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.     

Bee Bread Ameliorates Vascular Inflammation and Impaired Vasorelaxation in Obesity-Induced Vascular Damage Rat Model: The Role of eNOS/NO/cGMP-Signaling Pathway

Obesity and hyperlipidemia are major risk factors for developing vascular diseases. Bee bread (BB) has been reported to exhibit some biological actions, including anti-obesity and anti-hyperlipidemic. This study aims to investigate whether bee bread can ameliorate vascular inflammation and impaired vasorelaxation activity through eNOS/NO/cGMP pathway in obese rats. Forty male Sprague-Dawley rats were randomly divided into four groups (n = 10/group), namely: control (normal group), obese rats (OB group), obese rats treated with bee bread (0.5 g/kg/day, OB/BB group) and obese rats treated with orlistat (10 mg/kg/day, OB/OR group). The latter three groups were given a high-fat diet (HFD) for 6 weeks to induced obesity before being administered with their respective treatments for another 6 weeks. After 12 weeks of the total experimental period, rats in the OB group demonstrated significantly higher Lee obesity index, lipid profile (total cholesterol, triglyceride, low-density lipoprotein), aortic proinflammatory markers (tumor necrosis factor-α, nuclear factor-κβ), aortic structural damage and impairment in vasorelaxation response to acetylcholine (ACh). Bee bread significantly ameliorated the obesity-induced vascular damage manifested by improvements in the lipid profile, aortic inflammatory markers, and the impaired vasorelaxation activity by significantly enhancing nitric oxide release, promoting endothelial nitric oxide synthase (eNOS) and cyclic guanosine monophosphate (cGMP) immunoexpression. These findings suggest that the administration of bee bread ameliorates the impaired vasorelaxation response to ACh by improving eNOS/NO/cGMP-signaling pathway in obese rats, suggesting its vascular therapeutic role.     

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.     

Direct View on the Origin of High Li+ Transfer Impedance in All-Solid-State Battery

Large interfacial resistance plays a dominant role in the performance of all-solid-state lithium-ion batteries. However, the mechanism of interfacial resistance has been under debate. Here, the Li⁺ transport at the interfacial region is investigated to reveal the origin of the high Li⁺ transfer impedance in a LiCoO₂(LCO)/LiPON/Pt all-solid-state battery. Both an unexpected nanocrystalline layer and a structurally disordered transition layer are discovered to be inherent to the LCO/LiPON interface. Under electrochemical conditions, the nanocrystalline layer with insufficient electrochemical stability leads to the introduction of voids during electrochemical cycles, which is the origin of the high Li⁺ transfer impedance at solid electrolyte-electrode interfaces. In addition, at relatively low temperatures, the oxygen vacancies migration in the transition layer results in the formation of Co₃O₄ nanocrystalline layer with nanovoids, which contributes to the high Li⁺ transfer impedance. This work sheds light on the mechanism for the high interfacial resistance and promotes overcoming the interfacial issues in all-solid-state batteries.     

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.     

Designing Semipermeable Hydrogel Shells with Controlled Thickness through Internal Osmosis in Triple-Emulsion Droplets

Hydrogel shells that compartmentalize the water core from the aqueous surrounding provide molecular selectivity on size and charge in transmembrane transport. It is highly demanding to produce thin hydrogel shells to minimize diffusion length and maximize core volume. Here, internal osmosis in water-in-oil-in-water-in-oil (W/O/W/O) triple-emulsion droplets is used to produce thin hydrogel shells enclosing a large water core. The triple-emulsion droplets are prepared to have an ultrathin middle oil layer using a capillary microfluidic device. The innermost water droplet has a higher osmolarity than the outer water layer containing photopolymerizable hydrogel precursors, which pumps water from the outer layer to the core through the ultrathin oil layer by the osmosis. Therefore, the outer layer gets thinner and hydrogel precursors are enriched while the size of the triple-emulsion droplets remains unchanged. Through photopolymerization of precursors and phase transfer from oil to water, hydrogel shells enclosing water core are produced in the water environment; the oil layer is ruptured for molecular exchange through the shells. The thickness and composition of the hydrogel shells are precisely controllable by the osmotic conditions. The shells show a high permeation rate due to the thinness as well as controlled cut-off threshold of permeation for neutral and charged molecules.     

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.     

Fire safe,sustainable loose furnishing

The aim of this exploratory study has been to investigate the fire properties and environmental aspects of different upholstery material combinations, mainly for domestic applications. An analysis of the sustainability and circularity of selected textiles, along with lifecycle assessment, is used to qualitatively evaluate materials from an environmental perspective. The cone calorimeter was the primary tool used to screen 20 different material combinations from a fire performance perspective. It was found that textile covers of conventional fibres such as wool, cotton and polyester, can be improved by blending them with fire resistant speciality fibres. A new three‐dimensional web structure has been examined as an alternative padding material, showing preliminary promising fire properties with regard to ignition time, heat release rates and smoke production.     

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.