水热碳化法制备碳纳米材料

形态可控的碳纳米材料由于独特的结构和性能而受到研究者的普遍关注,常见的制备方法有化学气相沉积法(CVD)、乳液法和水热碳化法等。水热碳化法是一种重要的碳纳米材料制备方法,具有成本低、反应条件温和、产物粒径均匀且形态可控等特点。综述了近年来以糖类及淀粉等有机物为原料,采用水热碳化法制备各种形态可控碳纳米材料的研究现状,重点介绍了水热碳化工艺条件对合成碳微球、空心碳微球、核壳结构碳复合材料显微形貌的影响,并提出了水热碳化法制备碳纳米材料研究中存在的问题和今后可能的发展方向。     

基于细菌觅食特征改进粒子群算法优化SVM模型参数研究

针对粒子群算法优化SVM模型参数在进化后期容易陷入局部最优的问题,研究了细菌觅食趋利避害机制,提出了一种基于细菌觅食特性改进粒子群算法的方法,并将改进方法应用于优化SVM预测模型参数的研究;实验结果表明,该方法能够弥补粒子群算法在进化后期容易陷入局部最优的缺陷,具备更好的寻优性能。     

碳纳米管作为新型催化材料的发展

纳米材料真正作为研究领域的历史至今还不到一个世纪,在这不到一世纪时间里,纳米材料在人们越来越炽热的关注中飞速发展。作为纳米材料,其粒子由于尺寸的微观性,以及量子力学的出现,便具有了一些特殊的性质,包括量子尺寸效应、小尺寸效应、表面效应以及宏观量子隧道效应。在石油化工领域,催化剂是整个行业的命脉之一,而纳米材料由于其特殊的性质,使其在催化材料方面也开始逐渐崭露头角,并被专业人士视为富有前景的新型催化材料。本文中将以碳纳米管(CNTs)为例着重介绍其作为催化材料的发展进程并进行展望。     

一种基于异常值检测和群体智能优化神经网络的电价混合预测模型

为了提高短期电价预测精度,本文提出了一种将异常值检测、时间序列分析、神经网络以及群体智能算法相结合的混合算法。作为混合算法的具体实现,文中的异常值检测利用了残差比方法和正态分布方法,群体智能优化算法选取了粒子群(PSO)算法和布谷鸟(CS)算法。作为实例研究,本文将混合模型应用用于澳大利亚新南威尔士州短期电价预测中,结果表明,混合预测方法能在一定程度上提高模型的预测精度。     

Constructing porous ZnO/SnO2 nanocomposites for the detection of methane at low operating temperature

Journal of Porous Materials - Aimed at detecting methane (CH4) gas at low operating temperature, porous ZnO/SnO2 nanocomposites were constructed through a simple two-step method. Pure SnO2 with a...     

酶解辅助超声法提取花生红衣原花青素的工艺研究

本试验以花生红衣为原料,纤维素酶辅助超声波提取花生红衣中原花青素,采用单因素和正交试验研究了纤维素酶添加量、料液比、提取温度和提取时间对原花青素得率的影响,并分析其体外抗氧化活性。结果表明:最佳工艺条件为纤维素酶添加量为0.3%,料液比1∶20(m/v),提取时间40 min,提取温度55℃,原花青素得率为10.97%,原花青素提取物对DPPH自由基具有较强的清除作用。     

Investigation into the effects of grain size on strength and failure behaviors of granites using a breakable polygonal grain–based model

Bulletin of Engineering Geology and the Environment - The microstructure of rock is one of the most important factors that affect its mechanical behaviors. In order to study the effects of grain...     

光伏电站交流侧评估测试分析研究

目前,可再生能源受到了各国政府的高度重视,太阳能作为诸多永续利用的清洁能源中的一种,其开发和利用价值已成为各国可持续发展战略中的重要组成部分。选取了上海航天宁东一期100 MWp光伏电站项目具体实例,针对升压站交流侧一定数量并具有代表性的设备进行测试,运用科学的测试方法并对试验数据进行详细的整理分析,结合数学理论算法,最终计算出光伏电站交流侧典型日功率损耗率及电站发电效率,找出影响发电量的因素和解决办法。为光伏电站提供第一手数据资料,并对后期运维提出提供科学、合理、完善的管理及建议。     

Interfacial dilatational rheology and displacement mechanism of nano-flooding system

In the field of crude oil extraction, nano-flooding technology can significantly improve the oil displacement efficiency and provide important technical support for tertiary oil recovery. Although a host of studies have been carried out in this domain, its dilatational rheology and displacement mechanism are rarely reported. In order to address this gap in the extant literature, as a crucial component of this investigation, the interfacial rheology of the nano-flooding system and the simulated crude oil was systematically studied with the aid of the JMP2000A interface expansion rheometer. Meanwhile, a micro-displacement experiment was carried out to elucidate its displacement mechanism. The obtained results show that the nano-flooding system initially increases as its concentration, solution pH, and aging time increase, after which a decline is observed. However, with the change of salinity, it shows a trend of increasing first and then decreasing. Moreover, according to the multi-factor test results yielded by the relevant software, the relative error is less than 5%, which fully meets the needs of the field and provides an important basis for the field construction. The findings further suggest that the modulus between the nano-flooding system and the simulated crude oil can be increased by 84-fold (i.e., from 0.9271 to 78.0739 mN/m). In addition, during the displacement process, the fingering phenomenon of the displacement fluid can be reduced via piston-like displacement. The swept volume also improves the oil washing efficiency of crude oil, demonstrating that the proposed strategy achieves the purpose of enhancing oil recovery.