Broad-Spectral-Range Sustainability and Controllable Excitation of Hyperbolic Phonon Polaritons in α-MoO3

Hyperbolic phonon polaritons (HPhPs) in orthorhombic-phase molybdenum trioxide (α-MoO₃) show in-plane hyperbolicity, great wavelength compression, and ultralong lifetime, therefore holding great potential in nanophotonic applications. However, its polaritonic response in the far-infrared (FIR) range remains unexplored due to challenges in experimental characterization. Here, monochromated electron energy loss spectroscopy (EELS) in a scanning transmission electron microscope (STEM) is used to probe HPhPs in α-MoO₃ in both mid-infrared (MIR) and FIR frequencies and correlate their behaviors with microstructures and orientations. It is found that low structural symmetry leads to various phonon modes and multiple Reststrahlen bands (RBs) over a broad spectral range (over 70 meV) and in different directions (55–63 meV and 119–125 meV along the b-axis, 68–106 meV along the c-axis, and 101–121 meV along the a-axis). These HPhPs can be selectively excited by controlling the direction of swift electrons. These findings provide new opportunities in nanophotonic and optoelectronic applications, such as directed light propagation, hyperlenses, and heat transfer.     

Alloying behavior and novel properties of CoCrFeNiMn high-entropy alloy fabricated by mechanical alloying and spark plasma sintering

An equiatomic CoCrFeNiMn high-entropy alloy was synthesized by mechanical alloying (MA) and spark plasma sintering (SPS). During MA, a solid solution with refined microstructure of 10 nm which consists of a FCC phase and a BCC phase was formed. After SPS consolidation, only one FCC phase can be detected in the HEA bulks. The as-sintered bulks exhibit high compressive strength of 1987 MPa. An interesting magnetic transition associated with the structure coarsening and phase transformation was observed during SPS process.     

移动边缘计算环境下的动态资源分配策略

在通讯设备爆炸式增长的时代,移动边缘计算作为5G通讯技术的核心技术之一,对其进行合理的资源分配显得尤为重要。移动边缘计算的思想是把云计算中心下沉到基站部署(边缘云),使云计算中心更加靠近用户,以快速解决计算资源分配问题。但是,相对于大型的云计算中心,边缘云的计算资源有限,传统的虚拟机分配方式不足以灵活应对边缘云的计算资源分配问题。为解决此问题,提出一种根据用户综合需求变化的动态计算资源和频谱分配算法(DRFAA),采用"分治"策略,并将资源模拟成"流体"资源进行分配,以寻求较大的吞吐量和较低的传输时延。实验仿真结果显示,动态计算资源和频谱分配算法可以有效地降低用户与边缘云之间的传输时延,也可以提高边缘云的吞吐量。     

基于神经网络算法的井下裂缝诊断与堵漏技术

在钻井过程中，常常钻遇不同宽度的井下地层裂缝。钻遇裂缝时容易发生钻井液漏失现象，甚至发生钻井液失返现象，严重影响了安全、高效钻井。目前裂缝封堵的方法常存在封堵成功率不高、堵漏承压能力低的问题，其中一个重要的原因是对井下地层的裂缝宽度等特征认识不清。基于地层裂缝产生的岩石力学机理，确定影响裂缝宽度关键的6个力学和工程因素，并利用神经网络计算的非线性、大数据特点建立了井下地层裂缝宽度的分析模型，模型包含输入层、输出层和3个隐藏层。通过该模型诊断井下裂缝宽度，提高了计算精度，平均误差仅为2.09%，最大误差为5.88%，解决钻井现场仅凭经验判断裂缝误差较大和依靠成像测井成本较高的问题。同时根据神经网络模型诊断得到的裂缝宽度优化堵漏材料的粒径配比，提高了裂缝内的架桥封堵强度和架桥的稳定性，封堵层的承压能力达到12.8 MPa，反向承压能力达到4.5 MPa。现场堵漏试验最高憋压10 MPa，经过封堵作业后大排量循环不漏，达到了裂缝性地层高效堵漏的目的，堵漏一次成功。      

基于新型光纤的传输技术探讨

随着互联网的高速发展，引发了网络流量、电信骨干网流量急速增长，使得网络容量的提升迫在眉睫。目前，100G 系统已经商用，超100G系统能够更有效地解决流量和网络带宽持续增长带来的压力，本文主要介绍新型单模光纤的特性以及探讨基于新型单模光纤的传输技术。     

基于多尺度双线性卷积神经网络的多角度下车型精细识别

针对多角度下车辆出现一定的尺度变化和形变导致很难被准确识别的问题，提出基于多尺度双线性卷积神经网络（MS-B-CNN）的车型精细识别模型。首先，对双线性卷积神经网络（B-CNN）算法进行改进，提出MS-B-CNN算法对不同卷积层的特征进行了多尺度融合，以提高特征表达能力；此外，还采用基于中心损失函数与Softmax损失函数联合学习的策略，在Softmax损失函数基础上分别对训练集每个类别在特征空间维护一个类中心，在训练过程中新增加样本时，网络会约束样本的分类中心距离，以提高多角度情况下的车型识别的能力。实验结果显示，该车型识别模型在CompCars数据集上的正确率达到了93.63%，验证了模型在多角度情况下的准确性和鲁棒性。     

Coupling in situ experiments and modeling – Opportunities for data fusion,machine learning,and discovery of emergent behavior

This paper reviews recent studies, that not only includes both experiments and modeling components, but celebrates a close coupling between these techniques, in order to provide insights into the plasticity and failure of polycrystalline metals. Examples are provided of studies across multiple-scales, including, but not limited to, density functional theory combined with atom probe tomography, molecular dynamics combined with in situ transmission electron miscopy, discrete dislocation dynamics combined with nanopillars experiments, crystal plasticity combined with digital image correlation, and crystal plasticity combined with in situ high energy X-ray diffraction. The close synergy between in situ experiments and modeling provides new opportunities for model calibration, verification, and validation, by providing direct means of comparison, thus removing aspects of epistemic uncertainty in the approach. Further, data fusion between in situ experimental and model-based data, along with data driven approaches, provides a paradigm shift for determining the emergent behavior of deformation and failure, which is the foundation that underpins the mechanical behavior of polycrystalline materials.     

以用户为中心的可见光通信协作传输中训练资源分配算法

以用户为中心的可见光通信协作传输是近年来出现的新架构,这导致虚拟小区之间出现重叠。为避免导频污染问题,每个虚拟小区中的光接入点(AP)或者虚拟小区中选择相同AP的用户发送的训练序列应该是正交的。针对可见光通信中以用户为中心的协作网络,研究训练资源的正交分配问题,提出了一种新的导频分配算法,联合导频分配和用户选择问题,以期最大限度地增加虚拟小区内可被接入的用户数。分析和仿真结果表明,该导频分配方案可以有效改善导频污染问题,提高训练资源利用率,并且相比已有的导频分配方案,性能有所改进。     

Additively manufactured respirators: quantifying particle transmission and identifying system-level challenges for improving filtration efficiency

The COVID-19 pandemic has disrupted the supply chain for personal protective equipment (PPE) for medical professionals, including N95-type respiratory protective masks. To address this shortage, many have looked to the agility and accessibility of additive manufacturing (AM) systems to provide a democratized, decentralized solution to producing respirators with equivalent protection for last-resort measures. However, there are concerns about the viability and safety in deploying this localized download, print, and wear strategy due to a lack of commensurate quality assurance processes. Many open-source respirator designs for AM indicate that they do not provide N95-equivalent protection (filtering 95% of SARS-CoV-2 particles) because they have either not passed aerosol generation tests or not been tested. Few studies have quantified particle transmission through respirator designs outside of the filter medium. This is concerning because several polymer-based AM processes produce porous parts, and inherent process variation between printers and materials also threaten the integrity of tolerances and seals within the printed respirator assembly. No study has isolated these failure mechanisms specifically for respirators. The goal of this paper is to measure particle transmission through printed respirators of different designs, materials, and AM processes. The authors compare the performance of printed respirators to N95 respirators and cloth masks. Respirators in this study printed using desktop- and industrial-scale fused filament fabrication processes and industrial-scale powder bed fusion processes were not sufficiently reliable for widespread distribution and local production of N95-type respiratory protection. Even while assuming a perfect seal between the respirator and the user’s face, although a few respirators provided >90% efficiency at the 100−300 nm particle range, almost all printed respirators provided <60% filtration efficiency. Post-processing procedures including cleaning, sealing surfaces, and reinforcing the filter cap seal generally improved performance, but the printed respirators showed similar performance to various cloth masks. The authors further explore the process-driven aspects leading to low filtration efficiency. Although the design/printer/material combination dictates the AM respirator performance, the identified failure modes originate from system-level constraints and are therefore generalizable across multiple AM processes. Quantifying the limitations of AM in producing N95-type respiratory protective masks advances understanding of AM systems toward the development of better part and machine designs to meet the needs of reliable, functional, end-use parts.