Melting process and melt structure of fly ash/magnesium slag blends for the production of inorganic fibers

Fiber production from inorganic industrial solid wastes is an effective waste management strategy. Because of cost considerations, most enterprises generally use local solid wastes as raw materials to produce fibers. In this study, we explored the feasibility of producing fibers using fly ash and magnesium slag. The results show that the melting temperature of the blends composed of fly ash, magnesium slag, and a small amount of calcined dolomite first decreased and then increased with an increase in acidity coefficient (M_k) from 1.0 to 2.4_. The samples could form a eutectic system in the M_k range of 1.4–1.8, and therefore have a relatively low melting temperature in this M_k range. Fly ash could react with magnesium slag and calcined dolomite to form akermanite, gehlenite-magnesium, and anorthite at temperatures close to the melting temperature; therefore, these crystalline phases were the main reaction products formed in the samples with M_k values lower than 1.80. Anorthite reacted further with some Na-containing and Si-containing spieces to produce labradorite. Thus, the content of anorthite and labradorite rapidly increased and they became the major crystal phases in the blend samples with M_k values greater than 1.80. MAS-NMR spectroscopic analysis revealed that the network structure of the melts depended on the ratio of bridging oxygen to non-bridging oxygen; a high ratio of bridging oxygen to non-bridging oxygen could lead to the formation of a dense network structure in the melt. The blends of fly ash and magnesium slag can be used to produce wool fibers and continuous fibers. In addition, the suitable temperature ranges for the production of both types of fibers were determined. The drawing temperature for continuous fiber production depended on the degree of polymerization and structure of the melt.     

Effects of Cu on the corrosion behavior and microstructure of Mg–Zn–Ca bulk metallic glass

For the purpose of developing biodegradable magnesium alloys with suitable properties for biomedical applications, Mg–Zn–Ca–Cu metallic glasses were prepared by copper mold injection methods. In the present work, the effect of Cu doping on mechanical properties, corrosion behavior, and glass-forming ability of Mg₆₆Zn₃₀Ca₄ alloy was studied. The experimental findings demonstrated that the incorporation of Cu decreases the corrosion resistance of alloys, but increases the microhardness and degradation rate slightly. However, the addition of a trace amount of Cu can make the samples have antibacterial properties. Therefore, Mg–Zn–Ca–Cu has great advantages in clinical implantation and is the potential implant material.     

CuO-SiO2气凝胶@TiO2纳米纤维无牺牲剂光催化还原CO2

采用溶胶-凝胶法制备CuO-SiO2复合气凝胶,通过在气凝胶孔道内填充TiCl4,然后将其气相水解,得到了在CuO-SiO2气凝胶表面生长了高结晶度的TiO2纳米纤维(CuO-SiO2@TiO2),纤维直径～16 nm.通过XPS、UPS、UV-Vis DRS、荧光光谱(PL)等表征了材料的结构及光电性能.结果表明,制备的CuO-SiO2@TiO2对可见光有明显吸收,且荧光强度较商用TiO2(P25)大幅降低,光生电子-空穴对更加稳定.再在纳米纤维上负载CuO,所得CuO-SiO2@TiO2/CuO在可见光区的荧光强度进一步增强.以300 W氙灯为光源,分别以CuO-SiO2@TiO2及CuO-SiO2@TiO2/CuO为催化剂,无牺牲剂条件下光催化还原CO2,4 h后甲醇产率分别为1304.0及1589.0μmol/g-cat,转换频率(TOF)分别为0.038及0.046 h–1.循环实验表明,纳米纤维具有较好的光催化稳定性,经过4次光催化循环实验后,CuO-SiO2@TiO2/CuO的保留率～94％,甲醇产率可达1472.0μmol/g-cat,TOF为0.042 h–1.     

Reconstructed Water Oxidation Electrocatalysts: The Impact of Surface Dynamics on Intrinsic Activities

Electroreduction of small molecules such as H₂O, CO₂, and N₂ for producing clean fuels or valuable chemicals provides a sustainable approach to meet the increasing global energy demands and to alleviate the concern on climate change resulting from fossil fuel consumption. On the path to implement this purpose, however, several scientific hurdles remain, one of which is the low energy efficiency due to the sluggish kinetics of the paired oxygen evolution reaction (OER). In response, it is highly desirable to synthesize high-performance and cost-effective OER electrocatalysts. Recent advances have witnessed surface reconstruction engineering as a salient tool to significantly improve the catalytic performance of OER electrocatalysts. In this review, recent progress on the reconstructed OER electrocatalysts and future opportunities are discussed. A brief introduction of the fundamentals of OER and the experimental approaches for generating and characterizing the reconstructed active sites in OER nanocatalysts are given first, followed by an expanded discussion of recent advances on the reconstructed OER electrocatalysts with improved activities, with a particular emphasis on understanding the correlation between surface dynamics and activities. Finally, a prospect for clean future energy communities harnessing surface reconstruction-promoted electrochemical water oxidation will be provided.     

Additive Manufacturing of Stable Energy Storage Devices Using a Multinozzle Printing System

The development of the Internet of things has prompted an exponential increase in the demand for flexible, wearable devices, thereby posing new challenges to their integration and conformalization. Additive manufacturing facilitates the fabrication of complex parts via a single integrated process. Herein, the development of a multinozzle, multimaterial printing device is reported. This device accommodates the various characteristics of printing materials, ensures high-capacity printing, and can accommodate a wide range of material viscosities from 0 to 1000 Cp. Complete capacitors, inclusive of the current collector, electrode, and electrolyte, can be printed without repeated clamping to complete the preheating, printing, and sintering processes. This method addresses the poor stability issue associated with printed electrode materials. Furthermore, after the intercalation of LiFePO₄ with Na ions, X-ray photoelectron spectroscopy and X-ray diffraction results reveal that the Na ions permeate the interlayer structure of LiFePO₄, enhancing the ion migration channels by increasing the ion transmission rate. A current rate of 2.5 mAh ensures >2000 charge/discharge cycles, while retaining a charge/discharge efficiency of 96% and a discharge capacity of 91.3 mAh g⁻¹. This manufacturing process can provide conformal power modules for a diverse range of portable devices with various shapes, improving space utilization.     

Self-Adaptive Control System for Additive Manufacturing Using Double Electrode Micro Plasma Arc Welding

Wire arc additive manufacturing(WAAM)has been investigated to deposit large-scale metal parts due to its high deposition efficiency and low material cost.However,in the process of automatically manufacturing the high-quality metal parts by WAAM,several problems about the heat build-up,the deposit-path optimization,and the stability of the process parameters need to be well addressed.To overcome these issues,a new WAAM method based on the double electrode micro plasma arc welding(DE-MPAW)was designed.The circuit principles of different metal-transfer models in the DE-MPAW deposition process were analyzed theoretically.The effects between the parameters,wire feed rate and torch stand-off distance,in the process of WAAM were investigated experimentally.In addition,a real-time DE-MPAW control system was developed to optimize and stabilize the deposition process by self-adaptively changing the wire feed rate and torch stand-off distance.Finally,a series of tests were performed to evaluate the con-trol system's performance.The results show that the capability against interferences in the process of WAAM has been enhanced by this self-adaptive adjustment system.Further,the deposition paths about the metal part's layer heights in WAAM are simplified.Finally,the appearance of the WAAM-deposited metal layers is also improved with the use of the control system.     

基于堆叠稀疏去噪自动编码网络与多隐层反向传播神经网络的铣刀磨损预测模型

刀具磨损状态是机械加工过程中需考虑的重要因素之一.针对铣刀磨损的在线预测问题,建立了一种基于深度学习的铣刀磨损预测模型.首先,将采集到的铣刀切削时的振动信号进行小波去噪后,利用快速傅里叶变换和小波包分解等技术提取时域、频域及时频域上的特征参数,并根据相关性分析从中筛选出合格的特征参数合并为特征向量,以此作为堆叠稀疏去噪自动编码网络(SSDAE)的含噪样本.其次,利用特征后处理的方式对已经筛选出的特征参数进行单调不递减及平滑处理,并将其作为SSDAE的无噪样本来训练该网络.然后,将经过SSDAE降维后的特征向量作为多隐层反向传播神经网络(BPNN)的输入,以这些特征对应的实际铣刀的磨损量作为标签对该网络进行拟合训练.最后,对训练好的模型进行实验验证,通过测试数据集和人为加入噪声的测试数据集的对比,结果显示所提模型不仅具有较高的预测精度,还具有较高的鲁棒性.     

Soluble polyimide as liquid crystal perpendicular alignment layer

Journal of Materials Science - Three polyimides (PIs) were prepared from a diamine containing biphenyl ester group as a side chain and a corresponding dianhydride chosen from...     

内含实体对H型垂直轴风力机气动性能的影响

以H型垂直轴风力机及其内含圆柱形实体为研究对象,对NACA0018翼型的五叶片H型垂直轴风力机的气动性能进行数值模拟和实验验证。分析8种不同直径的内含圆柱体,在内含实体截面积占风轮迎风面积之比分别为21.2%、50.0%和76.9%时,风力机风能利用率的峰值分别下降8.04%、20.7%及74.3%。结果表明：随着内含实体直径的增大,风能利用率的峰值逐渐减小,开始较为缓慢,达到一定值时快速下降。小直径内含实体主要影响叶片在下风区的转矩,对风能利用率的影响较小,而大直径内含实体还会影响叶片在上风区的转矩,其风能利用率迅速减小。对于内含固定直径的实体,比如在现有建筑物外侧安装风力机时,其风轮半径的选择需综合考虑风能利用率和风力机的建造成本两方面的因素。研究结果可为建筑物与垂直轴风力机进行有效结合以提高风能的利用提供参考。