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Modeling and Characterization of Rate Phenomena in Complex Electrochemical Systems: Sodium-Metal Chloride Batteries and Ni/SiC Co-Deposition

机译:复杂电化学系统中速率现象的建模和表征:钠金属氯化物电池和Ni / SiC共沉积

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摘要

In the first part of the dissertation (Chapters 3-5), the effect of a cationic dispersant, polyethyleneimine (PEI) on the co-deposition of micro and nano SiC particles with nickel is characterized and modeled. A major challenge in Ni/SiC co-deposition for wear-resistant coatings is that the dispersants that are used to stabilize the particles in the electrolyte to ensure high and uniform particle incorporation into the deposit can significantly affect the electrodeposition kinetics. To overcome this challenge, studies of particle dispersion and electrodeposition are integrated. The effect of PEI on the electrodeposition of Ni/SiC composites is characterized as a function of SiC and PEI bath concentration, current density, rotation speed, molecular weight of PEI and particle size. A pre-coating procedure, in which SiC particles are pre-coated with PEI in a different electrolyte prior to plating, is described. With the pre-coating procedure, high particle stability in the plating bath is obtained. In addition, a significant increase on the SiC incorporation rate is seen without any substantial decrease on the current efficiency for both micro- and nano-composites. Furthermore, using pre-coated particles in the presence of a leveling agent is found to be advantageous relative to the direct addition of PEI into the electrolyte. The efficacy of employing the pre-coating procedure in manufacturing, where plating baths need a long life, is also found to be satisfactory. The use of pre-coated SiC particles changes the morphology, decreases the surface roughness and increases the hardness of the deposits for both particle sizes. Finally, a mathematical model of the co-deposition is proposed. The rate of incorporation is proportional to the residence time, inversely proportional to the burial time, and is proportional to the number density of particles on the surface. These times are influenced by the hydrodynamics, particle size, current density, and concentration of dispersants. SiC incorporation increases with the introduction of PEI due to an increase in the residence time of the particles on the surface. In the second part of the dissertation, a sodium-metal chloride battery, which is another important complex electrochemical system, is studied. A one-dimensional mathematical model of the porous cathode of a sodium-iron chloride battery for an isothermal, constant-current discharge-charge cycle is presented. In sodium-iron chloride batteries, it is desirable to maintain low FeCl2 solubility to minimize redistribution of active material in the cell. However, the iron chloride is sparingly soluble, and with increased cycling, it does redistribute. None of the previous models can predict this movement of the metal that takes place in the cell with increased cycling that can cause the failure of the cell. An advance offered by the model presented is that it accounts for the change in the solubility of FeCl2 within the cell and predicts the relocation of the iron by including the flux of a sparingly soluble ferrous complex. For instance, the model predicts that at the end of the fifth cycle, the iron amount decreases by ~1% near the sodium tetrachloroaluminate reservoir.
机译:在论文的第一部分(第3-5章)中,对阳离子分散剂聚乙烯亚胺(PEI)对微米和纳米SiC颗粒与镍共沉积的影响进行了表征和建模。用于耐磨涂层的Ni / SiC共沉积的主要挑战是,用于稳定电解质中的颗粒以确保高且均匀的颗粒结合到沉积物中的分散剂会显着影响电沉积动力学。为了克服这一挑战,对颗粒分散和电沉积的研究进行了整合。 PEI对Ni / SiC复合材料电沉积的影响是SiC和PEI浴液浓度,电流密度,转速,PEI分子量和粒径的函数。描述了一种预涂覆程序,其中在电镀之前用PEI在不同的电解质中预涂覆SiC颗粒。通过预涂布程序,可以在电镀浴中获得较高的颗粒稳定性。另外,对于微米和纳米复合材料,可以看到SiC掺入率显着增加,而电流效率却没有任何实质性降低。此外,发现在流平剂存在下使用预涂覆的颗粒相对于将PEI直接添加到电解质中是有利的。还发现在电镀浴需要长寿命的制造中采用预涂工艺的效果令人满意。使用预涂层的SiC颗粒会改变形貌,降低表面粗糙度,并增加两种粒径下沉积物的硬度。最后,提出了共沉积的数学模型。掺入速率与停留时间成正比,与掩埋时间成反比,并且与表面上的颗粒数密度成正比。这些时间受流体动力学,粒度,电流密度和分散剂浓度的影响。由于颗粒在表面上停留时间的增加,随着PEI的引入,SiC的结合增加。在论文的第二部分,研究了钠-金属氯化物电池,它是另一个重要的复杂电化学系统。建立了等温恒流充放电循环的氯化钠铁电池多孔阴极的一维数学模型。在氯化钠铁电池中,希望保持低的FeCl 2溶解度以最小化电池中活性物质的重新分布。但是,氯化铁微溶,并且随着循环次数的增加,它会重新分布。以前的模型都无法预测随着循环次数增加而导致电池失效的金属在电池中的运动。提出的模型提供的一项进步是,它说明了FeCl2在细胞内的溶解度变化,并通过包括微溶性亚铁络合物的通量来预测铁的重新定位。例如,该模型预测,在第五个循环结束时,四氯铝酸钠储层附近的铁含量将减少约1%。

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    Eroglu Damla;

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  • 年度 2013
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  • 原文格式 PDF
  • 正文语种 English
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