scholarly journals Comparison of the predictions of Langevin Dynamics-based diffusion charging collision kernel models with canonical experiments

2020 ◽  
Vol 140 ◽  
pp. 105481 ◽  
Author(s):  
Li Li ◽  
Harjindar Singh Chahl ◽  
Ranganathan Gopalakrishnan
Keyword(s):  
Langevin Dynamics ◽  
Collision Kernel ◽  
Kernel Models ◽  
Diffusion Charging

Effects of active crowder size and activity-crowding coupling on polymer translocation

Soft Matter ◽  
2020 ◽  
Author(s):  
Fei Tan ◽  
Ying Chen ◽  
Nanrong Zhao
Keyword(s):  
Langevin Dynamics ◽  
Dynamics Simulation ◽  
Biological Processes ◽  
Two Dimensional ◽  
Complex Environments ◽  
Polymer Translocation ◽  
Langevin Dynamics Simulation

Polymer translocation in complex environments is crucially important to many biological processes in life. In the present work, we adopted two-dimensional Langevin dynamics simulation to study the forced and unbiased...

AEROSOL COAGULATION IN DENSE SYSTEMS - LANGEVIN DYNAMICS SIMULATIONS

2004 ◽  
Vol 35 ◽  
pp. S963-S964
Author(s):  
T.M. TRZECIAK ◽  
A. PODGÓRSKI ◽  
J.W.M. VAN ERVEN ◽  
J.C.M. MARIJNISSEN
Keyword(s):  
Langevin Dynamics ◽  
Dynamics Simulations

DIFFUSION APPROXIMATION FOR TRANSPORT PROCESSES WITH GENERAL REFLECTION BOUNDARY CONDITIONS

2006 ◽  
Vol 16 (05) ◽  
pp. 717-762 ◽  
Author(s):  
CRISTINA COSTANTINI ◽  
THOMAS G. KURTZ
Keyword(s):  
Boundary Conditions ◽  
Stochastic Averaging ◽  
Transport Processes ◽  
Collision Kernel ◽  
Diffusion Approximations ◽  
Transport Models ◽  
Scattering Kernel ◽  
Reflection Boundary ◽  
Averaging Techniques ◽  
Number Of Particles

Diffusion approximations are obtained for space inhomogeneous linear transport models with reflection boundary conditions. The collision kernel is not required to satisfy any balance condition and the scattering kernel on the boundary is general enough to include all examples of boundary conditions known to the authors (with conservation of the number of particles) and, in addition, to model the Debye sheath. The mathematical approach does not rely on Hilbert expansions, but rather on martingale and stochastic averaging techniques.

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