded. This study provides a toolbox for the resonant frequency tracking control and performance improvement of EMATs.

A Cantilever Beam-Based Triboelectric Nanogenerator as a Drill Pipe Transverse Vibration Energy Harvester Powering Intelligent Exploitation System.

Measurement While Drilling (MWD) is the most commonly used real-time information acquisition technique in offshore intelligent drilling, its power supply has always been a concern. Triboelectric nanogenerators have been shown to harvest low-frequency vibrational energy in the environment and convert it into electricity to power small sensors and electrical devices. This work proposed a cantilever-beam-based triboelectric nanogenerator (CB-TENG) for transverse vibration energy harvesting of a drill pipe. The CB-TENG consists of two vibrators composed of spring steel with PTFE attached and Al electrodes. The structurally optimized CB-TENG can output a peak power of 2.56 mW under the vibration condition of f = 3.0 Hz and A = 50 mm, and the electrical output can be further enhanced with the increased vibration parameters. An array-type vibration energy harvester integrated with eight CB-TENGs is designed to fully adapt to the interior of the drill pipe and improve output performance. The device can realize omnidirectional vibration energy harvesting in the two-dimensional plane with good robustness. Under the typical vibration condition, the short-circuit current and the peak power can reach 49.85 µA and 30.95 mW, respectively. Finally, a series of demonstration experiments have been carried out, indicating the application prospects of the device.