Computational approaches towards the advancement of high temperature coatings

推动高温涂层进步的计算方法

• 批准号: 508047-2017
• 负责人: DiLabio, Gino
• 金额: $ 0.91万
• 依托单位: University of British Columbia
• 依托单位国家: 加拿大
• 项目类别: Engage Plus Grants Program
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=640453
• 关键词: Computational; approaches; towards; advancement; temperature

The research challenge to be addressed through the project is two-fold and will continue to contribute to thebenchmark feasibility study for a longer term collaborative project. The primary focus will be on thecomputational study mechanisms related to coke accumulation at a surface and its subsequent gasification.The mechanism and kinetics associated with non-oxide based gasification of carbon species is not known andmust be understood in order to develop more effective catalyst coatings. Simulations will be performed in orderto develop an understanding of how the surface of a metal carbide could facilitate this surface chemistry. Suchstudies have never been performed. A secondary outcome of this project will be to provide an atomistic viewof Cr-losses from the steel (forming a Cr-denuded zone). The stretch and future goals will be implementing thestudy on CAMOLTM G1/G2 product line which will provide more direct information to aid in thedevelopment of the new SGX product and optimization of an associated base alloy.The optimization of non-oxide based catalyst system for high carbon gasification is a challenge that must beaddressed in the development of anti-fouling coatings for high severity olefins manufacturing. The use ofcomputational techniques to better understand the available catalytic pathways and optimize the system for thebase catalyst as well as any doping elements can significantly increase the efficiency with which candidatematerials are identified and optimized.

通过该项目解决的研究挑战是双重的，并将继续为长期合作项目的基准可行性研究做出贡献。主要重点将放在与焦炭在表面积聚及其随后的气化相关的计算研究机制上。与碳物种的非氧化物基气化相关的机制和动力学尚不清楚，必须理解以开发更有效的催化剂涂层。将进行模拟，以了解金属碳化物的表面如何促进这种表面化学。这种研究从未进行过。该项目的第二个成果将是从原子角度观察钢中的铬损失（形成铬贫化区）。本项目的延伸和未来目标将是对CAMOLTM G1/G2产品线进行研究，这将为SGX新产品的开发和相关基础合金的优化提供更直接的信息。高碳气化非氧化物基催化剂体系的优化是开发用于高苛刻度烯烃生产的防污涂层必须解决的挑战。使用计算技术来更好地了解可用的催化途径和优化系统的基础催化剂以及任何掺杂元素可以显着提高效率与候选材料的识别和优化.