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Surfaces serve as highly efficient catalysts for a vast variety of chemical reactions. Typically, such surface reactions involve billions of molecules which diffuse and react over macroscopic areas. Therefore, stochastic fluctuations are…

Statistical Mechanics · Physics 2007-10-12 B. Barzel , O. Biham

The modeling and simulation of stochastic reaction-diffusion processes is a topic of steady interest that is approached with a wide range of methods. \rev{At the level of particle-resolved descriptions, where chemical reactions are coupled…

Subdiffusion has been proposed as an explanation of various kinetic phenomena inside living cells. In order to fascilitate large-scale computational studies of subdiffusive chemical processes, we extend a recently suggested mesoscopic model…

Analysis of PDEs · Mathematics 2018-02-19 Emilie Blanc , Stefan Engblom , Andreas Hellander , Per Lötstedt

By discretising space into compartments and letting system dynamics be governed by the reaction-diffusion master equation, it is possible to derive and simulate a stochastic model of reaction and diffusion on an arbitrary domain. However,…

Computational Physics · Physics 2019-11-27 Bartosz J. Bartmanski , Ruth E. Baker

Traditional chemical kinetics may be inappropriate to describe chemical reactions in micro-domains involving only a small number of substrate and reactant molecules. Starting with the stochastic dynamics of the molecules, we derive a…

Mathematical Physics · Physics 2009-11-10 D. Holcman , Z. Schuss

Diffusion-limited association reactions are ubiquitous in nature. They are particularly important for biological reactions, where the reaction rates are often determined by the diffusive transport of the molecules on two-dimensional…

Soft Condensed Matter · Physics 2020-10-06 Sumantra Sarkar

Several different methods exist for efficient approximation of paths in multiscale stochastic chemical systems. Another approach is to use bursts of stochastic simulation to estimate the parameters of a stochastic differential equation…

Numerical Analysis · Mathematics 2014-12-19 Simon Cotter , Radek Erban

The interactions between diffusing molecules and membrane-bound receptors drive numerous cellular processes. In this work, we develop a spatial model of molecular interactions with membrane receptors by homogenizing the cell membrane and…

Quantitative Methods · Quantitative Biology 2025-01-24 Anil Cengiz , Sean D Lawley

The reversible reactions like A+B <-> C in the many-component diffusive system affect the diffusive properties of the constituents. The effective conjugation of irreversible processes of different dimensionality takes place due to the…

Other Condensed Matter · Physics 2007-05-23 Serge Shpyrko , Vladimir M. Sysoev

The efficiency of exact simulation methods for the reaction-diffusion master equation (RDME) is severely limited by the large number of diffusion events if the mesh is fine or if diffusion constants are large. Furthermore, inherent…

Numerical Analysis · Computer Science 2015-06-15 Andreas Hellander , Michael Lawson , Brian Drawert , Linda Petzold

We investigate the influence of a stochastically fluctuating step-barrier potential on bimolecular reaction rates by exact analytical theory and stochastic simulations. We demonstrate that the system exhibits a new resonant reaction…

Chemical Physics · Physics 2016-03-23 Jakob J. Kolb , Stefano Angioletti-Uberti , Joachim Dzubiella

Many cellular and subcellular biological processes can be described in terms of diffusing and chemically reacting species (e.g. enzymes). Such reaction-diffusion processes can be mathematically modelled using either deterministic…

Biological Physics · Physics 2015-06-26 Radek Erban , S. Jonathan Chapman

Reaction-diffusion models are widely used to study spatially-extended chemical reaction systems. In order to understand how the dynamics of a reaction-diffusion model are affected by changes in its input parameters, efficient methods for…

Quantitative Methods · Quantitative Biology 2017-03-08 Christopher Lester , Christian A. Yates , Ruth E. Baker

The macroscopic behavior of the solution of a coupled system of partial differential equations arising in the modeling of reaction-diffusion processes in periodic porous media is analyzed. Our mathematical model can be used for studying…

Analysis of PDEs · Mathematics 2019-06-19 G. Cardone , C. Perugia , C. Timofte

We have developed an algorithm coupling mesoscopic simulations on different levels in a hierarchy of Cartesian meshes. Based on the multiscale nature of the chemical reactions, some molecules in the system will live on a fine-grained mesh,…

Numerical Analysis · Mathematics 2020-02-19 Stefan Hellander , Andreas Hellander

Chemical reactions inside cells are generally considered to happen within fixed-size compartments. Needless to say, cells and their compartments are highly dynamic. Thus, such stringent assumptions may not reflect biochemical reality, and…

Quantitative Methods · Quantitative Biology 2016-02-17 Atiyo Ghosh , Tatiana T. Marquez-Lago

Reaction rate equations are ordinary differential equations that are frequently used to describe deterministic chemical kinetics at the macroscopic scale. At the microscopic scale, the chemical kinetics is stochastic and can be captured by…

Soft Condensed Matter · Physics 2021-05-12 Ariana Torres-Knoop , Ivan Kryven

We study a system of diffusing point particles in which any triplet of particles reacts and is removed from the system when the relative proximity of the constituent particles satisfies a predefined condition. Proximity-based reaction…

Numerical Analysis · Mathematics 2025-04-07 Taylor Kearney , Ricardo Ruiz-Baier , Mark B. Flegg

Morphogenesis is central to biology but remains largely unexplored in chemistry. Reaction-diffusion (RD) mechanisms are, however, essential to understand how shape emerges in the living world. While numerical methods confirm the incredible…

Pattern Formation and Solitons · Physics 2014-07-17 Anton S. Zadorin , Yannick Rondelez , Jean-Christophe Galas , André Estevez-Torres

The reaction-diffusion equation is one of the cornerstones equations in applied science and engineering. In the present study, a deep neural network has been trained in order to predict the solution of the equation with different…

Machine Learning · Computer Science 2019-12-12 Amin Karimi Monsefi , Rana Bakhtiyarzade