Ultra-Robust and High-Performance Rotational Triboelectric Nanogenerator by Bearing Charge Pumping

As an emerging technology to convert environmental high-entropy energy into electrical energy,triboelectric nanogenerator(TENG)has great demands for further enhancing the service lifetime and output performance in practical applications.Here,an ultra-robust and high-performance rotational triboelectric nanogenerator(R-TENG)by bearing charge pumping is proposed.The R-TENG composes of a pumping TENG(P-TENG),an output TENG(O-TENG),a voltage-multiplying circuit(VMC),and a buffer capacitor.The P-TENG is designed with freestanding mode based on a rolling ball bearing,which can also act as the rotating mechanical energy harvester.The output low charge from the P-TENG is accumulated and pumped to the non-contact O-TENG,which can simultaneously realize ultralow mechanical wear and high output performance.The matched instantaneous power of R-TENG is increased by 32 times under 300 r/min.Furthermore,the transferring charge of R-TENG can remain 95%during 15 days(6.4×10^(6)cycles)continuous operation.This work presents a realizable method to further enhance the durability of TENG,which would facilitate the practical applications of high-performance TENG in harvesting distributed ambient micro mechanical energy.

Optimization-based mode selection scheme for OAM millimeter wave system in the off-axis misalignment case

Millimeter-wave transmission combined with Orbital Angular Momentum(OAM)has the advantage of reducing the loss of beam power and increasing the system capacity.However,to fulfill this advantage,the antennas at the transmitter and receiver must be parallel and coaxial;otherwise,the accuracy of mode detection at the receiver can be seriously influenced.In this paper,we design an OAM millimeter-wave communication system for overcoming the above limitation.Specifically,the first contribution is that the power distribution between different OAM modes and the capacity of the system with different mode sets are analytically derived for performance analysis.The second contribution lies in that a novel mode selection scheme is proposed to reduce the total interference between different modes.Numerical results show that system performance is less affected by the offset when the mode set with smaller modes or larger intervals is selected.

Collision off-axis position dependence of relativistic nonlinear Thomson inverse scattering of an excited electron in a tightly focused circular polarized laser pulse

This paper presents a novel view of the impact of electron collision off-axis positions on the dynamic properties and relativistic nonlinear Thomson inverse scattering of excited electrons within tightly focused, circularly polarized laser pulses of varying intensities. We examine the effects of the transverse ponderomotive force, specifically how the deviation angle and speed of electron motion are affected by the initial off-axis position of the electron and the peak amplitude of the laser pulse. When the laser pulse intensity is low, an increase in the electron's initial off-axis distance results in reduced spatial radiation power, improved collimation, super-continuum phenomena generation, red-shifting of the spectrum's harmonic peak, and significant symmetry in the radiation radial direction. However, in contradiction to conventional understandings,when the laser pulse intensity is relatively high, the properties of the relativistic nonlinear Thomson inverse scattering of the electron deviate from the central axis, changing direction in opposition to the aforementioned effects. After reaching a peak, these properties then shift again, aligning with the previous direction. The complex interplay of these effects suggests a greater nuance and intricacy in the relationship between laser pulse intensity, electron position, and scattering properties than previously thought.

In-phase and out-of-phase spin pumping effects in Py/Ru/Pysynthetic antiferromagnetic structures

The spin pumping effect in magnetic heterostructures and multilayers is a highly effective method for the generationand transmission of spin currents. In the increasingly prominent synthetic antiferromagnetic structures, the two ferromagneticlayers demonstrate in-phase and out-of-phase states, corresponding to acoustic and optical precession modes. Withinthis context, our study explores the spin pumping effect in Py/Ru/Py synthetic antiferromagnetic structures across differentmodes. The heightened magnetic damping resulting from the spin pumping effect in the in-phase state initially decreaseswith increasing Py thickness before stabilizing. Conversely, in the out-of-phase state, the amplified damping exceeds thatof the in-phase state, suggesting a greater spin relaxation within this configuration, which demonstrates sensitivity to alterationsin static exchange interactions. These findings contribute to advancing the application of synthetic antiferromagneticstructures in magnonic devices.

Working condition recognition of sucker rod pumping system based on 4-segment time-frequency signature matrix and deep learning

High-precision and real-time diagnosis of sucker rod pumping system(SRPS)is important for quickly mastering oil well operations.Deep learning-based method for classifying the dynamometer card(DC)of oil wells is an efficient diagnosis method.However,the input of the DC as a two-dimensional image into the deep learning framework suffers from low feature utilization and high computational effort.Additionally,different SRPSs in an oil field have various system parameters,and the same SRPS generates different DCs at different moments.Thus,there is heterogeneity in field data,which can dramatically impair the diagnostic accuracy.To solve the above problems,a working condition recognition method based on 4-segment time-frequency signature matrix(4S-TFSM)and deep learning is presented in this paper.First,the 4-segment time-frequency signature(4S-TFS)method that can reduce the computing power requirements is proposed for feature extraction of DC data.Subsequently,the 4S-TFSM is constructed by relative normalization and matrix calculation to synthesize the features of multiple data and solve the problem of data heterogeneity.Finally,a convolutional neural network(CNN),one of the deep learning frameworks,is used to determine the functioning conditions based on the 4S-TFSM.Experiments on field data verify that the proposed diagnostic method based on 4S-TFSM and CNN(4S-TFSM-CNN)can significantly improve the accuracy of working condition recognition with lower computational cost.To the best of our knowledge,this is the first work to discuss the effect of data heterogeneity on the working condition recognition performance of SRPS.

Adoption of Solar Pumping Systems by Vegetable Farmers in Niayes Agro-Ecological Zone of Senegal: Adoption as a Sequential Process

This article examines the determinants of the adoption of solar pumping systems (PV) by vegetable farmers in the Niayes area of Senegal. To measure the determinants, we used a sequential logit model to translate the adoption process from becoming aware of solar pumping systems to testing them, i.e. using them at least once, and then continuing to use them over time. The results show that the main variables affecting awareness of the use of solar pumping systems (PV) are age, marital status, experience, access to credit, the farmer’s knowledge of climate change, the farmer’s origin in the Thiès region and length of time in the Niayes area. The first use of PVs is influenced by factors such as the size of the plot, the distance of the plot from the main road or from the market. Finally, the decision to adopt or continue use is influenced by gender, experience, household size and access to credit. Surprisingly, access to credit does not affect the first use of solar pumping systems, but plays a key role in their continued use.

Comparative Study of the Types of Photovoltaic Panels Used in Solar Pumping Systems in Dry Tropical Zones: Case of Adamawa Region in Cameroon

In the dry tropical zone where access to water is increasingly difficult for populations, solar pumping units are increasingly installed to provide water to population. In the local market, there are essentially two types of solar panels, namely monocrystalline and polycrystalline. However, the part of the local market is more dominated by the polycrystalline panel. In this work, comparative studies are carried out in order to characterize the two types of solar panels with regard to local constraints. Tests were carried out over the course of the sun to establish the performance of each type. The panels used have the same electrical characteristics and are connected to loads with same characteristics. Under the set operating conditions, the monocrystalline panel presents more performance than the polycrystalline panel. Although the local market is dominated by the polycrystalline panel, dust deposition tests on the surface of the panels show that the performance of the polycrystalline panel is more affected compared to the performance of the monocrystalline panel.

Pumpingline管道预制与安装研究——以2023 SH 二次配Pumping-line工程项目为例

本文以中芯南方集成电路制造有限公司负责的2023?SH?二次配Pumping-line工程项目为例,首先对Pumping line管道预制与安装流程进行了简单介绍。在此基础上,本文围绕机台Pumping line会勘、Pumping line管道测量绘图作业、Pumping line管道的预制与现场安装作业要素、机台Monve-in定位后Hook up相关作业要素等展开分析,希望为相关从业人员提供一定的参考。

Few-shot working condition recognition of a sucker-rod pumping system based on a 4-dimensional time-frequency signature and meta-learning convolutional shrinkage neural network

The accurate and intelligent identification of the working conditions of a sucker-rod pumping system is necessary. As onshore oil extraction gradually enters its mid-to late-stage, the cost required to train a deep learning working condition recognition model for pumping wells by obtaining enough new working condition samples is expensive. For the few-shot problem and large calculation issues of new working conditions of oil wells, a working condition recognition method for pumping unit wells based on a 4-dimensional time-frequency signature (4D-TFS) and meta-learning convolutional shrinkage neural network (ML-CSNN) is proposed. First, the measured pumping unit well workup data are converted into 4D-TFS data, and the initial feature extraction task is performed while compressing the data. Subsequently, a convolutional shrinkage neural network (CSNN) with a specific structure that can ablate low-frequency features is designed to extract working conditions features. Finally, a meta-learning fine-tuning framework for learning the network parameters that are susceptible to task changes is merged into the CSNN to solve the few-shot issue. The results of the experiments demonstrate that the trained ML-CSNN has good recognition accuracy and generalization ability for few-shot working condition recognition. More specifically, in the case of lower computational complexity, only few-shot samples are needed to fine-tune the network parameters, and the model can be quickly adapted to new classes of well conditions.

Effects of proton pump inhibitors on inflammatory bowel disease:An updated review

Inflammatory bowel disease(IBD)is believed to be caused by various factors,including abnormalities in disease susceptibility genes,environmental factors,immune factors,and intestinal bacteria.Proton pump inhibitors(PPIs)are the primary drugs used to treat acid-related diseases.They are also commonly prescribed to patients with IBD.Recent studies have suggested a potential association between the use of certain medications,such as PPIs,and the occurrence and progression of IBD.In this review,we summarize the potential impact of PPIs on IBD and analyze the underlying mechanisms.Our findings may provide insights for conducting further investigations into the effects of PPIs on IBD and serve as an important reminder for physicians to exercise caution when prescribing PPIs to patients with IBD.

Factors of Pumping Capacity in Some Different Types of Channel Brownian Pumps

The motion of particles in different channel Brownian pumps can be described by Langevin equations,and the pumping capacity is a useful indicator to demonstrate the strength of a pump’s transportation ability.Via the simulation,there is always an optimal value of temperature and unbiased external force for different pumps which make the concentration ratio between the right tube and left tube derive its maximum and minimum in two asymmetric tubes respectively.Besides,the concentration ratio will keep 1 regardless of radius,temperature or magnitude of force in the tube in a symmetric tube.To obtain more information about pumping capacity,exploring the average probability current(APC) of tubes in different conditions is necessary.Results indicate that as the concentration ratio is 1,the change of the APC when x_(0)=0 is similar to that when x_(0)=π.Also,when the concentration ratio is more than 1,there are optimal values of temperature,radius and magnitude of force where the APC gains a maximum,and the maximum decreases as the concentration in the right tube increases when x_(0)=0.

Spin pumping by higher-order dipole-exchange spin-wave modes

Spin pumping(SP)and inverse spin Hall effect(ISHE)driven by parametrically-excited dipole-exchange spin waves in a yttrium iron garnet film have been systematically investigated.The measured voltage spectrum exhibits a feature of the field-induced transition from parallel pumping to perpendicular pumping because of the inhomogeneous excitation geometry.Thanks to the high precision of the SP-ISHE detection,two sets of fine structures in the voltage spectrum are observed,which can correspond well to two kinds of critical points in the multimode spin-wave spectrum for magnetic films.One is the q=0 point of each higher-order dispersion branch,and the other is the local minimum due to the interplay between the dipolar and exchange interactions.These fine structures on the voltage spectrum confirm the spin pumping by higher-order dipole-exchange spin-wave modes,and are helpful for probing the multimode spin-wave spectrum.

Simultaneous detection of CH_(4)and CO_(2)through dual modulation off-axis integrated cavity output spectroscopy

This study established a novel method for the simultaneous detection of two-component gases.Radio frequency(RF)white noise disturbance laser current and wavelength modulation were simultaneously used to improve the off-axis integrated cavity output spectroscopy technique,and a high-precision dual modulation OA-ICOS(RF-WM-OA-ICOS)system was established.The two laser beams were coupled into one laser beam that was applied incident to the cavity of RF-WM-OA-ICOS system.The second harmonic signals of CH_(4)and CO_(2)gas simultaneously appeared in the rising or falling edge of a triangular wave.This method was used to measure CH_(4)and CO_(2)with different concentrations.The results indicated that the proposed system has high stability and can accurately and simultaneously measure the concentrations of CH_(4)and CO_(2),with an optimal integration time of 220 s.The minimum detection limit was 10 ppb for CH_(4)and 1.5 ppm for CO_(2).The corresponding noise equivalent absorption sensitivity values were calculated as 2.67×10^(-13)cm^(-1)·Hz^(-1/2)and 5.18×10^(-11)cm^(-1)·Hz^(-1/2),respectively.The proposed dual-component gas simultaneous detection method can also be used for high-precision simultaneous detection of other gases.Therefore,this study may serve as a reference for developing portable multicomponent gas analyzers.

A cladding-pumping based power-scaled noise-like and dissipative soliton pulse fiber laser

We report a high-average-power noise-like pulse(NLP) and dissipative soliton(DS) pulse fiber laser. Average power as high as 4.8 W could be obtained at the fundamental mode-locked repetition rate. The NLP can also be transformed into a more powerful DS mode-locking state by optimizing the polarization and losses of intra-cavity pulses in the nonlinear polarization evolution regime. The operation mode between the NLP and DS can be switched, and the laser output performance in both modes has been studied. The main advantage of this work is switchable high-power operation between the NLP and DS. In comparison with conventional single-mode NLP fiber lasers, the multi-function high-power optical source will greatly push its application in supercontinuum generation, coherence tomography, and industrial processing.

An NMOS output-capacitorless low-dropout regulator with dynamic-strength event-driven charge pump

In this paper,an NMOS output-capacitorless low-dropout regulator(OCL-LDO)featuring dual-loop regulation has been proposed,achieving fast transient response with low power consumption.An event-driven charge pump(CP)loop with the dynamic strength control(DSC),is proposed in this paper,which overcomes trade-offs inherent in conventional structures.The presented design addresses and resolves the large signal stability issue,which has been previously overlooked in the event-driven charge pump structure.This breakthrough allows for the full exploitation of the charge-pump structure's poten-tial,particularly in enhancing transient recovery.Moreover,a dynamic error amplifier is utilized to attain precise regulation of the steady-state output voltage,leading to favorable static characteristics.A prototype chip has been fabricated in 65 nm CMOS technology.The measurement results show that the proposed OCL-LDO achieves a 410 nA low quiescent current(IQ)and can recover within 30 ns under 200 mA/10 ns loading change.

Characteristic Analysis of Off-Axis Meta-Lens

Meta-lens are a new type of planar optical element that can flexibly manipulate the phase, polarization and amplitude of the beam, and are currently receiving a great deal of attention as they are easier to process and manufacture. Off-axis meta-lens are a special type of meta-lens with a certain degree of dispersion that can be used as a beam-splitting element, providing a unique and feasible way to realize micro-miniature instruments. We analyze the effects of different numerical apertures and off-axis angles on the spectral resolution, focusing efficiency and simulation results of off-axis meta-lens to provide ideas for subsequent research and application of off-axis meta-lens. A number of off-axis meta-lens with parameters NA = 0.408 α = 13°, NA = 0.18 α = 13° and NA = 0.408 α = 20° were simulated through Lumerical software. The results show that the off-axis angle is related to the resolution;the larger the angle, the better the spectral resolution but the lower the focusing efficiency;when the numerical aperture is smaller, the smaller the coverage of the phase distribution, which will lead to a larger deviation between simulation and theory. The designer needs to balance the numerical aperture, off-axis angle and other parameters reasonably according to the requirements in order to achieve the desired effect. The findings of this study have important reference values for the theoretical analysis of off-axis meta-lens and the design of parameters in practical applications. .

Preface:Development and utilization of pumped storage in closed/abandoned mines

China has embarked on an extensive and sustained endeavor to harness its coal resources for a substantial period.However,the depletion of coal reserves in mining regions has necessitated the closure or abandonment of numerous mines,resulting in a marked increase in the number of such facilities.Parallel to this,China is vigorously advancing the development of a novel energy power system,aimed at transitioning the power sector from a high-carbon,fossil fuel-dependent paradigm to a low-carbon,clean energy footing.

An LED-Side-Pumped Intracavity Frequency-Doubled Nd,Ce:YAG Laser Producing a 2W Q-Switched Red Beam

We report a high-average-power acousto-optic(AO)Q-switched intracavity frequency-doubled red laser based on a high-efficiency light-emitting-diode(LED)pumped two-rod Nd,Ce:YAG laser module.Under quasi-continuous wave operation conditions,a maximum output power of 1319.08 nm wavelength was achieved at 11.26 W at a repetition rate of 100 Hz.

Wear dependent virtual flow rate sensor for progressing cavity pumps with deformable stator

This contribution presents a novel wear dependent virtual flow rate sensor for single stage single lobe progressing cavity pumps. We study the wear-induced material loss of the pump components and the impact of this material loss on the volumetric efficiency. The results are combined with an established backflow model to implement a backflow calculation procedure that is adaptive to wear. We use a laboratory test setup with a highly abrasive fluid and operate a pump from new to worn condition to validate our approach. The obtained measurement data show that the presented virtual sensor is capable of calculating the flow rate of a pump being subject to wear during its regular operation.

Dual-wavelength pumped latticed Fermi-Pasta-Ulam recurrences in nonlinear Schrödinger equation

We show that the nonlinear stage of the dual-wavelength pumped modulation instability(MI)in nonlinear Schrödinger equation(NLSE)can be effectively analyzed by mode truncation methods.The resulting complicated heteroclinic structure of instability unveils all possible dynamic trajectories of nonlinear waves.Significantly,the latticed-Fermi-Pasta-Ulam recurrences on the modulated-wave background in NLSE are also investigated and their dynamic trajectories run along the Hamiltonian contours of the heteroclinic structure.It is demonstrated that there has much richer dynamic behavior,in contrast to the nonlinear waves reported before.This novel nonlinear wave promises to inject new vitality into the study of MI.