In this work we compare and characterize the behavior of Langevin and dissipative particle dynamics (DPD) thermostats in a broad range of nonequilibrium simulations of polymeric systems. Polymer brushes in relative sliding motion, polymeric liquids in Poiseuille and Couette flows, and brush-melt interfaces are used as model systems to analyze the efficiency and limitations of different Langevin and DPD thermostat implementations. Widely used coarse-grained bead-spring models under good and poor solvent conditions are employed to assess the effects of the thermostats. We considered equilibrium, transient, and steady state examples for testing the ability of the thermostats to maintain constant temperature and to reproduce the underlying phys...
Dissipative particle dynamics (DPD) is a relatively new technique which has proved successful in the...
We present here a systematic study of dynamic behavior for polymer (PE) melt by means of Dissipativ...
Langevin dynamics is a versatile stochastic model used in biology, chemistry, engineering, physics a...
The numerical investigation of the statics and dynamics of systems in non-equilibrium in general, an...
In this article we present a new thermostat - theory and simulation results - obtained by combining ...
AbstractWe examine the formulation and numerical treatment of dissipative particle dynamics (DPD) an...
AbstractWe review and compare numerical methods that simultaneously control temperature while preser...
We discuss dissipative particle dynamics as a thermostat to molecular dynamics, and highlight some o...
In this article, we present several algorithms for stochastic dynamics, including Langevin dynamics ...
The authors analyzed extensively the dynamics of polymer chains in solutions simulated with dissipat...
A new technique, dissipative particle dynamics (DPD), appears promising as a means of studying the d...
Temperature control algorithms in molecular dynamics (MD) simulations are necessary to study isother...
In this volume, a relatively new simulation method---Dissipative Particle Dynamics (DPD) is used to ...
Dissipative particle dynamics (DPD) and multi-particle collision (MPC) dynamics are powerful tools t...
Thermostats are often used in various condensed matter problems, e.g. when a biological molecule und...
Dissipative particle dynamics (DPD) is a relatively new technique which has proved successful in the...
We present here a systematic study of dynamic behavior for polymer (PE) melt by means of Dissipativ...
Langevin dynamics is a versatile stochastic model used in biology, chemistry, engineering, physics a...
The numerical investigation of the statics and dynamics of systems in non-equilibrium in general, an...
In this article we present a new thermostat - theory and simulation results - obtained by combining ...
AbstractWe examine the formulation and numerical treatment of dissipative particle dynamics (DPD) an...
AbstractWe review and compare numerical methods that simultaneously control temperature while preser...
We discuss dissipative particle dynamics as a thermostat to molecular dynamics, and highlight some o...
In this article, we present several algorithms for stochastic dynamics, including Langevin dynamics ...
The authors analyzed extensively the dynamics of polymer chains in solutions simulated with dissipat...
A new technique, dissipative particle dynamics (DPD), appears promising as a means of studying the d...
Temperature control algorithms in molecular dynamics (MD) simulations are necessary to study isother...
In this volume, a relatively new simulation method---Dissipative Particle Dynamics (DPD) is used to ...
Dissipative particle dynamics (DPD) and multi-particle collision (MPC) dynamics are powerful tools t...
Thermostats are often used in various condensed matter problems, e.g. when a biological molecule und...
Dissipative particle dynamics (DPD) is a relatively new technique which has proved successful in the...
We present here a systematic study of dynamic behavior for polymer (PE) melt by means of Dissipativ...
Langevin dynamics is a versatile stochastic model used in biology, chemistry, engineering, physics a...