基于CSAPSO-BP神经网络的光纤陀螺温度补偿研究

光纤陀螺是惯导系统的重要组成器件,环境温度变化会造成光纤陀螺的零偏发生漂移,从而降低测量精度。运用传统的BP神经网络进行预测易陷入局部极小值,导致补偿失败。该文采用混沌模拟退火粒子群BP神经网络的光纤陀螺零偏温度补偿模型,优化了网络参数。通过在-40～60℃的升降温实验对模型进行验证,实验结果表明,该温度补偿模型的零偏稳定性比补偿前约有70%的精度提升,与以往BP模型相比,其预测性能和补偿效果更好。     

配电网分布式光伏可开放容量工程快速求解方法

随着我国“双碳”战略的实施,分布式电源尤其是分布式光伏呈现爆发式增长。分布式光伏的大量无序接入,引起局部地区配电网过电压、设备反向重过载等一系列问题,阻碍分布式光伏的健康有序发展。本文提出一种配电设备级及行政区域级分布式光伏可开放容量工程快速求解方法,该方法统筹考虑配电设备及配电系统的各类约束指标,兼顾计算精度和计算效率,在确保配电网安全、可靠、经济运行的前提下,科学确定其所能接纳的分布式光伏容量上限,为分布式光伏的有序接入和健康发展提供支撑。最后以某县域为例,验证了该方法的科学性和可行性。     

Degradation state analysis of the IGBT module based on apparent junction temperature

The multi-chip parallel insulated gate bipolar transistor (IGBT) is the core device in large-capacity power electronic equipment, but its operational reliability is of considerable concern to industry. The application of IGBT online degradation state analysis technology can be benefcial to the improvement of system reliability. The failure mechanism of IGBT devices is discussed in this paper, and a technique for analyzing the degradation state of IGBT based on apparent junction temperature is proposed. First, the distortion consistency of the voltage rise time in various failures is discussed, and the junction temperature dependence of the voltage rise time is then demonstrated. Subsequently, an apparent junction temperature model based on the voltage rise time is established (the ftting accuracy is as high as 94.3%). From the high-frequency model in the switching process of the device, an online extraction technology of key parameters (e.g., voltage rise time) is developed. Finally, an experimental platform for IGBT degradation state estimation is established, and the feasibility of IGBT degradation state estimation based on apparent junction temperature is proved, especially the degradation of bonding-wire and the gate-oxide-layer. The experimental results show that the proposed IGBT degradation state estimation technique based on apparent junction temperature is a reliable online estimation method with non-contact, high accuracy, and comprehensiveness.     

Degradation state analysis of the IGBT module based on apparent junction temperature

The multi-chip parallel insulated gate bipolar transistor (IGBT) is the core device in large-capacity power electronic equipment, but its operational reliability is of considerable concern to industry. The application of IGBT online degradation state analysis technology can be benefcial to the improvement of system reliability. The failure mechanism of IGBT devices is discussed in this paper, and a technique for analyzing the degradation state of IGBT based on apparent junction temperature is proposed. First, the distortion consistency of the voltage rise time in various failures is discussed, and the junction temperature dependence of the voltage rise time is then demonstrated. Subsequently, an apparent junction temperature model based on the voltage rise time is established (the ftting accuracy is as high as 94.3%). From the high-frequency model in the switching process of the device, an online extraction technology of key parameters (e.g., voltage rise time) is developed. Finally, an experimental platform for IGBT degradation state estimation is established, and the feasibility of IGBT degradation state estimation based on apparent junction temperature is proved, especially the degradation of bonding-wire and the gate-oxide-layer. The experimental results show that the proposed IGBT degradation state estimation technique based on apparent junction temperature is a reliable online estimation method with non-contact, high accuracy, and comprehensiveness.     

Surface Control and Electrical Tuning of MXene Electrode for Flexible Self-Powered Human–Machine Interaction

MXene materials emerge as promising candidates for energy harvesting and storage application. In this study, the effect of the surface chemistry on the work function of MXenes, which determines the performance of MXene-based triboelectric nanogenerator (TENG), is elucidated. First-principles calculations reveal that the surface functional group greatly influences MXene work function:  OH termination reduces the work function with respect to that of bare surface, while  F and  Cl increase it. Then, work functions are experimentally determined by Kelvin probe force microscopy. The MXene prepared by gentle etching at 40 °C for 48 h (GE_40/48) has the largest work function. Furthermore, an electron-cloud potential-well model is established to explain the mechanism of electron emission-dominated charge transfer and assemble a triboelectric device to verify experimentally its conclusions. It is found that GE_40/48 has the best performance with a 281 V open-circuit voltage, 9.7 µA short-current current, and storing 1.019 µC of charge, which is consistent with the model. Last, a patterned TENG is demonstrated for self-powered human–machine interaction application. This finding enhances the understanding of the inherent mechanism between the surface structure and the output performance of MXene-based TENG, which can be applied to other TENG based on 2D materials.     

Ultraprecise 3D Printed Graphene Aerogel Microlattices on Tape for Micro Sensors and E-Skin

3D printed graphene aerogels hold promise for flexible sensing fields due to their flexibility, low density, conductivity, and piezo-resistivity. However, low printing accuracy/fidelity and stochastic porous networks have hindered both sensing performance and device miniaturization. Here, printable graphene oxide (GO) inks are formulated through modulating oxygen functional groups, which allows printing of self-standing 3D graphene oxide aerogel microlattice (GOAL) with an ultra-high printing resolution of 70 µm. The reduced GOAL (RGOAL) is then stuck onto the adhesive tape as a facile and large-scale strategy to adapt their functionalities into target applications. Benefiting from the printing resolution of 70 µm, RGOAL tape shows better performance and data readability when used as micro sensors and robot e-skin. By adjusting the molecular structure of GO, the research realizes regulation of rheological properties of GO hydrogel and the 3D printing of lightweight and ultra-precision RGOAL, improves the sensing accuracy of graphene aerogel electronic devices and realizes the device miniaturization, expanding the application of graphene aerogel devices to a broader field such as micro robots, which is beyond the reach of previous reports.     

Doped/Undoped A1-A2 Typed Copolymers as ETLs for Highly Efficient Organic Solar Cells

The electron transport layer (ETL) is a critical component in achieving high device performance and stability in organic solar cells. Conjugated polyelectrolytes (CPEs) have become an attractive alternative due to film-forming properties and ease of preparation. However, p-type CPEs generally exhibit poor charge mobility and conductivity, incorporation of electron-withdrawing units forming alternated D-A conjugated backbone can make up for these deficiencies. Herein, the ratio of electron withdrawing moieties are further increased and two poly(A1-alt-A2) typed PIIDNDI-Br and PDPPNDI-Br based on the combination of naphthalene diimide (NDI) with isoindigo (IID) or diketopyrrolopyrrole (DPP) via direct arylation polycondensation are synthesized. These CPEs possess excellent alcohol solubility, a suitable lowest unocuppied molecular orbital energy level, and work function tunability. Surprisingly, the incorporation of IID and DPP units generate distinct self-doping behaviors, which are confirmed by UV–vis absorption and ESR spectra. However, no matter doped or undoped, both CPEs present better charge-transporting properties and conductivity when utilized as ETLs. The PIIDNDI-Br and PDPPNDI-Br display good universal compatibility with the blend of PM6:Y6 and PM6:L8-BO, and PCEs of 18.32% and 18.36% are obtained, respectively, which also present excellent storage stability. In short, the combination of two different acceptors demonstrates an efficient strategy to design highly efficient ETLs for high performance photovoltaic devices.     

Unsupervised model-driven neural network based image denoising for transmission line monitoring

With the expansion of smart grid and Internet of things (IoT) technology, edge computing has a wide variety of applications in these domains. The criteria for real-time monitoring and accuracy are particularly high in the field of online real-time monitoring of electricity lines. Based on edge technology, high-quality real-time monitoring can be performed for transmission lines using image processing techniques. Therefore, we propose an image denoising method, which can learn clean images using a stream-based generative model. The stream model uses a two-stage approach in the network to handle the different training periods of denoising separately. Experimental results show that the proposed method has good denoising performance.     

Reduced Graphene Oxides Modified Bi2Te3 Nanosheets for Rapid Photo-Thermoelectric Catalytic Therapy of Bacteria-Infected Wounds

Temperature variation-induced thermoelectric catalytic efficiency of thermoelectric material is simultaneously restricted by its electrical conductivity, Seebeck coefficient, and thermal conductivity. Herein, Bi₂Te₃ nanosheets are in situ grown on reduced graphene oxides (rGO) to generate an efficient photo-thermoelectric catalyst (rGO-Bi₂Te₃). This system exhibits phonon scattering effect and extra carrier transport channels induced by the formed heterointerface between rGO and Bi₂Te₃, which improves the power factor value and reduces thermal conductivity, thus enhancing the thermoelectric performance of 2.13 times than single Bi₂Te₃. The photo-thermoelectric catalysis of rGO-Bi₂Te₃ significantly improves the reactive oxygen species yields, resulting from the effective electron–hole separation caused by the unique thermoelectric field and heterointerfaces of rGO-Bi₂Te₃. Correspondingly, the electrospinning membranes containing rGO-Bi₂Te₃ nanosheets exhibit high antibacterial efficiency in vivo (99.35 ± 0.29%), accelerated tissue repair ability, and excellent biosafety. This study provides an insight into heterointerface design in photo-thermoelectric catalysis.     

Piezoelectric Nanostructured Surface for Ultrasound-Driven Immunoregulation to Rescue Titanium Implant Infection

Treating bacterial biofilm infections on implanted materials remains challenging in clinical practice, as bacteria can be resistant by weakening the host defense from immune cells like macrophages. Herein, a metal-piezoelectric hetero-nanostructure with mechanical energy-driven antimicrobial property is in situ constructed on the Ti implant. Under ultrasonic irradiation, the formed piezotronic Ti (piezoTi) can promote the generation of reactive oxygen species (ROS) by facilitating local charge transfer at the surface, thus leading to piezodynamic killing of Staphylococcus aureus (S. aureus) while downregulating biofilm-forming genes. In addition, the stimulated macrophages on piezoTi display potent phagocytosis and anti-bacterial activity through the activation of PI3K-AKT and MAPK pathway. As a demonstration, one-time ultrasound irradiation of piezoTi pillar implanted in an osteomyelitis model efficiently eliminates the S. aureus biofilm infection and rescues the implant with enhanced osteointegration. By the synergistic effect of ultrasound-driven piezodynamic therapy and immuno-regulation, the proposed piezoelectric nanostructured surface can endow Ti implants with highly efficient antibacterial performance in an antibiotic-free, noninvasive, and on-demand manner.