Mixing characteristics for the single and air-water two-phase flows in miniaturized parallel multichannel-based devices

Investigation on the miniaturized parallel multichannel-based devices packed with glass beads to improve the mass exchange execution is the critical focal point of the current study. One of the essential parameters to specify the miniaturized devices' flow distribution is the residence time distribution (RTD). In the present context, the RTDs of a liquid tracer were investigated for the air-water multiphase flows (concurrent) across the multichannel-based miniaturized devices (comprising of 11 similar dimensional parallel channels). The devices were variable in height and packed with glass beads. The conductivity estimations generated the RTD curves and were addressed by the axial dispersion model (ADM). The fluid-flow rates differed within the range of 5–23 ml min⁻¹. The axial dispersion coefficients and the rate of the specific energy dispersion were investigated. The effects of pressure difference and geometry on the hydrodynamic attributes and mixing properties were well-illustrated, and the new correlations were suggested.     

Lanthanide-organic-frameworks modified ZnIn2S4 for boosting hydrogen generation under UV–Vis and visible light

Novel Ln-MOF with microrods shape were successfully combined with ZnIn₂S₄ (ZIS) microsphere and used for photocatalytic hydrogen generation under UV–Vis and visible light. The Ln-MOFs/ZIS system comprises lanthanide-carboxylate coordination networks (Tm and Gd as metal ions, and 1,3,5-benzenetricarboxylic acid (BTC) as the organic linker) deposited on ZnIn₂S₄ microspheres. Effect of the amount of ((Tm,Gd)-BTC) (1, 5, 10 wt%) on the optical properties and photocatalytic hydrogen evolution performance was investigated. ZIS microsphere shows the marigold flower-like morphology and hexagonal polytopic crystal form. Our results proved that the combination of ZIS microsphere, Ln-MOF and Pt nanoparticles (NPs) caused significant enhancement in hydrogen generation. Amount of formed hydrogen was raised from 196.3 to 7782.1 μmol g^?1 for pristine ZIS and ZIS decorated with 1% (Tm, Gd)-BTC/Pt under UV–Vis light, respectively.     

基于VMD和BSA-KELM的高陡边坡位移预测模型研究

边坡位移的时间序列曲线存在复杂的非线性特性,传统的预测模型精度不足以满足预测要求。为此提出了基于变分模态分解的鸟群优化-核极限学习机的预测模型,并用于河北省某水泥厂的边坡位移预测。该方法首先采用VMD把边坡位移序列分解为一系列的有限带宽的子序列,再对各子序列分别采用相空间重构并用核极限学习机预测,采用鸟群算法优化相空间重构的嵌入维度和KELM中惩罚系数和核参数三个数值,以取得最优预测模型。最后将各个子序列预测值叠加,得到边坡位移的最终预测值。结果表明：和KELM、BSA-KELM、EEMD-BSA-KELM模型相比,基于VMD的BSA-KELM预测精度更高,为边坡位移的预测提供一种有效的方法。     

电信运营商云网规划数字化研究和实现

基于电信运营商数字化转型，系统性地提出了数据驱动的云网发展规划体系，以及六大关键数字化能力构建，设计和实现了一种云网规划数字化平台，该平台可用于实现目标网络精细规划、边缘计算精准预测等场景，并探讨了数字孪生在规划领域的应用前景，对运营商推进云网融合战略、推进高质量发展具有指导和参考意义。     

使能未来工厂的5G能力综述

5G系统将移动通信服务从移动电话、移动宽带和大规模机器通信扩展到新的应用领域，即所谓对通信服务有特殊要求的垂直领域。对使能未来工厂的5G能力进行了全面的分析总结，包括弹性网络架构、灵活频谱、超可靠低时延通信、时间敏感网络、安全和定位，而弹性网络架构又包括对网络切片、非公共网络、5G局域网和边缘计算的支持。希望从广度到深度，对相关的理论及技术应用做透彻、全面的梳理，对其挑战做清晰的总结，从而为相关研究和工程技术人员提供借鉴。     

Designing optical glasses by machine learning coupled with a genetic algorithm

Engineering new glass compositions have experienced a sturdy tendency to move forward from (educated) trial-and-error to data- and simulation-driven strategies. In this work, we developed a computer program that combines data-driven predictive models (in this case, neural networks) with a genetic algorithm to design glass compositions with desired combinations of properties. First, we induced predictive models for the glass transition temperature (T_g) using a dataset of 45,302 compositions with 39 different chemical elements, and for the refractive index (n_d) using a dataset of 41,225 compositions with 38 different chemical elements. Then, we searched for relevant glass compositions using a genetic algorithm informed by a design trend of glasses having high n_d (1.7 or more) and low T_g (500 °C or less). Two candidate compositions suggested by the combined algorithms were selected and produced in the laboratory. These compositions are significantly different from those in the datasets used to induce the predictive models, showing that the used method is indeed capable of exploration. Both glasses met the constraints of the work, which supports the proposed framework. Therefore, this new tool can be immediately used for accelerating the design of new glasses. These results are a stepping stone in the pathway of machine learning-guided design of novel glasses.     

Nanoraspberry-like palladium/spongy nickel oxide for electrooxidation of five light fuels

The spongy nickel oxide (SNO) was synthesized the solution combustion method. The SNO was selected as a promoter to boost the catalytic activity of nanoraspberry-like palladium (NRPd) toward electrooxidation of five light fuels (LFs): methanol, ethanol, formaldehyde, formic acid, and ethylene glycol. The X-ray powder diffraction, Fourier-transform infrared spectroscopy (FT-IR), scanning electron microscopy, and field emission scanning electron microscope techniques were used for the materials characterization. In comparison with nonpromoted Pd, the NRPd-SNO electrocatalyst shown an excellent efficiency in parameters like the electrochemical active surface area and anti-CO poisoning behavior. The turnover data and the parameters, including reaction order, activation energy, and the coefficients of electron transfer and diffusion, were evaluated for the each process of LFs electrooxidation. The outcome for NRPd-SNO activity toward LFs electrooxidation was compared to some reported electrodes. The SNO increases the removal of intermediates created in the oxidation of LFs that can poison the surface of palladium catalyst. This is due to the presence of the lattice oxygens in SNO structure and Ni switching between its high and low valances. The compatibility of the adsorption process of LFs on the surface of the NRPd-SNO catalyst with different isotherms was determined by studying the Tafel polarization and calculating the surface coverage.     

Fabrication of barium titanate ceramics via digital light processing 3D printing by using high refractive index monomer

A digital light processing (DLP) technology has been developed for 3D printing lead-free barium titanate (BTO) piezoelectric ceramics. By comparing the curing and rheological properties of slurries with different photosensitive monomer, a high refractive index monomer acryloyl morpholine (ACMO) was chosen, and a design and preparation method of BTO slurry with high solid content, low viscosity and high curing ability was proposed. By further selecting the printing parameters, the single-layer exposure time was reduced and the forming efficiency has been greatly improved. Sintered specimens were obtained after a nitrogen-air double-step debinding and furnace sintering process, and the BTO ceramics fabricated with 80 wt% slurry shows the highest relative density (95.32 %) and piezoelectric constant (168.1 pC/N). Furthermore, complex-structured BTO ceramics were prepared, impregnated by epoxy resin and finally assembly made into hydrophones, which has significance for the future design and manufacture of piezoelectric ceramic-based composites that used in functional devices.     

A novel strategy based on salp swarm algorithm for extracting the maximum power of proton exchange membrane fuel cell

Cell temperature and water content of the membrane have a significant effect on the performance of fuel cells. The current-power curve of the fuel cell has a maximum power point (MPP) that is needed to be tracked. This study presents a novel strategy based on a salp swarm algorithm (SSA) for extracting the maximum power of proton-exchange membrane fuel cell (PEMFC). At first, a new formula is derived to estimate the optimal voltage of PEMFC corresponding to MPP. Then the error between the estimated voltage at MPP and the actual terminal voltage of the fuel cell is fed to a proportional-integral-derivative controller (PID). The output of the PID controller tunes the duty cycle of a boost converter to maximize the harvested power from the PEMFC. SSA determines the optimal gains of PID. Sensitivity analysis is performed with the operating fuel cell at different cell temperature and water content of the membrane. The obtained results through the proposed strategy are compared with other programmed approaches of incremental resistance method, Fuzzy-Logic, grey antlion optimizer, wolf optimizer, and mine-blast algorithm. The obtained results demonstrated high reliability and efficiency of the proposed strategy in extracting the maximum power of the PEMFC.     

Effect of microwave heating time on the gel properties of chicken myofibrillar proteins and their formation mechanism

The present work was conducted to illustrate the mechanism of gel formation of myofibrillar proteins (MPs) under different microwave heating times. The results showed that the denaturation enthalpy (ΔH) of the MPs significantly decreased when the heating time increased from 3 to 9 s and then completely disappeared as the heating time progressed, indicating that the MPs gradually denatured and subsequently aggregated with increasing heating time, which was further verified by the changes in the secondary structure, electrophoretic bands, and gel properties (e.g., water holding capacity and textural profiles) of the MPs. Microstructural images indicated that the MP gel formed under 12 s had the most compact network, indicating that extended microwave heating time could induce quality deterioration of MP gels. Moreover, the hydrophobic forces, electrostatic forces, and disulphide bonds of the MPs gradually intensified with increasing microwave heating time, suggesting that both non-covalent and covalent bonds could promote molecular denaturation and subsequent aggregation of MPs. In addition, correlation analysis revealed that the changes in the molecular conformation of MPs induced by different microwave heating times could effectively regulate the formation of MP gels and their related properties.