Kinetic analysis of magnesium aluminate spinel formation: Effect of MgO:Al2O3 ratio and titania dopant

The mechanistic pathway of MgO-Al₂O₃ reaction in solid state to form MgAl₂O₄ spinel was investigated to correlate the kinetic parameters with ratio of reactants (MgO:Al₂O₃) and with the presence of a doping agent, TiO₂. The time-temperature-expansion data of oxide compacts was analyzed using several model free analyses and model based (linear and non-linear) kinetic algorithms. These indicated that spinel formation process can be best described by single step with n-dimensional Avrami equation for every MgO:Al₂O₃ ratio, irrespective of titania dopant. The activation energy (E_a) of the process was proportional to % spinel formed in each system and validated with quantitative XRD analysis. The higher value of Avrami coefficient (n) in 90 wt% Al₂O₃ compositions has been explained with geometric considerations of powder packing. Incorporations of 1% TiO₂ in the MgO: Al₂O₃ oxide compact did not markedly affect the reaction model, frequency factor and Activation energy.     

能源互联网技术成熟度等级评估

能源互联网是实现未来可持续发展的重要建设内容之一。构建能源互联网需要众多关键技术的支撑,而技术处于不断地进化过程中,了解技术发展的现实水平,把握技术的未来需求,可以指导正确的发展路线和科学的战略决策的制定。本文旨在评估能源互联网关键技术成熟度。基于文献计量方法评估理念建立具有系统性和普适性的综合评估指标体系,并引入数据分析方法和变异系数法构建技术成熟度综合评估方法,为能源互联网的建设提供科学的指导。对能源互联网的云大物移创新应用关键技术进行算例分析,结果表明该方法能准确地判断技术的成熟度,定位技术性能。     

Accuracy of wind energy forecasts in Great Britain and prospects for improvement

The metric representing the wind energy forecast error, when reported as a percent, is calculated quite differently than the error metrics for electricity transmission, electricity load, or in other industries such as manufacturing when they are also reported as a percent. The resulting calculated metric is quite different from what would be reported if the method utilized elsewhere was employed. This paper examines the possible forecast assessment and operational challenges associated with this finding. Concerning the prospects for improvement, the errors reported in MW of energy have a systematic component. With this insight, we developed a model to improve accuracy.     

High-efficiency Silicon Solar Cells: A Review

Over the past few decades, crystalline silicon solar cells have been extensively studied due to their high efficiency, high reliability, and low cost. In addition, these types of cells lead the industry and account for more than half of the market. For the foreseeable future, Si will still be a critical material for photovoltaic devices in the solar cell industry. In this paper, we discuss key issues, cell concepts, and the status of recent high-efficiency crystalline silicon solar cells.     

Hydrogel photocatalysts for efficient energy conversion and environmental treatment

Photocatalysts have attracted great research interest owing to their excellent properties and potential for simultaneously addressing challenges related to energy needs and environmental pollution. Photocatalytic particles need to be in contact with their respective media to exhibit efficient photocatalytic performances. However, it is difficult to separate nanometer-sized photocatalytic materials from reaction media later, which may lead to secondary pollution and a poor recycling performance. Hydrogel photocatalysts with a three-dimensional (3D) network structures are promising support materials for photocatalysts based on features such as high specific surface areas and adsorption capacities and good environmental compatibility. In this review, hydrogel photocatalysts are classified into two different categories depending on their elemental composition and recent progresses in the methods for preparing hydrogel photocatalysts are summarized. Moreover, current applications of hydrogel photocatalysts in energy conversion and environmental remediation are reviewed. Furthermore, a comprehensive outlook and highlight future challenges in the development of hydrogel photocatalysts are presented.     

基于降噪时序深度学习网络的风电功率短期预测方法

利用风电场历史功率数据预测未来一段时间内的风功率,对保障电网安全稳定运行具有重要的意义。本文提出一种基于奇异谱分析SSA(singular spectrum analysis)和长短时记忆LSTM(long-short term memory net⁃work)网络的时序特征预测框架用于短期风功率的预测。首先通过SSA对历史风功率原始数据进行降噪处理,然后经过数据转换之后,以LSTM网络为基础进行预测模型的训练,最后通过某风电场提供的两个风机的历史功率数据进行验证。实验结果表明,奇异谱分析对风电场的历史数据具有良好的降噪性,SSA+LSTM模型在测试数据上取得了较好的预测性能,能够有效进行短期风功率的预测。     

基于量子效应的微型推进器设计

微/纳机电系统(MEMS/NEMS)技术的发展,大大促进了航空航天领域飞行器的微型化。依据量子理论,有效提取真空中的零点能,并以此作为驱动能源,可以解决微型飞行器由于必须携带燃料而增加重量等问题。从理论上阐述了真空零点能及Casimir力的产生机理,研究了真空中两平行平板和矩形腔等结构设计依据,提出并建立了以Casimir力作为驱动力的微型推进器设计模型。     

关于基站空调运行节能的研究

基站空调的电费支出已成为公司的一项庞大开支,为了节约电费支出,在保证基站设备正常工作的前提下进行了空调节能实验.本文论述了实验的目的、依据、原理,并对各试验站的实验结果进行深入分析,总结研讨节能方案.     

谱图合成在铝土矿矿物鉴别中的应用

本文主要论述用X射线能谱仪的谱图合成功能鉴别铝土矿中诸如高岭石、绿泥石、伊利石等组成相似的矿物．进而利用能谱仪的INCA系统强大的比较、匹配功能达到快速、准确地发现铝土矿中其他微量矿物，为制定利用该矿石生产氧化铝工艺流程提供重要依据。