KINETIC MONTE CARLO METHOD FOR MODELING THE KINETICS OF HOMOGENEOUS LIQUID-PHASE REACTIONS IN MICROREACTORS
Authors:
1.
St. Petersburg State Technological Institute (technical university)
(kafedra sistemnogo analiza i upravleniya)
graduate student from 01.01.2023 until now
graduate student from 01.01.2023 until now
2.
St. Petersburg State Technological Institute (technical university)
Type:
Article
Pages:
from 154
to 161
Status:
Published
Received:
31.01.2026
Accepted:
31.01.2026
Published:
31.01.2026
Language:
Russian
Keywords:
MATHEMATICAL MODELING, KINETIC MONTE CARLO METHOD, HOMOGENEOUS REACTIONS, OPTIMIZATION OF CHEMICAL ENGINEERING PROCESSES, MODELING OF CHEMICAL REACTION KINETICS, MICROREACTORS
Abstract:
This article explores the feasibility of using the kinetic Monte Carlo method (KMC) to simulate the kinetics of homogeneous liquid-phase reactions in microreactors. Despite the successful use of microreactors in multiphase processes, process intensification in microreactors remains an understudied area requiring the development of new modeling approaches. This paper presents a detailed stochastic KMC algorithm that takes into account the time sequence of elementary reaction steps and provides a critical comparison with molecular dynamics. It is shown that KMC allows for more efficient modeling of nonlinear effects, stochastic fluctuations, and multistep reaction mechanisms on time scales inaccessible to traditional molecular modeling. To verify the developed software package, a numerical simulation of the methanolysis reaction was performed in Python, followed by parallel verification of the results using Kinetiscope. A comprehensive quantitative analysis of the discrepancies was conducted using the mean absolute error, cosine similarity, and Pearson's correlation coefficient. The results demonstrate high accuracy in modeling the system's main components. Thus, the developed model has proven its applicability for studying and optimizing the intensification of chemical-engineering systems in microreactors, providing a basis for developing energy-efficient and environmentally friendly production technologies.
This article explores the feasibility of using the kinetic Monte Carlo method (KMC) to simulate the kinetics of homogeneous liquid-phase reactions in microreactors. Despite the successful use of microreactors in multiphase processes, process intensification in microreactors remains an understudied area requiring the development of new modeling approaches. This paper presents a detailed stochastic KMC algorithm that takes into account the time sequence of elementary reaction steps and provides a critical comparison with molecular dynamics. It is shown that KMC allows for more efficient modeling of nonlinear effects, stochastic fluctuations, and multistep reaction mechanisms on time scales inaccessible to traditional molecular modeling. To verify the developed software package, a numerical simulation of the methanolysis reaction was performed in Python, followed by parallel verification of the results using Kinetiscope. A comprehensive quantitative analysis of the discrepancies was conducted using the mean absolute error, cosine similarity, and Pearson's correlation coefficient. The results demonstrate high accuracy in modeling the system's main components. Thus, the developed model has proven its applicability for studying and optimizing the intensification of chemical-engineering systems in microreactors, providing a basis for developing energy-efficient and environmentally friendly production technologies.
Keywords:
MATHEMATICAL MODELING, KINETIC MONTE CARLO METHOD, HOMOGENEOUS REACTIONS, OPTIMIZATION OF CHEMICAL ENGINEERING PROCESSES, MODELING OF CHEMICAL REACTION KINETICS, MICROREACTORS
MATHEMATICAL MODELING, KINETIC MONTE CARLO METHOD, HOMOGENEOUS REACTIONS, OPTIMIZATION OF CHEMICAL ENGINEERING PROCESSES, MODELING OF CHEMICAL REACTION KINETICS, MICROREACTORS
