Microstructure and damage evolution of SiCf/PyC/SiC and SiCf/BN/SiC mini-composites: A synchrotron X-ray computed microtomography study

SiC_f/PyC/SiC and SiC_f/BN/SiC mini-composites comprising single tow SiC fibre-reinforced SiC with chemical vapor deposited PyC or BN interface layers are fabricated. The microstructure evolutions of the mini-composite samples as the oxidation temperature increases (oxidation at 1000, 1200, 1400, and 1600?°C in air for 2?h) are observed by scanning electron microscopy, energy dispersive spectrometry, and X-ray diffraction characterization methods. The damage evolution for each component of the as-fabricated SiC_f/SiC composites (SiC fibre, PyC/BN interface, SiC matrix, and mesophase) is mapped as a three-dimensional (3D) image and quantified with X-ray computed tomography. The mechanical performance of the composites is investigated via tensile tests.The results reveal that tensile failure occurs after the delamination and fibre pull-out in the SiC_f/PyC/SiC composites due to the volatilization of the PyC interface at high temperatures in the air environment. Meanwhile, the gaps between the fibres and matrix lead to rapid oxidation and crack propagation from the SiC matrix to SiC fibre, resulting in the failure of the SiC_f/PyC/SiC composites as the oxidation temperature increases to 1600?°C. On the other hand, the oxidation products of B₂O₃ molten compounds (reacted from the BN interface) fill up the fracture, cracks, and voids in the SiC matrix, providing excellent strength retention at elevated oxidation temperatures. Moreover, under the protection of B₂O₃, the SiC_f/BN/SiC mini-composites show a nearly intact microstructure of the SiC fibre, a low void growth rate from the matrix to fibre, and inhibition of new void formation and the SiO₂ grain growth from room to high temperatures. This work provides guidance for predicting the service life of SiC_f/PyC/SiC and SiC_f/BN/SiC composite materials, and is fundamental for establishing multiscale damage models on a local scale.     

Research on hydrophobicity of electrospun Fe3O4/PVDF nanofiber membranes under different preparation conditions

Abstract

Preparation condition can affect the structure and the properties of nanofiber membrane. In order to explore suitable conditions to prepare the Fe₃O₄/PVDF nanofiber membrane with good hydrophobicity, the hydrophobicity of Fe₃O₄/PVDF nanofiber membranes obtained by electrospinning was investigated by changing preparation conditions like weight percentage of Fe₃O₄ nanoparticles, blending quality concentration of poly (vinylidene fluoride) (PVDF) and Fe₃O₄ nanoparticles, and positive voltage. And the variations of hydrophobicity of Fe₃O₄/PVDF nanofiber membranes modified by 1H, 1H, 2H, 2H-perfluorodecyl trimethoxysilane were studied. The results show that the hydrophobicity of Fe₃O₄/PVDF nanofiber membranes has changed under different preparation conditions. The contact angles of samples increased after a modification by 1H, 1H, 2H, 2H-perfluorodecyl trimethoxysilane, which indicates that the hydrophobicity of Fe₃O₄/PVDF nanofiber membranes has been enhanced.     

深度学习识别光网络单元故障的设计与应用

为解决依赖装维上门鉴别光网络单元故障带来的不便,可以从机器视觉入手实现自动化故障识别。近年,ImageNet挑战赛的成功推动了物体识别技术的跨越式发展,特别是基于卷积的深度学习技术在视觉识别方面已经达到人类水平,为光网络单元故障的自动识别提供了技术基础。文章对识别光网络单元的工作状态进行了研究,将设备工作状态分为7个场景,提出了利用手机APP采集图片识别故障的解决方案并投入了实际生产;重点阐述了深度学习模块的设计与实现,提出一种通过算法整合的方式综合运用物体检测和图像分类算法,分3阶段逐步求精,解决了图片过滤,光网络单元型号和状态识别等问题,实现了基于计算机视觉自动识别光网络单元故障。从数据上看产品的端到端准确率超过84%,识别速度达到10 FPS,月均提供服务超过1万人次,在减少用户等待的同时节约了人力资源。     

基于关键水平的水下采油树预防性维修决策方法

为解决电液复合水下采油树在运行过程中工作环境恶劣且复杂、系统要求可靠性高、维修难度大且费用高的问题,建立基于伽马退化过程的水下采油树组件可靠度退化模型和考虑维修花费、停产损失在内的维修成本模型,建立水下采油树系统预防性维修优化目标体系,基于多目标粒子群优化算法对维修策略进行优化。建立的模型可有效描述水下采油树系统的工作特性,最优解能够满足在低维修成本的前提下系统高可靠性的工作要求。     

某进口固体废物“铁精粉”的鉴别方法探析

为了确保不进口污染环境的固体废物，针对某冒充铁精粉的进口固体废物，通过外观、成分、物相分析进行了系统的鉴别。确定样品主要为经研磨加工的氧化铁皮，属于禁止进口的固体废物——轧钢产生的氧化皮。     

Eu@C86 isomers: Calculated relative populations

Abstract

Relative populations of four energy-lowest IPR (isolated-pentagon-rule) isomers of Eu@C₈₆ are computed using the Gibbs energy based on characteristics from density functional theory calculations (M06-2X/3-21G?～?SDD entropy term, M06-2X/6-31G*～SDD or B2PLYP(D)/6-31G*～SDD energetics). The calculations confirm that the recently isolated Eu@C₁(7)-C₈₆ species is a major isomer in a relevant temperature region. Relationship to the empty C₈₆ cages is discussed, too.     

Effects of Cooling Rate and Component on the Microstructure and Mechanical Properties of Mg–Zn–Y Alloys

The microstructure and mechanical properties of Mg–6Zn–1Y and Mg–6Zn–3Y(wt%) alloys under different cooling rates were investigated. The results show that the second dendrite arm spacing(SDAS) of Mg–6Zn–1Y and Mg–6Zn–3Y is reduced by 32 and 30% with increasing cooling rates(Rc) from 10.2 to 23 K/s, which can be predicted using a empirical model of SDAS=68 R 0:45:45cand SDAS=73 R 0c, respectively. The compressive strength of both alloys increases with increasing the cooling rate, which is attributed to the increase of volume fraction(Vf) of secondary phases under high cooling rate. The interaction of the cooling rate and component with SDAS has been theoretically analyzed using interdependence theory.     

Multicellular Tumor Spheroids (MCTS) as a 3D In Vitro Evaluation Tool of Nanoparticles

Multicellular tumor spheroid models (MCTS) are often coined as 3D in vitro models that can mimic the microenvironment of tissues. MCTS have gained increasing interest in the nano‐biotechnology field as they can provide easily accessible information on the performance of nanoparticles without using animal models. Considering that many countries have put restrictions on animals testing, which will only tighten in the future as seen by the recent developments in the Netherlands, 3D models will become an even more valuable tool. Here, an overview on MCTS is provided, focusing on their use in cancer research as most nanoparticles are tested in MCTS for treatment of primary tumors. Thereafter, various types of nanoparticles—from self‐assembled block copolymers to inorganic nanoparticles, are discussed. A range of physicochemical parameters including the size, shape, surface chemistry, ligands attachment, stability, and stiffness are found to influence nanoparticles in MCTS. Some of these studies are complemented by animal studies confirming that lessons from MCTS can in part predict the behaviour in vivo. In summary, MCTS are suitable models to gain additional information on nanoparticles. While not being able to replace in vivo studies, they can bridge the gap between traditional 2D in vitro studies and in vivo models.