Dissipative Particle Dynamics: Addressing deficiencies and establishing new frontiers
- John Brennan (U.S. Army Research Laboratory, USA)
- Martin Lisal (Academy of Sciences of the Czech Republic, Czech Republic)
Since its development a little over 15 years ago, the dissipative particle dynamics method (DPD) [1,2] has become a robust tool for the study of soft condensed matter including polymers, polymer-nanoparticle systems and colloids. DPD allows for simulation studies at length and time scales that are inaccessible using molecular-level methods, the reasons for which are two-fold. First, larger length scales can be simulated since the internal degrees of freedom of the atoms and molecules which a DPD particle is intended to represent are effectively ignored. Secondly, the weakly repulsive particle interactions lend themselves to stable integrations of the equations of motion at longer time steps.
The fundamentals of the DPD method are now fairly well-established [3-7], as are the technical subtleties [8, 9] and the coarse-grained parametrization of the DPD particles, with improvements consistently being introduced e.g., . Moreover, the similarities between the molecular dynamics and the DPD methods make it a rather easy method to implement where many of the same computational tricks can be utilized. Extensions of the DPD method which impose energy conservation have also been introduced allowing for internal energy exchange between particles [11, 12]. All of these factors have led to many DPD simulation studies which have provided insight into a variety of phenomena that occurs at the mesoscale, most notably for polymer, polymer-nanoparticle and colloid systems. However, DPD is beginning to be applied in other areas such as biophysics, for example, in the simulation of biomembranes and lipid bilayers. Furthermore, it is expected that DPD will play an ever-increasing role in multiscale modeling approaches through bridging of the atomistic and continuum scales. In such approaches, atomistic simulations are performed to build the DPD models, followed by DPD simulations which provide the necessary input to the continuum codes. Implementations of such approaches can circumvent assumptions in the continuum codes since the mesoscale simulations can provide more accurate estimates of the thermodynamic state within the localized regions compared to a constitutive equation.