71 citations · 292 across the 22 of their papers we have counts for
6 papers · 1 filter
BoltzmaNN: Predicting effective pair potentials and equations of state using neural networks
Fabian Berressem, Arash Nikoubashman
Neural networks (NNs) are employed to predict equations of state from a given isotropic pair potential using the virial expansion of the pressure. The NNs are trained with data fro…
Phase behavior of flexible and semiflexible polymers in solvents of varying quality
Jiarul Midya, Sergei A. Egorov, Kurt Binder +1
The interplay of nematic order and phase separation in solutions of semiflexible polymers in solvents of variable quality is investigated by density functional theory (DFT) and mol…
Transport coefficients of self-propelled particles. II. Numerics for vorticity fluctuations and the reverse perturbation method
Arash Nikoubashman, Thomas Ihle
In Part I of this two-part series, the reverse perturbation method for shearing simple liquids [Phys. Rev. E 59, 4894 (1999)] was extended to systems of interacting particles with…
Transport coefficients of self-propelled particles: Reverse perturbations and transverse current correlations
Arash Nikoubashman, Thomas Ihle
The reverse perturbation method [Phys. Rev. E 59, 4894 (1999)] for shearing simple liquids and measuring their viscosity is extended to the Vicsek-model (VM) of active particles [P…
Modeling hydrodynamic interactions in soft materials with multiparticle collision dynamics
Michael P. Howard, Arash Nikoubashman, Jeremy C. Palmer
Multiparticle collision dynamics (MPCD) is a flexible and robust mesoscale computational technique for simulating solvent-mediated hydrodynamic interactions in soft materials. Here…
The smectic phase in semiflexible polymer materials: A large scale Molecular Dynamics study
Andrey Milchev, Arash Nikoubashman, Kurt Binder
Semiflexible polymers in concentrated lyotropic solution are studied within a bead-spring model by molecular dynamics simulations, focusing on the emergence of a smectic A phase an…