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，基于第一原理的微动力模型已演变为对异质催化过程的机械理解和新的，改进的催化剂的鉴定的宝贵贡献。这一发展主要沿着两条完整的链进行。动力学蒙特卡洛（KMC）模拟基于明确的第一原理数据，旨在对单个系统进行全面，最准确的描述。相反，计算筛选研究求助于简化的平均场动力学，并近似从缩放，布朗斯特德·埃文斯 - 帕利尼和其他关系中得出的趋势能量。在对复杂反应网络的应用中，这两个链都挑战了。全面的KMC模拟需要超过基本步骤数量超过数量的能量数据。简化的平均场动力学表达可能会依赖于有关主要反应机制或速率决定步骤的错误假设，并在处理活动表面的显微镜异质性时揭示了内在的缺点，以及在不同活性位点发生的反应步骤之间可能的敏感相互作用。这项工作的目的是通过组合迄今主要共存的链来克服这些局限性，并通常探索基于缩放关系的能量在KMC模拟中的使用。作为展示系统，调查将集中于合成气体中较高醇的选择性合成，这是一种有吸引力的能源解决方案工艺，它将以较大量产生这些可持续的燃料替代品，从而减少油依赖性和温室气体的排放。从机械上讲，研究将建立确定迄今为止独特选择性的若达克的重要因素，并针对所谓的氧化物促进在阻塞和改变步骤位点方面的作用。生成的见解将直接在精致的筛选方案中进行探索，以识别替代昂贵的若um恒的替代金属化合物，促销或掺杂策略。