减水剂类型对赤泥—矿渣基地聚物注浆材料性能的影响及机理研究

针对赤泥等固体废弃物对环境危害性大且利用率低等问题,以碱激发赤泥-矿渣基地聚物注浆材料为 研究对象,研究了不同掺量的聚羧酸(PA)减水剂、醛酮缩合物(AKC)减水剂和萘系(N)减水剂对材料凝结时间、流动 性及强度等的影响,并通过 XRD、傅里叶红外光谱及 SEM 等设备对减水剂的作用机理进行研究。 结果表明:减水剂增 强了材料的流动性但降低了材料的剪切应力;N 和 PA 减水剂能缩短材料的凝结时间,但 AKC 减水剂会延长材料的凝 结时间;N 和 AKC 减水剂能提高材料的强度,但 PA 减水剂会降低材料的强度;N 减水剂对材料的综合性能提升效果 更加明显,其最优掺量为 0. 7%;减水剂对赤泥-矿渣基地聚物性能提升的作用机理主要是促进地聚合物凝胶的形成。 研究成果为拓展赤泥在工程上的使用途径和效率提供了理论指导。     

Effect of nanoparticles orientation on morphology of polymeric nanocomposite foams: preparation of foamed nanocomposite fibers by supercritical carbon dioxide

ABSTRACT

Polymeric foams have received increasing attention in both academic and industrial communities. Using of nanoparticles as heterogeneous nucleation agent has been verified as one of the most valid means to enhance cell nucleation and improve cell morphology. However, few researches have been conducted to investigate the effect of the nanoparticles’ spatial orientation on their nucleation efficiency. In this work, to study the influence of the orientation of nanoparticles on their performance in improving morphology of polymeric foam, thermoplastic polyurethane (TPU) composite fibers with different nanoparticles (carbon nanotubes, graphene and SiO₂) were prepared by using different traction speeds. The different traction speeds lead to different orientation state of the nanoparticles which then resulted different nucleation effect. It was found that carbon nanotubes (CNTs) were easily oriented and aligned along the fiber length direction under the high traction speed, while graphene and SiO₂ nanoparticles did not show orientation under the traction speed in this study. As a result, the foam of TPU/CNTs composite fibers from high traction speed exhibited a much smaller cell size and higher cell density compared to the foams of the fibers from low traction speeds, while TPU/graphene, and TPU/SiO₂ composite fibers with different traction speeds showed almost similar cell size and size density after foaming, indicating that the orientated nanoparticles possessed higher heterogeneous nucleation efficiency. To our best knowledge, this work, for the first time, demonstrated the high nucleation effect of the aligned nanoparticles, which hopefully open a new path for improving the cell morphology of polymeric foam materials.     

基于三维胞元空间的MA双向并行路由算法

针对传统移动代理(MA)在监测无线传感器网络(WSNs)的感兴趣信息时产生的延迟较大和能耗较多问题,提出了基于三维胞元空间的MA双向并行(3D-BPMA)路由算法.3D-BPMA将MA与传统的客户/服务器(c/S)模式相结合,在胞元内利用C/S模式搜集信息,在单层胞元系统和路由器与路由器之间采用MA双向并行的策略进行传输.仿真结果表明:3D-BPMA与LCF,DSG-MIP算法相比减少了平均响应时间和网络平均能耗,提高了MA发送率.     

Photopolymerization synthesis of polyacrylic acid dispersant with methoxysilicon end groups and its application in a nano‐SiO2 aqueous system

In order to improve the dispersity and stability of the nano‐SiO₂ aqueous system with high solid content, a kind of polyacrylic acid dispersant with methoxysilicon end groups (KH590‐PAA) was synthesized by photopolymerization of acrylic acid (AA) initiated with (3‐mercaptopropyl)trimethoxysilane (KH590). After adding KH590‐PAA into the nano‐SiO₂ aqueous dispersion system (20 wt% solid content), the viscosity and the curing time of the system were measured with a rotational viscometer and the inverted bottle method. Moreover, the dispersion mechanism of KH590‐PAA for the nano‐SiO₂ aqueous system was researched by measuring the adsorption capacity, the particle size and the zeta potential of the nanoparticles with a conductivity meter, dynamic light scattering, SEM and TEM, respectively. The results showed that the methoxysilicon groups in KH590‐PAA could react with hydroxyl groups on the surface of nano‐SiO₂ in the process of stirring, which enhanced the adsorption capacity of the dispersant and then increased the surface charge of the particles. Therefore, electrostatic repulsion and steric hindrance effects between the SiO₂ nanoparticles could be further enhanced by adding the KH590‐PAA dispersant, and then the nano‐SiO₂ aqueous system exhibited better dispersity and stability. Besides, the dispersion properties of SiO₂ nanoparticles in water were closely related to the addition amount and the molecular weight of the KH590‐PAA dispersant. © 2018 Society of Chemical Industry     

Preparation of a CeO2–ZrO2 based nano-composite with enhanced thermal stability by a novel chelating precipitation method

In this study, a chelating agent is introduced to prepare CeO₂–ZrO₂ nano-composite through a precipitation process. The physicochemical properties of the oxide precursors, nano composite materials are strongly dependent on the preparation method and whether a chelating agent is used. Adding an appropriate quantity of chelating agent SO₄²⁻ can facilitate thermal stability and phase structure uniformity of CeO₂–ZrO₂ mixed oxides. The calculation results showed that the Gibbs free energy of chelating complex of [ZrSO₄]²⁺ (ΔG = −127.2469 kJ/mol) is higher than the [Ce(III)SO₄]⁺ (ΔG = -29.8279 kJ/mol). The precipitation chemical potential of Zr⁴⁺ moves close to the precipitation chemical potential of Ce³⁺. The novel and low-cost chelating precipitation method can modify the homogeneity of the compounds at the atomic scale, which can offer a powerful opportunity for, and provide direction in, the design of materials with exceptional properties.     

Two-agent two-machine flowshop scheduling with learning effects to minimize the total completion time

We study a two-agent scheduling problem in a two-machine permutation flowshop with learning effects. The objective is to minimize the total completion time of the jobs from one agent, given that the maximum tardiness of the jobs from the other agent cannot exceed a bound. We provide a branch-and-bound algorithm for the problem. In addition, we present several genetic algorithms to obtain near-optimal solutions. Computational results indicate that the algorithms perform well in either solving the problem or efficiently generating near-optimal solutions.     

Study on the relationship between the particle size distribution and the effectiveness of the K‐powder fire extinguishing agent

The relationship between the particle size distribution and the extinguishing effectiveness of the new K‐powder fire extinguishing agent has been studied experimentally, to explore the reason of the great extinguishing efficiency exhibited by the new K‐powder fire extinguishing agent on Class B fire (liquid fuel fire). The results of the experiment showed that the extinguishing effectiveness increased along with the decrease of the particle size distribution. In addition, a sharp discontinuity appeared around the limiting size, about 40 μm. The powder with the particle size below 40 μm exhibited highly effective extinguishing with the minimum effective extinguishing concentration C_xr = 23 g·m^?3, while the powder with the particle size above 40 μm exhibited little fire extinguishing efficiency. Compared with other fire extinguishing agents produced by different substances, the new K‐powder fire extinguishing has the bigger limiting size. That means, in the same particle size distribution, the new K‐powder fire extinguishing agent contains more highly effective powder than others contain, and is more effective.     

Synthesis of Cellulose-Based Macromolecular Coupling Agent and its Utilization in Poly (butylene succinate)/Wood Flour Composites

A long fatty side chain was introduced into the macromolecule of hydroxyethyl cellulose (HEC) via esterification reaction. The hydrophobicity of hydroxyethyl cellulose lauric acid ester (HECLAE) was enhanced in comparison with HEC. The obtained HECLAE was used as macromolecular coupling agent in poly (butylene succinate)/wood flour composites and exhibited a positive influence on improving the mechanical performance of composites. Besides, HECLAE plays a role as a hydrophobic agent in composites. A significant increase in storage modulus (E’) was observed upon the incorporation of treated wood flour. SEM images showed that the dispersion of treated wood flour in PBS matrix was improved.     

基于Q-learning的不确定环境BDI Agent最优策略规划研究

BDI模型能够很好地解决在特定环境下的Agent的推理和决策问题,但在动态和不确定环境下缺少决策和学习的能力。强化学习解决了Agent在未知环境下的决策问题,却缺少BDI模型中的规则描述和逻辑推理。针对BDI在未知和动态环境下的策略规划问题,提出基于强化学习Q-learning算法来实现BDI Agent学习和规划的方法,并针对BDI的实现模型ASL的决策机制做出了改进,最后在ASL的仿真平台Jason上建立了迷宫的仿真,仿真实验表明,在加入Q-learning学习机制后的新的ASL系统中,Agent在不确定环境下依然可以完成任务。