Heterofullerene C48B12-impregnated MOF-5 and IRMOF-10 for hydrogen storage: A combined DFT and GCMC simulations study

The H₂ storage properties of isoreticular metal-organic framework materials (IRMOFs), MOF-5 and IRMOF-10, impregnated with different numbers and types of heterogeneous C₄₈B₁₂ molecules were investigated using density functional theory and grand canonical Monte Carlo (GCMC) calculations. The excess hydrogen adsorption isotherms of IRMOFs at 77 K within 20 bar indicate that suitable number and type of C₄₈B₁₂ molecules play a crucial role in improving the H₂ storage properties of IRMOFs. Among the studied pure and nC₄₈B₁₂ (n = 1, 2, 4, 8) in Ci symmetry impregnating into MOF-5, at 77 K under 6 bar, MOF-5-4C₄₈B₁₂ with a 3.5 wt% and 29.9 g/L hydrogen storage density, and at 77 K under 12 bar, the pure MOF-5 with a 4.9 wt% and 31.0 g/L hydrogen storage density has the best hydrogen storage properties. Whereas, among the studied pure and nC₄₈B₁₂ (n = 1, 2, 4, 8) in S6 symmetry impregnating into IRMOF-10, IRMOF-10-8C₄₈B₁₂ always shows the best hydrogen storage properties among the pure and C₄₈B₁₂-impregnated IRMOF-10 at 77 K within 20 bar. IRMOF-10-8C₄₈B₁₂ has a 6.0 wt% and 34.6 g/L hydrogen storage density at 77 K under 6 bar, and has a 7.1 wt% and 41.4 g/L hydrogen storage density at 77 K under 12 bar. The confinement effect of IRMOFs on C₄₈B₁₂ molecules, and steric hindrance effect of C₄₈B₁₂ molecules on IRMOFs mainly affects the H₂ uptake capacity by comparing the absolute H₂ molecules in individual IRMOFs units, C₄₈B₁₂ molecules, and IRMOFs-nC₄₈B₁₂ compounds. The absolute hydrogen adsorption profiles show that eight C₄₈B₁₂ molecules impregnating into MOF-5 can exert obvious steric effects for H₂ adsorption. The saturated gravimetric and volumetric H₂ densities of IRMOF-10-8C₄₈B₁₂ higher than those of MOF-5-8C₄₈B₁₂ due to with larger free volume.     

5G核心网业务模型的智能化预测研究

摘 要：核心网业务模型的建立是5G网络容量规划和网络建设的基础，通过现有方法得到的理论业务模型是静态不可变的且与实际网络存在偏离。为了克服现有5G核心网业务模型与现网模型适配性较差以及规划设备无法满足用户实际业务需求的问题，提出了一种长短期记忆（long short-term memory，LSTM）网络与卷积LSTM （convolution LSTM，ConvLSTM）网络双通道融合的 5G 核心网业务模型预测方法。该方法基于人工智能（artificial intelligence，AI）技术以实现高质量的核心网业务模型的智能预测，形成数据反馈闭环，实现网络自优化调整，助力网络智能化建设。     

我国水-能源-粮食耦合关系及影响因素

为缓解我国水、能源和粮食资源紧张问题，促进资源可持续利用，构建水-能源-粮食系统，利用耦合协调度模型对我国的30个省（自治区、直辖市）进行测算,并利用空间杜宾模型分析主要影响因素。结果表明：2003—2017年，我国能源、粮食评价[JP]指数高于水资源评价指数，系统综合评价指数逐年递增；大部分省份耦合协调度处于初级协调水平且呈现逐年上升的态势，个别省份耦合协调度濒临失调；耦合协调度空间自相关性较强，虽有明显波动，但是呈现逐年加强的态势；影响耦合协调度的主要因素有从业人口数、固定资产投资额、人均生产总值、人口总数、[JP]文盲人口占比、工业污染排放、城镇化。     

High Q×f values of Zn-Ni co-modified LiMg0.9Zn0.1-xNixPO4 microwave dielectric ceramics for 5G/6G LTCC modules

In this work, Zn-Ni co-modified LiMg_0.9Zn_0.1-xNi_xPO₄ (x = 0–0.1) microwave dielectric ceramics were fabricated using a solid state synthesis route. Rietveld refinement of the XRD data revealed that all ceramic samples have formed a single phase with olivine structure. SEM images showed that the samples have a dense microstructure, that agrees with the measured relative density of 97.73 %. Based on the complex chemical bond theory, Raman and infrared reflectance spectra, we postulate that ε_r is mainly affected by the ionic polarizability, lattice and bond energy, while P-O bond plays a decisive role in Q×f and τ_f value. Optimum properties of Q×f ~ 153,500 GHz, ε_r ~ 7.13 and τ_f ~ ?59 ppm/°C were achieved for the composition LiMg_0.9Zn_0.06Ni_0.04PO₄ sintered at 875 ℃ for 2 h. This set of properties makes these ceramics an excellent candidate for LTCC, wave-guide filters and antennas for 5 G/6 G communication applications.     

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。     

基于5G时长驻留的分析及优化提升方法

随着中国移动5G网络的逐步发展，目前已实现城区的5G网络连片覆盖，全网5G用户大规模增长。本文通过对经分数据用户产生的话单，结合用户使用的网络类型，利用成熟的经分平台，实现直接针对用户使用的网络、流量、时长等方面的分析，直观的体现了用户在5G网络的驻留时长占比以及5G网络的流量占比，为网络优化工作提供了重要分析依据。     

Application of artificial neural network method to predict the breakage properties of PGE bearing chromite ore

In the present investigation, systematic grinding experiments were conducted in a laboratory ball mill to determine the breakage properties of low-grade PGE bearing chromite ore. The population balance modeling technique was used to study the breakage parameters such as primary breakage distribution (B_{i, j}) and the specific rates of breakage (S_i). The breakage and selection function values were determined for six feed sizes. The results stated that the breakage follows the first-order grinding kinetics for all the feed sizes. It was observed that the coarser feed sizes exhibit higher selection function values than the finer feed size. Further, an artificial neural network was used to predict breakage characteristics of low-grade PGE bearing chromite ore. The predicted results obtained from the neural network modeling were close to the experimental results with a correlation of determination R² = 0.99 for both product size and selection function.