Building a kinetic Monte Carlo model with a chosen accuracy

被引:14
作者
Bhute, Vijesh J. [1 ]
Chatterjee, Abhijit [1 ,2 ]
机构
[1] Indian Inst Technol, Dept Chem Engn, Kanpur 208016, Uttar Pradesh, India
[2] Indian Inst Technol, Dept Chem Engn, Bombay 400076, Maharashtra, India
关键词
CLUSTER-EXPANSION MODEL; MOLECULAR-DYNAMICS; ENERGY LANDSCAPES; SIMULATION;
D O I
10.1063/1.4812319
中图分类号
O64 [物理化学(理论化学)、化学物理学];
学科分类号
070304 ; 081704 ;
摘要
The kinetic Monte Carlo (KMC) method is a popular modeling approach for reaching large materials length and time scales. The KMC dynamics is erroneous when atomic processes that are relevant to the dynamics are missing from the KMC model. Recently, we had developed for the first time an error measure for KMC in Bhute and Chatterjee [J. Chem. Phys. 138, 084103 (2013)]. The error measure, which is given in terms of the probability that a missing process will be selected in the correct dynamics, requires estimation of the missing rate. In this work, we present an improved procedure for estimating the missing rate. The estimate found using the new procedure is within an order of magnitude of the correct missing rate, unlike our previous approach where the estimate was larger by orders of magnitude. This enables one to find the error in the KMC model more accurately. In addition, we find the time for which the KMC model can be used before a maximum error in the dynamics has been reached. (C) 2013 AIP Publishing LLC.
引用
收藏
页数:10
相关论文
共 50 条
[41]   Calculation of kinetic parameters for mixed TRIGA cores with Monte Carlo [J].
Snoj, Luka ;
Kavcic, Andrej ;
Zerovnik, Gasper ;
Ravnik, Matjaz .
ANNALS OF NUCLEAR ENERGY, 2010, 37 (02) :223-229
[42]   Acceleration scheme for particle transport in kinetic Monte Carlo methods [J].
Kaiser, Waldemar ;
Goesswein, Manuel ;
Gagliardi, Alessio .
JOURNAL OF CHEMICAL PHYSICS, 2020, 152 (17)
[43]   An overview of spatial microscopic and accelerated kinetic Monte Carlo methods [J].
Chatterjee, Abhijit ;
Vlachos, Dionisios G. .
JOURNAL OF COMPUTER-AIDED MATERIALS DESIGN, 2007, 14 (02) :253-308
[44]   Modeling of Heteroepitaxial Thin Film Growth by Kinetic Monte Carlo [J].
Yamamoto, Masahiro ;
Matsunaka, Daisuke ;
Shibutani, Yoji .
JAPANESE JOURNAL OF APPLIED PHYSICS, 2008, 47 (10) :7986-7992
[45]   Kinetic Monte Carlo modeling of oxide thin film growth [J].
Purton, John A. ;
Elena, Alin M. ;
Teobaldi, Gilberto .
JOURNAL OF CHEMICAL PHYSICS, 2022, 156 (21)
[46]   Kinetic Monte Carlo simulation of film morphologies at the initial stages [J].
XiaoPing Zheng ;
PeiFeng Zhang ;
DeYan He ;
Lian Li .
Science in China Series G: Physics, Mechanics and Astronomy, 2008, 51 :56-63
[47]   An energy basin finding algorithm for kinetic Monte Carlo acceleration [J].
Puchala, Brian ;
Falk, Michael L. ;
Garikipati, Krishna .
JOURNAL OF CHEMICAL PHYSICS, 2010, 132 (13)
[48]   Highly accelerated kinetic Monte Carlo models for depolymerisation systems [J].
Viet, Dominic Bui ;
Weihs, Gustavo Fimbres ;
Rajarathnam, Gobinath ;
Abbas, Ali .
COMPUTERS & CHEMICAL ENGINEERING, 2025, 193
[49]   Kinetic Monte Carlo modeling of silicate oligomerization and early gelation [J].
Zhang, Xue-Qing ;
van Santen, Rutger A. ;
Jansen, Antonius P. J. .
PHYSICAL CHEMISTRY CHEMICAL PHYSICS, 2012, 14 (34) :11969-11973
[50]   A new data structure for accelerating kinetic Monte Carlo method [J].
Zheng, Xu-Li ;
Quan, Dong-Hui ;
Zhang, Hai-Long ;
Li, Xiao-Hu ;
Chang, Qiang ;
Sipila, Olli .
RESEARCH IN ASTRONOMY AND ASTROPHYSICS, 2019, 19 (12)