Scaling-relation based kinetic Monte Carlo modeling of higher alcohol synthesis

基于标度关系的高级醇合成动力学蒙特卡罗模型

• 批准号: 259352216
• 负责人: Professor Dr. Karsten Reuter
• 金额: --
• 依托单位: Department of Physics
• 依托单位国家: 德国
• 项目类别: Research Grants
• 财政年份: 2014
• 资助国家: 德国
• 起止时间: 2013-12-31 至 2014-12-31
• 项目状态: 已结题
• 来源: https://gepris.dfg.de/gepris/projekt/259352216?language=en
• 关键词: Scaling; relation; based; kinetic; Monte

Over the past years first-principles based microkinetic modeling has evolved into an invaluable contributor to mechanistic understanding of heterogeneously catalyzed processes and the identification of new, improved catalysts. This development proceeded largely along two complementary strands. Kinetic Monte Carlo (kMC) simulations based on explicit first-principles data aimed at a comprehensive and most accurate description of individual systems. Computational screening studies resorted instead to simplified mean-field kinetics and approximate trend energetics derived from scaling, Brønsted-Evans-Polanyi and other relations. In the application to complex reaction networks both strands are challenged. Comprehensive kMC simulations require energetic data for an exceeding number of in principle possible elementary steps. Simplified mean-field kinetic expressions might rely on erroneous assumptions regarding the dominant reaction mechanism or rate-determining steps, as well as reveal intrinsic shortcomings when dealing with microscopic heterogeneity of the active surface and a possibly sensitive interplay between reaction steps taking place at different active sites. The objective of the work is to overcome these limitations by combining the hitherto largely coexisting strands - and generally explore the use of scaling-relation based energetics in kMC simulations. As a showcase system the investigations will focus on the selective synthesis of higher alcohols from synthesis gas, as an attractive energy solution process that would yield these sustainable fuel substitutes in larger quantities and thereby reduce oil dependency and greenhouse gas emissions. Mechanistically, the studies will establish the important factors that determine rhodiums hitherto unique selectivity and target the alleged role of oxide promotion in terms of blocking and alteration of step sites. The generated insight will directly be exploited in refined screening protocols to identify alternative metal compounds, promotion or doping strategies to replace the prohibitively expensive rhodium.

在过去的几年中，基于第一性原理的微观动力学模型已经发展成为一个宝贵的贡献者，多相催化过程的机理理解和识别新的，改进的催化剂。这种发展主要是沿着沿着两条互补的路线进行的。动力学蒙特卡罗（kMC）模拟基于明确的第一性原理数据，旨在全面和最准确地描述单个系统。计算筛选研究转而采用简化的平均场动力学和近似的趋势能量学，它们来自标度、布朗斯特-埃文斯-波兰尼和其他关系。在复杂反应网络的应用中，两条链都受到了挑战。综合kMC模拟需要精力充沛的数据超过原则上可能的基本步骤的数量。简化的平均场动力学表达式可能依赖于错误的假设，占主导地位的反应机制或速率决定步骤，以及揭示内在的缺点时，处理微观异质性的活性表面和可能敏感的反应步骤之间的相互作用发生在不同的活性位点。这项工作的目的是克服这些限制，结合迄今为止在很大程度上共存的股-一般探索使用的缩放关系为基础的能量在kMC模拟。作为一个展示系统，调查将集中在从合成气中选择性合成高级醇，作为一个有吸引力的能源解决方案过程，将产生这些可持续的燃料替代品，在更大的数量，从而减少对石油的依赖和温室气体排放。从机制上讲，这些研究将确定决定铑迄今为止独特的选择性的重要因素，并针对氧化物促进在阻断和改变步骤位点方面的所谓作用。所产生的洞察力将直接用于精细的筛选方案，以确定替代金属化合物，促进或掺杂策略，以取代昂贵的铑。