Small but mighty:Empowering sodium/potassium-ion battery performance with S-doped SnO_(2) quantum dots embedded in N,S codoped carbon fiber network

SnO_(2) has been extensively investigated as an anode material for sodium-ion batteries(SIBs)and potassium-ion batteries(PIBs)due to its high Na/K storage capacity,high abundance,and low toxicity.However,the sluggish reaction kinetics,low electronic conductivity,and large volume changes during charge and discharge hinder the practical applications of SnO_(2)-based electrodes for SIBs and PIBs.Engineering rational structures with fast charge/ion transfer and robust stability is important to overcoming these challenges.Herein,S-doped SnO_(2)(S-SnO_(2))quantum dots(QDs)(≈3 nm)encapsulated in an N,S codoped carbon fiber networks(S-SnO_(2)-CFN)are rationally fabricated using a sequential freeze-drying,calcination,and S-doping strategy.Experimental analysis and density functional theory calculations reveal that the integration of S-SnO_(2) QDs with N,S codoped carbon fiber network remarkably decreases the adsorption energies of Na/K atoms in the interlayer of SnO_(2)-CFN,and the S doping can increase the conductivity of SnO_(2),thereby enhancing the ion transfer kinetics.The synergistic interaction between S-SnO_(2) QDs and N,S codoped carbon fiber network results in a composite with fast Na+/K+storage and extraordinary long-term cyclability.Specifically,the S-SnO_(2)-CFN delivers high rate capacities of 141.0 mAh g^(−1) at 20 A g^(−1) in SIBs and 102.8 mAh g^(−1) at 10 A g^(−1) in PIBs.Impressively,it delivers ultra-stable sodium storage up to 10,000 cycles at 5 A g^(−1) and potassium storage up to 5000 cycles at 2 A g^(−1).This study provides insights into constructing metal oxide-based carbon fiber network structures for high-performance electrochemical energy storage and conversion devices.

Impairments Approximations in Assembled mmWave and Radio Over Fiber Network

The fiber nonlinearity and phase noise(PN)are the focused impairments in the optical communication system,induced by high-capacity transmission and high laser input power.The channels include high-capacity transmissions that cannot be achieved at the end side without aliasing because of fiber nonlinearity and PN impairments.Thus,addressing of these distortions is the basic objective for the 5G mobile network.In this paper,the fiber nonlinearity and PN are investigated using the assembled methodology of millimeter-wave and radio over fiber(mmWave-RoF).The analytical model is designed in terms of outage probability for the proposed mmWave-RoF system.The performance of mmWave-RoF against fiber nonlinearity and PN is studied for input power,output power and length using peak to average power ratio(PAPR)and bit error rate(BER)measuring parameters.The simulation outcomes present that the impacts of fiber nonlinearity and PNcan be balanced for a huge capacity mmWave-RoF model applying input power carefully.

Designing metal-organic framework fiber network reinforced polymer electrolytes to provide continuous ion transport in solid state lithium metal batteries

Polyethylene oxide(PEO)-based solid-state electrolytes are considered ideal for electrolyte materials in solid-state lithium metal batteries(SSLMBs).However,practical applications are hindered by the lower conductivity and poor interfacial stability.Here,we propose a strategy to construct a three-dimensional(3D)fiber network of metal-organic frameworks(MOFs).Composite solid electrolytes(CSEs)with continuous ion transport pathways were fabricated by filling a PEO polymer matrix in fibers containing interconnected MOFs.This 3D fiber network provides a fast Li+transport path and effectively improves the ionic conductivity(1.36×10^(-4) S·cm^(-1),30℃).In addition,the network of interconnected MOFs not only effectively traps the anions,but also provides sufficient mechanical strength to prevent the growth of Li dendrites.Benefiting from the advantages of structural design,the CSEs stabilize the Li/electrolyte interface and extend the cycle life of the Li-symmetric cells to 3000 h.The assembled SSLMBs exhibit excellent cycling performance at both room and high temperatures.In addition,the constructed pouch cells can provide an areal capacity of 0.62 mA·h·cm^(-2),which can still operate under extreme conditions.This work provides a new strategy for the design of CSEs with continuous structure and stable operation of SSLMBs.

Characterization and Modeling of Mechanical Properties of Additively Manufactured Coconut Fiber-Reinforced Polypropylene Composites

In the face of the increased global campaign to minimize the emission of greenhouse gases and the need for sustainability in manufacturing, there is a great deal of research focusing on environmentally benign and renewable materials as a substitute for synthetic and petroleum-based products. Natural fiber-reinforced polymeric composites have recently been proposed as a viable alternative to synthetic materials. The current work investigates the suitability of coconut fiber-reinforced polypropylene as a structural material. The coconut fiber-reinforced polypropylene composites were developed. Samples of coconut fiber/polypropylene (PP) composites were prepared using Fused Filament Fabrication (FFF). Tests were then conducted on the mechanical properties of the composites for different proportions of coconut fibers. The results obtained indicate that the composites loaded with 2 wt% exhibited the highest tensile and flexural strength, while the ones loaded with 3 wt% had the highest compression strength. The ultimate tensile and flexural strength at 2 wt% were determined to be 34.13 MPa and 70.47 MPa respectively. The compression strength at 3 wt% was found to be 37.88 MPa. Compared to pure polypropylene, the addition of coconut fibers increased the tensile, flexural, and compression strength of the composite. In the study, an artificial neural network model was proposed to predict the mechanical properties of polymeric composites based on the proportion of fibers. The model was found to predict data with high accuracy.

Delay Time Measurement and Comparison of Protection Strategies with One-Link Failed Domestic Optical Fiber Networks in Taiwan

In this paper, we study the protection strategies of domestic optical fiber networks in Taiwan. Delay time experiment of two one-link failed cases are also reported and compared. We can get best protection strategy and bypass the optical transmission signal at shortest delay time.

An Offloading Scheme Leveraging on Neighboring Node Resources for Edge Computing over Fiber-Wireless (FiWi) Access Networks

The computation resources at a single node in Edge Computing(EC)are commonly limited,which cannot execute large scale computation tasks.To face the challenge,an Offloading scheme leveraging on NEighboring node Resources(ONER)for EC over Fiber-Wireless(FiWi)access networks is proposed in this paper.In the ONER scheme,the FiWi network connects edge computing nodes with fiber and converges wireless and fiber connections seamlessly,so that it can support the offloading transmission with low delay and wide bandwidth.Based on the ONER scheme supported by FiWi networks,computation tasks can be offloaded to edge computing nodes in a wider range of area without increasing wireless hops(e.g.,just one wireless hop),which achieves low delay.Additionally,an efficient Computation Resource Scheduling(CRS)algorithm based on the ONER scheme is also proposed to make offloading decision.The results show that more offloading requests can be satisfied and the average completion time of computation tasks decreases significantly with the ONER scheme and the CRS algorithm.Therefore,the ONER scheme and the CRS algorithm can schedule computation resources at neighboring edge computing nodes for offloading to meet the challenge of large scale computation tasks.

Relationship between fatigue life of asphalt concrete and polypropylene/polyester fibers using artificial neural network and genetic algorithm

While various kinds of fibers are used to improve the hot mix asphalt(HMA) performance, a few works have been undertaken on the hybrid fiber-reinforced HMA. Therefore, the fatigue life of modified HMA samples using polypropylene and polyester fibers was evaluated and two models namely regression and artificial neural network(ANN) were used to predict the fatigue life based on the fibers parameters. As ANN contains many parameters such as the number of hidden layers which directly influence the prediction accuracy, genetic algorithm(GA) was used to solve optimization problem for ANN. Moreover, the trial and error method was used to optimize the GA parameters such as the population size. The comparison of the results obtained from regression and optimized ANN with GA shows that the two-hidden-layer ANN with two and five neurons in the first and second hidden layers, respectively, can predict the fatigue life of fiber-reinforced HMA with high accuracy(correlation coefficient of 0.96).

Combined Transmission Interference Spectrum of No Core Fiber and BP Neural Network for Concentration Sensing Research

To investigate wavelength response of the no core fiber（NCF）interference spectrum to concentration,a three-layer back propagation（BP）neural network model was established to optimize the concentration sensing data.In this method,the measured wavelength and the corresponding concentration were trained by a BP neural network,so that the accuracy of the measurement system was optimized.The wavelength was used as the training set and got into the input layer of the three layer BP network model which is used as the input value of the network,and the corresponding actual concentration value was used as the output value of the network,and the optimal network structure was trained.This paper discovers a preferable correlation between the predicted value and the actual value,where the former is approximately equal to the latter.The correlation coefficients of the measured and predicted values for a sucrose concentration were 1.000 89 and 1.003 94;similarly,correlations of0.999 51 and 1.018 8 for a glucose concentration were observed.The results demonstrate that the BP neural network can improve the prediction accuracy of the nonlinear relationship between the interference spectral data and the concentration in NCF sensing systems.

浅谈配网自动化光纤通信系统施工技术

为了保证配网自动化光纤通信系统的稳定运行和信号的可靠传输,论文简要介绍了配网自动化光纤通信系统,对配网自动化光纤通信技术在施工过程中的施工要求、关键要点和注意事项进行了探究。

高密度聚乙烯三维网状纳微米纤维的强伸性能

为实现高密度聚乙烯三维网状纳微米纤维(PENFs)的自主化规模化生产,以高密度聚乙烯和二氯甲烷为原料,通过高压闪喷纺丝设备成功制备了性能优异的PENFs,采用响应面法对纺丝过程中各工艺参数进行优化,并对其力学性能和耐候性能进行分析。结果表明:PENFs的最佳制备工艺条件为纺丝温度176.3℃、纺丝压力8.6 MPa、纺丝溶液质量分数8.0%,此时制得的PENFs的断裂强度和断裂伸长率分别可达到29.1 cN/dtex和99.9%,优于芳纶和涤纶等常规纤维;定伸长和定载荷条件下,PENFs的弹性回复能力随着拉伸次数和载荷的增加而逐渐降低,拉伸伸长为5%时PENFs纤维的弹性回复率可达到92.8%且拉伸10次后降低至75.5%,拉伸载荷为1.2 N时PENFs纤维的弹性回复率为84.6%;放置在室外20 d内PENFs纤维的强伸性能损失较小,30 d后断裂强度和断裂伸长率明显降低,但纤维外貌并无明显变化。

考虑信息泄露影响的光纤传感网络传输数据安全导入方法

为了提高对光纤传感网络传输数据安全传输能力,提出基于信息泄漏加密传输的光纤传感网络传输数据安全导入方法。采用离散混沌时间序列同步调制方法实现对光纤传感网络传输数据导入过程中调制编码处理,根据混沌随机编码特性实现对光纤传感网络传输数据过程中的同步输出稳定性调节和自主随机编码,构建光纤传感网络信息传输泄漏抑制的加密密钥,通过Logistics映射实现对光纤传感网络传输数据导入过程中的信息泄漏加密重传,根据光纤传感网络传输数据的混合敏感密钥表征和算术编码,实现信息泄漏控制和数据安全导入。实验结果表明,采用该方法进行光纤传感网络传输数据导入的加密性能较好,其光纤传感网络传输数据已加密比特序列的识别率为98%,误码率仅为2.7∗10-9%,抗泄漏能力达到了0.970,并且导入后的数据完整度达到了0.996,说明该方法具备了较强的加密效果、抗泄漏能力,实现数据的安全导入和加密传输。

Green Architecture for Dense Home Area Networks Based on Radio-over-Fiber with Data Aggregation Approach

The high-density population leads to crowded cities. The future city is envisaged to encompass a large-scale network with diverse applications and a massive number of interconnected heterogeneous wireless-enabled devices. Hence, green technology elements are crucial to design sustainable and future-proof network architectures. They are the solutions for spectrum scarcity, high latency, interference, energy efficiency, and scalability that occur in dense and heterogeneous wireless networks especially in the home area network （HAN）. Radio-over-fiber （ROF） is a technology candidate to provide a global view of HAN＇s activities that can be leveraged to allocate orthogonal channel communications for enabling wireless-enabled HAN devices transmission, with considering the clustered-frequency-reuse approach. Our proposed network architecture design is mainly focused on enhancing the network throughput and reducing the average network communications latency by proposing a data aggregation unit （DAU）. The performance shows that with the DAU, the average network communications latency reduces significantly while the network throughput is enhanced, compared with the existing ROF architecture without the DAU.

物联网环境下复杂光纤通信传输网络节点调度

为了解决物联网环境下,光纤通信传输网络节点能耗高、调度效率低的问题,提出一种物联网环境下复杂光纤通信传输网络节点调度方法。在物联网环境下,分析光纤通信传输网络节点的分布情况,根据动态联盟理论,以最快调度速度和最小投资为目标,构建复杂光纤通信传输网络节点调度模型。通过蚁群和粒子群算法相结合的融合算法展开全部搜索,获取最佳调度方案,实现光纤通信传输网络节点调度。实验结果表明,所提方法的节点平均能耗在6.0 mJ以下,LBF值始终高于0.20,且节点调度耗时始终低于200 ms,具有良好的调度效果。

基于GOOSE反馈机制的智能变电站过程层网络备用方法

智能变电站过程层光纤网络一旦发生故障,会使二次系统功能失效,故障修复效率低,可靠性降低。为此,提出一种基于GOOSE反馈机制的智能变电站过程层网络备用方法。文章根据二次系统对过程层网络的传输要求,对间隔抖动、丢帧率和光功率等指标建立相应的危害程度量化模型;建立了备用光纤光口单指标和综合指标启动判据;利用GOOSE反馈机制实现对主光纤光口的备用。仿真表明,所提方法可快速完成故障光纤光口的备用切换,提高了过程层网络的可靠性。

Application of the Spectrum Peak Positioning Technology Based on BP Neural Network in Demodulation of Cavity Length of EFPI Fiber Optical Sensor

An Extrinsic Fabry-Perot Interferometric (EFPI) fiber optical sensor system is an online testing system for the gas density. The system achieves the measurement of gas density information mainly by demodulating the cavity length of EF- PI fiber optical sensor. There are many ways to achieve the demodulation of the cavity length. For shortcomings of the big intensity demodulation error and complex structure of phase demodulation, this paper proposes that BP neural net-work is used to locate the special peak points in normalized interference spectrum and combining the advantages of the unimodal and bimodal measurement achieves the demodulation of the cavity length. Through online simulation and actual measurement, the results show that the peak positioning technology based on BP neural network can not only achieve high-precision demodulation of the cavity length, but also achieve an absolute measurement of cavity length in large dynamic range.

光纤时间频率同步技术及应用

时间是人类目前测量和复现不确定度指标最高的物理量,代表了人类科技发展的最高水平。光纤时频同步技术经过几十年的发展,目前已广泛应用于量子计量、射电干涉测量、定位导航、现代通信、电力电网、高能物理、大地测量等诸多领域,成为人类社会高效运行的重要支撑。得益于光纤时频同步技术的高可靠性和高稳定度,综合原子时“分布式”和“实时性”这一长期存在的矛盾得到了解决。文章介绍了光纤时频同步技术的发展历史、各技术路径的研究现状,以及基于北京地区光纤时频同步网生成的分布式实时综合原子时。在此基础上,指出光纤时频同步的发展重点正从技术研究转为大规模网络化应用,开展基于光网络的多功能、多应用融合研究,实现一体化通信、感知、计算、测量、控制,将是未来的重要发展趋势。

融合短时傅里叶变换和卷积神经网络的托辊故障诊断方法

托辊故障已成为带式输送机运行中的常见问题。若不能及时诊断托辊故障,则将严重制约带式输送机的安全运行。为了解决上述问题,基于某矿带式输送机中间段托辊的实际运行工况,提出了一种融合短时傅里叶变换(short-time Fourier transform,STFT)和卷积神经网络(convolutional neural network,CNN)的托辊故障诊断方法。首先,以分布式光纤为基础,对托辊在正常、轴承损坏及筒皮断裂工况下运行时的振动信号进行采集并作STFT处理,得到对应的时频图样本集,并将其分为训练集和测试集。然后,将训练集输入CNN模型以进行诊断模型训练,在训练过程中不断更新不同工况下托辊的运行状态特征。最后,将训练好的CNN模型应用于测试集,并输出托辊运行状态的识别结果。结果表明,所构建的CNN模型的识别准确率高达99.6%。基于所提出的故障诊断方法,在某矿上开展现场实验,以进一步验证CNN模型的识别准确率。实验结果表明,CNN模型对带式输送机中间段托辊的运行状态有较高的识别准确率,可达96.5%,与测试集上的识别准确率仅相差3.1个百分点,说明所提出的故障诊断方法具有一定的可靠性。后续可通过不断增加不同工况下托辊的运行数据来提高该故障诊断方法的鲁棒性,这可为煤矿企业有效诊断托辊故障提供有力的理论基础。

浅层膨胀土及其纤维改良土的剪切强度特性

与膨胀土工程灾害密切相关的浅层膨胀土受到的围压通常较低,其力学特性有别于高围压下的情形.通过三轴剪切试验比较高、低围压下膨胀土的剪切行为及剪切强度的非线性特征,探讨聚丙烯纤维改良浅层膨胀土的剪切特性及加固机理.结果表明,浅层膨胀土剪切强度具有明显的非线性,可用幂函数表征.随着土体中水的质量分数增大和围压减小,膨胀土剪切强度非线性更加明显.采用高围压下的抗剪强度参数试验结果会导致浅层饱和膨胀土的黏聚力被高估225.7%、内摩擦角被低估42.5%.掺入纤维后膨胀土的剪切强度明显提高,提升幅度与土体中的三维纤维网状结构的形成度有关.增大纤维长度可以有效降低剪切强度衰减率,继而消弱膨胀土的应变软化效应;过长的纤维在膨胀土内容易弯曲和扭折,会导致纤维-膨胀土界面作用随着土体变形而逐渐劣化.

基于非相干光频域反射的多芯光纤网络链路缺陷智能检测

为了保证通信安全稳定、数据传输完整,提出了一种基于非相干光频域反射的多芯光纤网络链路缺陷智能检测。先构建多芯光纤网络数学模型,约束光纤节点映射和频谱分配,使频谱数量最少的同时占用的频隙数最大。然后利用分簇检测建立数据传输链路模型,得出通信传输函数,根据相关匹配滤波器调整链路,通过波特间隔均衡完成链路数据采集。最后运用非相干光频域反射步进频率调制产生的瑞利散射光波,结合傅里叶逆变换获得网络健康状况空间分布位置,实现多芯光纤网络链路缺陷智能检测。实验结果表明,所提方法能够准确检测出链路缺陷,对链路阻塞缺陷检测、链路平均故障风险检测率、链路频谱利用率缺陷检测误差分别小于0.4%、0.2%和0.5,且检测时长控制在1.5 s以内,可帮助网络及时恢复运行。

Reflective Ladder Topology Network Based on White Light Fiber-Optic Mach-Zehnder Interferometer

In order to improve the multiplexing capability of the optical sensors based on the lower interferential optic fiber sensing technology and the white light fiber-optic Mach-Zehnder interferometer,reflective ladder topology network ( RLT) with tailored formula was proposed. The topology network consists of 6 rungs sensing elements linked by 5 couplers. Two cases with different choices of couplers were contrasted: one is equal coupling ratio,and the other is tailored coupling ratio. Through the simulation of these two cases,the detailed multiplexing capability was analyzed,and accordingly the experiments were also carried out. The simulation results showed that,the tailored formula enhances the multiplexing capability of the structure. In the first case, the maximum number of sensors which can be multiplexed is 8,and in the other case is 12 fiber optic sensors. The experimental results have a good agreement with numerical simulation results. Thus,it is considered expedient to incorporate RLT into large-scale building,grounds,bridges,dams,tunnels,highways and perimeter security.