68 citations · 157 across the 5 of their papers we have counts for
5 papers
Prediction of Diblock Copolymer Morphology via Machine Learning
Hyun Park, Boyuan Yu, Juhae Park +4
A machine learning approach is presented to accelerate the computation of block polymer morphology evolution for large domains over long timescales. The strategy exploits the separ…
PySAGES: flexible, advanced sampling methods accelerated with GPUs
Pablo F. Zubieta Rico, Ludwig Schneider, Gustavo R. Pérez-Lemus +11
Molecular simulations are an important tool for research in physics, chemistry, and biology. The capabilities of simulations can be greatly expanded by providing access to advanced…
Entanglements via Slip-Springs with Soft, Coarse-Grained Models for Systems Having Explicit Liquid-Vapor Interfaces
Ludwig Schneider, Juan de Pablo
Recent advances in nano-rheology require that new methods and models be developed to describe the equilibrium and non-equilibrium properties of entangled polymeric materials and th…
Dynamics and Rheology of Polymer Melts via Hierarchical Atomistic, Coarse-grained, and Slip-spring Simulations
Alireza F. Behbahani, Ludwig Schneider, Anastassia Rissanou +9
A hierarchical (triple scale) simulation methodology is presented for the prediction of the dynamical and rheological properties of high molecular weight entangled polymer melts. T…
Multi-Architecture Monte-Carlo (MC) Simulation of Soft Coarse-Grained Polymeric Materials: SOft coarse grained Monte-carlo Acceleration (SOMA)
Ludwig Schneider, Marcus Müller
Multi-component polymer systems are important for the development of new materials because of their ability to phase-separate or self-assemble into nano-structures. The Single-Chai…