Self-Adhesive Polydimethylsiloxane Foam Materials Decorated with MXene/Cellulose Nanofiber Interconnected Network for Versatile Functionalities

Polydimethylsiloxanes (PDMS) foam as one of next-generation polymer foam materials shows poor surface adhesion and limited functionality, which greatly restricts its potential applications. Fabrication of advanced PDMS foam materials with multiple functionalities remains a critical challenge. In this study, unprecedented self-adhesive PDMS foam materials are reported with worm-like rough structure and reactive groups for fabricating multifunctional PDMS foam nanocomposites decorated with MXene/cellulose nanofiber (MXene/CNF) interconnected network by a facile silicone foaming and dip-coating strategy followed by silane surface modification. Interestingly, such self-adhesive PDMS foam produces strong interfacial adhesion with the hybrid MXene/CNF nano-coatings. Consequently, the optimized PDMS foam nanocomposites have excellent surface super-hydrophobicity (water contact angle of ≈159^o), tunable electrical conductivity (from 10⁻⁸ to 10 S m⁻¹), stable compressive cyclic reliability in both wide-temperature range (from −20 to 200 ^oC) and complex environments (acid, sodium, and alkali conditions), outstanding flame resistance (LOI value of >27% and low smoke production rate), good thermal insulating performance and reliable strain sensing in various stress modes and complex environmental conditions. It provides a new route for the rational design and development of advanced PDMS foam nanocomposites with versatile multifunctionalities for various promising applications such as intelligent healthcare monitoring and fire-safe thermal insulation.     

Improved aquila optimization-based parameter evaluation framework and meta-heuristic algorithm in radio-over-fiber SpatialMux multi-input multi-output long-term evolution system

In heterogeneous access network, Multiple-Input Multiple-Output (MIMO) radio-over-fiber (RoF) system is an efficient approach for multiple signal transmission with low cost and complexity. The performance of RoF fronthaul system in MIMO system will be varied with different nonlinear effects. By adjusting various transmission parameters, such as the input signal power or the laser bias current, the nonlinear impacts produced by the RoF system can be reduced. In this paper, a novel algorithm Improved Aquila Optimization (IAO) is proposed to optimize transmission circumstances of MIMO RoF system. It determines the appropriate bias current for both lasers and Radio Frequency (RF) signal power in a short period. The input signals are wavelength multiplexed with Intensity Modulation and Direct Detection (IM/DD) applied. The carrier as well as transmission frequency is governed by the MIMO-Long-Term Evolution (LTE) standard. The proposed system is implemented in MATLAB, and the performance is evaluated. The experimental results show that fast convergence and trade-off between noise and nonlinearity are obtained with varying bandwidth. In the experimental scenario, the maximum Error Vector Magnitude (EVM) of 1.88, 3.14, and signal-to-noise ratio (SNR) of 3.204, and 2.698 was attained for both quadrature phase shift keying (QPSK) and quadrature amplitude modulation (QAM) modulation. [Correction added on 24 April 2023, after first online publication: the SNR values were corrected in the preceding sentence.] For 100 iterations, the processing time was reduced to 0.137 s. When compared with the conventional state-of-the-art approaches, the accuracy and computational complexity of the proposed approach are improved.     

Kinetically Accelerating Elementary Steps via Bridged Ru-H State for the Hydrogen-Evolution in Anion-Exchange Membrane Electrolyzer

Designing hydrogen evolution reaction (HER) electrocatalysts for facilitating its sluggish adsorption kinetics is crucial in generating green hydrogen via sustainable water electrolysis. Herein, a high-performance ultra-low Ruthenium (Ru) catalyst is developed consisting of atomically-layered Ru nanoclusters with adjacent single Ru sites, which executs a bridging-Ru-H activation strategy to kinetically accelerate the HER elementary steps. Owing to its optimal electronic structure and unique adsorption configuration, the hybrid Ru catalyst simultaneously displayed a drastically reduced overpotential of 16 mV at 10 mA cm⁻² as well as a low Tafel slope of 35.2 mV dec⁻¹ in alkaline electrolyte. When further coupled with a commercial IrO₂ anode catalyst, the ensembled anion-exchange membrane water electrolyzer achievs a current density of 1.0 A cm⁻² at a voltage of only 1.70 V_cell. In situ spectroscopic analysis verified that Ru single atom and atomically-layered Ru nanoclusters in the hybrid materials play a critical role in facilitating water dissociation and weakening *H adsorption, respectively. Theoretical calculations further elucidate the underlaying mechanism, suggesting that the dissociated proton at the single atom Ru site orients itself adjacently with Ru nanoclusters in a bridged structure through targeted charge transfer, thus promoting Volmer-Heyrovsky dynamics and boosting the HER activity.     

Electret Molecular Configuration Induced Programmable Photonic Memory for Advanced Logic Operation and Data Encryption

Nonvolatile organic photonic transistor (OPT) memories have attracted widespread attention due to their nondestructive readout, remote controllability, and robust tunability. Developing electrets with similar molecular structures but different memory behaviors and light-responsive features is crucial for light-wavelength-modulated data encryption. However, reported OPT memories have yet to meet this challenge. Here a new electret molecule (“H-PDI”) is developed via reconfiguring the linear perylene diimide molecule (“L-PDI”) to a helical shape. Respectively incorporating H-PDI and L-PDI into the floating gate layer results to H-PDI OPT and L-PDI OPT. Attributing to their remarkably different electronic structures and energy bandgaps, H-PDI OPT and L-PDI OPT preferably respond to 405 and 532 nm light irradiation, respectively. Upon electrical programming, data can be written and stored in both memories with good retention features and a high “1”/“0” state current ratio over 10⁵, though the data can only be erased by light with correct wavelengths, rather than the electrical field. Moreover, data stored in a memory array consisting of both H-PDI OPT and L-PDI OPT can only be read out by correct inputs, and wrong inputs will lead to highly deceptive outputs. This study provides a general design strategy of OPT for advanced data encryption and protection.     

On-chip Diamond MEMS Magnetic Sensing through Multifunctionalized Magnetostrictive Thin Film

Electrically integrable, high-sensitivity, and high-reliability magnetic sensors are not yet realized at high temperatures (500 °C). In this study, an integrated on-chip single-crystal diamond (SCD) micro-electromechanical system (MEMS) magnetic transducer is demonstrated by coupling SCD with a large magnetostrictive FeGa film. The FeGa film is multifunctionalized to actuate the resonator, self-sense the external magnetic field, and electrically readout the resonance signal. The on-chip SCD MEMS transducer shows a high sensitivity of 3.2 Hz mT⁻¹ from room temperature to 500 °C and a low noise level of 9.45 nT Hz^−1/2 up to 300 °C. The minimum fluctuation of the resonance frequency is 1.9 × 10⁻⁶ at room temperature and 2.3 × 10⁻⁶ at 300 °C. An SCD MEMS resonator array with parallel electric readout is subsequently achieved, thus providing a basis for the development of magnetic image sensors. The present study facilitates the development of highly integrated on-chip MEMS resonator transducers with high performance and high thermal stability.     

含氢储能的多源联合发电系统调度研究

风电和光伏发电具有间歇性和随机性,为了降低在多源联合发电系统中的弃风弃光率,采用含氢储能系统和火电机组配合来平滑风电和光电机组出力。文中以系统运行成本最小和弃电惩罚成本最小为目标,以系统功率平衡、火电机组出力和爬坡、热备用、风电和光电出力及储能系统储氢罐容量、电解槽和燃料电池功率等为约束条件构建了多源联合发电系统日前调度模型。通过YALMIP工具箱对模型进行编程,并调用CPLEX对编写的程序进行求解。对含有风电、光电、火电机组以及储能系统的多源联合发电系统进行算例分析,通过对比有无储能系统的弃风弃光量和系统总运行成本,证明了含氢储能系统可以有效降低系统的弃风弃光率,并提高系统的经济性。     

Visual video evaluation association modeling based on chaotic pseudo-random multi-layer compressed sensing for visual privacy-protected keyframe extraction

In current society, artificial intelligence processing technology offers convenient video monitoring, but also raises the risk of privacy leakage. Theoretically, the data used in intelligent video processing methods may directly convey visual information containing private content. For the above problem, this paper uses a multi-layer visual privacy-protected (VPP) coding method to blur private content in the video at the visual level, while avoiding the loss of important visual features contained in the video as much as possible. And this provides a guarantee of the quality of the subsequent keyframe extraction step. Then a visual evaluation algorithm is proposed for assessing the quality of VPP-encoded video privacy protection. And the experiment shows that the results are consistent with those of subjective evaluation. In addition, for VPP-encoded video, we propose an unsupervised two-layer clustering keyframe extraction method with corresponding performance evaluation index. Finally, an association model is established to balance the privacy protection quality and the keyframe extraction performance.     

新工科理念下思政元素与电子实践教学的融合探索

为了落实建设新工科和大思政教育模式的育人理念,结合专业发展,本文以工程训练中的电子创新实践课程为例,研究思政元素如何融入实践教学的各个环节,具体探讨在设定教学目标、教学内容、优化教学方法、教学考核设置及课后总结交流等环节中,将思政元素与专业课程相互贯通融合的教学设计理念与方法。     

一种实时多尺度目标检测识别算法

无人机目标检测与识别任务中,目标随着飞行高度的改变尺寸发生显著变化。常规目标检测模型中,获取的小目标细节信息有限,检测精度较低;而适用于小目标的实时检测模型往往容易丢失大目标的背景信息,降低大目标的检测精度。针对以上多尺度目标检测识别任务难点,提出一种基于改进特征金字塔网络(Feature Pyramid Network, FPN)结构的实时多尺度目标检测识别模型。该模型通过增加特征金字塔层级覆盖更广的目标尺度,获取更为丰富的目标信息;同时,利用跨连接增加不同尺度特征融合的多样性,降低特征传导距离,保留更加完整的尺度特征来提高模型检测识别多尺度目标的性能。通过实验发现,相比于原始网络结构和相同特征层级的四层特征金字塔结构,加入改进特征金字塔结构的多尺度目标检测模型识别性能得到了提升。     

扩频体制低轨卫星通信信号捕获与跟踪系统设计

针对扩频体制下低轨卫星信号的捕获及跟踪等系统设计实现问题,根据卫星信号模型进行了捕获及跟踪算法设计,重点对基于快速傅里叶变换的快速捕获算法、锁频环、锁相环和码跟踪环路进行了设计,并进行了工程系统实现。试验验证表明,该系统可以实现码分多址体制低轨卫星信号捕获、跟踪处理,工作性能参数满足系统需求。