Achieving Theory-Experiment Parity for Activity and Selectivity in Heterogeneous Catalysis Using Microkinetic Modeling

被引:59
作者
Xie, Wenbo [1 ]
Xu, Jiayan [1 ]
Chen, Jianfu [2 ,3 ]
Wang, Haifeng [2 ,3 ]
Hu, P. [1 ,2 ,3 ]
机构
[1] Queens Univ Belfast, Sch Chem & Chem Engn, Belfast BT9 5AG, Antrim, North Ireland
[2] East China Univ Sci & Technol, Key Lab Adv Mat, Ctr Computat Chem, Shanghai 200237, Peoples R China
[3] East China Univ Sci & Technol, Res Inst Ind Catalysis, Shanghai 200237, Peoples R China
基金
英国工程与自然科学研究理事会;
关键词
GAS SHIFT REACTION; ADSORBATE-ADSORBATE INTERACTIONS; CO ADSORPTION; COVERAGE; HYDROGENATION; ACETYLENE; OXIDATION; SURFACE; 1ST-PRINCIPLES; MECHANISM;
D O I
10.1021/acs.accounts.2c00058
中图分类号
O6 [化学];
学科分类号
0703 ;
摘要
Microkinetic modeling based on density functional theory (DFT) energies plays an essential role in heterogeneous catalysis because it reveals the fundamental chemistry for catalytic reactions and bridges the microscopic understanding from theoretical calculations and experimental observations. Microkinetic modeling requires building a set of ordinary differential equations (ODES) based on the calculation results of thermodynamic properties of adsorbates and kinetic parameters for the reaction elementary steps. Solving a microkinetic model can extract information on catalytic chemistry, including critical reaction intermediates, reaction pathways, the surface species distribution, activity, and selectivity, thus providing vital guidelines for altering catalysts. However, the quantitative reliability of traditional microkinetic models is often insufficient to conclusively extrapolate the mechanistic details of complex reaction systems. This can be attributed to several factors, the most important of which is the limitation of obtaining an accurate estimation of the energy inputs via traditional calculation methods. These limitations include the difficulty of using static DFT methods to calculate reaction energies of adsorption/desorption processes, often rate-controlling or selectivity-determining steps, and the inadequate consideration of surface coverage effects. In addition, the robust microkinetic software is rare, which also complicates the resolution of complex catalytic systems. In this Account, we review our recent works toward refining the predictions of microkinetic modeling in heterogeneous catalysis and achieving theory-experiment parity for activity and selectivity. First, we introduce CATKINAS, a microkinetic software developed in our group, and show how it disentangles the problem that traditional microkinetic software has and how it can now be applied to obtain kinetic results for more sophisticated reaction systems. Second, we describe a molecular dynamics method developed recently to obtain the free-energy changes for the adsorption/desorption process to fill in the missing energy inputs. Third, we show that a rigorous consideration of surface coverage effects is pivotal for building more realistic models and obtaining accurate kinetic results. Following a series of studies on acetylene hydrogenation reactions on Pd catalysts, we demonstrate how this new approach can provide an improved quantitative understanding of the mechanism, active site, and intrinsic structural sensitivity. Finally, we conclude with a brief outlook and the remaining challenges in this field.
引用
收藏
页码:1237 / 1248
页数:12
相关论文
共 67 条
[1]   On the reaction pathway for the hydrogenation of acetylene and vinylidene on Pd(111) [J].
Azad, S ;
Kaltchev, M ;
Stacchiola, D ;
Wu, G ;
Tysoe, WT .
JOURNAL OF PHYSICAL CHEMISTRY B, 2000, 104 (14) :3107-3115
[2]   CO adsorption and CO oxidation on Rh(100) [J].
Baraldi, A ;
Gregoratti, L ;
Comelli, G ;
Dhanak, VR ;
Kiskinova, M ;
Rosei, R .
APPLIED SURFACE SCIENCE, 1996, 99 (01) :1-8
[3]   Combining Computational Modeling with Reaction Kinetics Experiments for Elucidating the In Situ Nature of the Active Site in Catalysis [J].
Bhandari, Saurabh ;
Rangarajan, Srinivas ;
Mavrikakis, Manos .
ACCOUNTS OF CHEMICAL RESEARCH, 2020, 53 (09) :1893-1904
[4]   The Bronsted-Evans-Polanyi relation and the volcano curve in heterogeneous catalysis [J].
Bligaard, T ;
Norskov, JK ;
Dahl, S ;
Matthiesen, J ;
Christensen, CH ;
Sehested, J .
JOURNAL OF CATALYSIS, 2004, 224 (01) :206-217
[5]   Investigating the innate selectivity issues of methane to methanol: consideration of an aqueous environment [J].
Bunting, Rhys J. ;
Rice, Peter S. ;
Thompson, Jillian ;
Hu, P. .
CHEMICAL SCIENCE, 2021, 12 (12) :4443-4449
[6]   The Degree of Rate Control: A Powerful Tool for Catalysis Research [J].
Campbell, Charles T. .
ACS CATALYSIS, 2017, 7 (04) :2770-2779
[7]   A fast species redistribution approach to accelerate the kinetic Monte Carlo simulation for heterogeneous catalysis [J].
Cao, Xiao-Ming ;
Shao, Zheng-Jiang ;
Hu, P. .
PHYSICAL CHEMISTRY CHEMICAL PHYSICS, 2020, 22 (14) :7348-7364
[8]   An understanding of chemoselective hydrogenation on crotonaldehyde over Pt(111) in the free energy landscape: The microkinetics study based on first-principles calculations [J].
Cao, Xiao-Ming ;
Burch, Robbie ;
Hardacre, Chris ;
Hu, P. .
CATALYSIS TODAY, 2011, 165 (01) :71-79
[9]   Gold Segregation Improves Electrocatalytic Activity of Icosahedron Au@Pt Nanocluster: Insights from Machine Learning† [J].
Chen, Dingming ;
Lai, Zhuangzhuang ;
Zhang, Jiawei ;
Chen, Jianfu ;
Hu, Peijun ;
Wang, Haifeng .
CHINESE JOURNAL OF CHEMISTRY, 2021, 39 (11) :3029-3036
[10]   Reversibility Iteration Method for Understanding Reaction Networks and for Solving Microkinetics in Heterogeneous Catalysis [J].
Chen, Jian-Fu ;
Mao, Yu ;
Wang, Hai-Feng ;
Hu, P. .
ACS CATALYSIS, 2016, 6 (10) :7078-7087