Optimization and evaluation of reduced graphene oxide hydrogel composite as a demulsifier for heavy crude oil-in-water emulsion

The rising production of produced water from oilfields had been proven to bring detrimental environmental effects. In this study, an efficient, recyclable, and environmental-friendly reduced graphene oxide immobilized κ-Carrageenan hydrogel composite(κCa GO) was fabricated as an alternative sorbent for crude oil-in-water demulsification. Polyethyleneimine(PEI) was employed to form a stable hydrogel composite. The conditions for the immobilization of graphene oxide(GO) on PEI-modified κ-Carrageenan(κC) beads were optimized appropriately. An immobilization yield of 77% was attained at 2% PEI, 2 h immobilization activation time, and p H6.5. Moreover, the synthesized κCa GO is capable of demulsification with an average demulsification efficiency of 70%. It was found that the demulsification efficiency increases with salinity and κCa GO dosage, and it deteriorates under alkaline condition. These phenomena can be attributed to the interfacial interactions between κCa GO and the emulsion. Furthermore, the κCa GO can be recycled to use for up to six cycles without significant leaching and degradation. As such, the synthesized κCa GO could be further developed as a potential sorbent substitute for the separation of crude oil from produced water.     

热处理工艺对新型轻质奥氏体耐磨钢的组织与力学性能的影响

以新型轻质高锰、高铝的奥氏体耐磨钢为研究对象,利用XRD,OM,SEM,EDS观察显微组织和析出物,研究不同的热处理工艺对新型钢种的组织与力学性能影响。结果表明:该新型轻质奥氏体耐磨钢的最佳优化热处理工艺为1050℃保温1h水韧,550℃时效2h,空冷。在最佳热处理工艺条件下奥氏体基体内弥散析出细小的钙钛矿结构(Fe,Mn)3AlC的κ-碳化物颗粒,不仅强化了奥氏体基体,其力学性能也得到明显改善;最优工艺处理后实验钢的硬度、强度、冲击韧度达到了最佳匹配,其抗拉强度为825MPa,屈服强度为574MPa,冲击韧度值为156J/cm2(V型缺口),硬度为271HB;与只进行水韧处理相比实验钢的屈服强度提高40.0%,硬度提高32.2%。     

纳米卡拉胶微球的制备

利用 Span 80作表面活性剂 ,正丁醇作助表面活性剂制得反相微乳液。将天然海洋高分子κ-卡拉胶进行酸水解使其分子量降低 ,通过反相乳液法对水解后的κ-卡拉胶进行分散并用甲醛和戊二醛进行交联 ,制备卡拉胶微球 ,利用 TEM、IR研究了卡拉胶微球的粒度和分子结构变化。 TEM显示 :低分子量的卡拉胶能够得到纳米级的卡拉胶微球 ,粒径约为 40 nm,添加正丁醇有助于卡拉胶的分散。 IR光谱证明了甲醛和戊二醛在卡拉胶微球内部发生了羟醛缩合反应 ,产生了交联     

利用κ-Köhler理论研究大气气溶胶的吸湿特性

利用κ-K?hler理论对西安、北京两地大气气溶胶体系的吸湿特性进行研究。选取多种代表性无机物（硫酸盐、硝酸盐、氯盐）及有机物（烯烃、芳香烃、羧酸）建立气溶胶体系模型，使研究体系更接近于真实大气成分。结果表明，在空气质量由清洁状态向雾霾发生状态转变的过程中，两种体系中均呈现有机物含量逐渐减少而(NH₄)₂SO₄和NH₄NO₃含量逐渐增多的趋势，这种变化趋势总是促使气溶胶体系整体吸湿能力增强，因此更易吸湿增长形成雾霾。对体系中不同组分对吸湿性的影响进行了定量预测，理论预测的变动趋势与实际观测的变动趋势相同，揭示了雾霾形成过程中各组分的变动趋势及影响程度，为针对性解决雾霾问题提供思路。     

Cooperative learning neural network output feedback control of uncertain nonlinear multi-agent systems under directed topologies

Without assuming that the communication topologies among the neural network (NN) weights are to be undirected and the states of each agent are measurable, the cooperative learning NN output feedback control is addressed for uncertain nonlinear multi-agent systems with identical structures in strict-feedback form. By establishing directed communication topologies among NN weights to share their learned knowledge, NNs with cooperative learning laws are employed to identify the uncertainties. By designing NN-based κ-filter observers to estimate the unmeasurable states, a new cooperative learning output feedback control scheme is proposed to guarantee that the system outputs can track nonidentical reference signals with bounded tracking errors. A simulation example is given to demonstrate the effectiveness of the theoretical results.