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 approac...
This review article is intended as a practical guide for newcomers to the field of kinetic Monte Car...
This Article is brought to you for free and open access by the Mathematics and Statistics at Scholar...
Markov state models (MSMs) and other related kinetic network models are frequently used to study the...
The kinetic Monte Carlo (KMC) method is a popular modeling approach for reaching large materials len...
Markov state models (MSMs) are employed extensively in literature with the kinetic Monte Carlo (KMC)...
Markov state models (MSMs) are employed extensively in literature with the kinetic Monte Carlo (KMC)...
Kinetic Monte Carlo (KMC) models of complex materials and biomolecules are increasingly being constr...
International audienceExact modeling of the dynamics of chemical and material systems over experimen...
On-lattice Kinetic Monte Carlo (KMC) is a powerful computational method that is widely used to study...
This program has been imported from the CPC Program Library held at Queen's University Belfast (1969...
The relevance of kinetic Monte Carlo (kMC) algorithms and modeling to obtain and tune detailed molec...
The accuracy of the kinetic Monte Carlo (KMC) simulations depends on the reliability of transition d...
In this paper we study from a numerical analysis perspective the fractional step kinetic Monte Carlo...
Kinetic Monte Carlo (KMC) uses random numbers to simulate the time evolution of processes with well-...
A coarse-grained kinetic Monte Carlo (CG-KMC) method was recently introduced as a hierarchical multi...
This review article is intended as a practical guide for newcomers to the field of kinetic Monte Car...
This Article is brought to you for free and open access by the Mathematics and Statistics at Scholar...
Markov state models (MSMs) and other related kinetic network models are frequently used to study the...
The kinetic Monte Carlo (KMC) method is a popular modeling approach for reaching large materials len...
Markov state models (MSMs) are employed extensively in literature with the kinetic Monte Carlo (KMC)...
Markov state models (MSMs) are employed extensively in literature with the kinetic Monte Carlo (KMC)...
Kinetic Monte Carlo (KMC) models of complex materials and biomolecules are increasingly being constr...
International audienceExact modeling of the dynamics of chemical and material systems over experimen...
On-lattice Kinetic Monte Carlo (KMC) is a powerful computational method that is widely used to study...
This program has been imported from the CPC Program Library held at Queen's University Belfast (1969...
The relevance of kinetic Monte Carlo (kMC) algorithms and modeling to obtain and tune detailed molec...
The accuracy of the kinetic Monte Carlo (KMC) simulations depends on the reliability of transition d...
In this paper we study from a numerical analysis perspective the fractional step kinetic Monte Carlo...
Kinetic Monte Carlo (KMC) uses random numbers to simulate the time evolution of processes with well-...
A coarse-grained kinetic Monte Carlo (CG-KMC) method was recently introduced as a hierarchical multi...
This review article is intended as a practical guide for newcomers to the field of kinetic Monte Car...
This Article is brought to you for free and open access by the Mathematics and Statistics at Scholar...
Markov state models (MSMs) and other related kinetic network models are frequently used to study the...