arXiv subjects

Fabian Berressem

Publications and source records attributed to Fabian Berressem.

2 recordsLinked to original sources

arXiv2023

Viscosity of flexible and semiflexible ring melts -- molecular origins and flow-induced segregation

We investigate with numerical simulations the molecular origin of viscosity in melts of flexible and semiflexible oligomer rings in comparison to corresponding systems with linear chains. The strong increase of viscosity with ring stiffness is linked to the formation of entangled clusters, which dissolve under shear. This shear-induced breakup and alignment of rings in the flow direction lead to pronounced shear-thinning and non-Newtonian behavior. In melts of linear chains, the viscosity can be associated with the (average) number of entanglements between chains, which also dissolve under shear. While blends of flexible and semiflexible rings are mixed at rest, the two species separate under flow. This phenomenon has potential applications in microfluidic devices to segregate ring polymers of similar mass and chemical composition by their bending rigidity.

cond-mat.soft↗

arXiv2020

BoltzmaNN: Predicting effective pair potentials and equations of state using neural networks

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 from molecular dynamics simulations of monoatomic gases and liquids, sampled in the $NVT$ ensemble at various densities. We find that the NNs provide much more accurate results compared to the analytic low-density limit estimate of the second virial coefficient. Further, we design and train NNs for computing (effective) pair potentials from radial pair distribution functions, $g(r)$, a task which is often performed for inverse design and coarse-graining. Providing the NNs with additional information on the forces greatly improves the accuracy of the predictions, since more correlations are taken into account; the predicted potentials become smoother, are significantly closer to the target potentials, and are more transferable as a result.

cond-mat.soft↗