The Martini model, a coarse‐grained force field for molecular dynamics simulations, has
been around for nearly two decades. Originally developed for lipid‐based systems by the …

In the recent decades, with rapid development in computing power and algorithms, machine
learning (ML) has exhibited its enormous potential in new polymer discovery. Herein, the …

This paper describes and provides Z1+, the successor of the Z-and Z1-codes for topological
analyses of mono-and polydisperse entangled linear polymeric systems, in the presence or …

Polymer materials are multiscale systems by definition. Already the description of a single
macromolecule involves a multitude of scales, and cooperative processes in polymer …

Fractional free volume (FFV) characterizes the microstructural level features of polymers and
affects their properties including thermal, mechanical, and separation performance …

A fundamental endeavour in macromolecular science is the control of molecular-level
complexity, including molecular weight distribution, end groups and architecture. Since the …

For decades, a wide variety of products have benefitted from the use of flexible PVC, ranging
from healthcare to cable to packaging & household items. The uniqueness of PVC rises from …

Establishing the structure-property relationship is extremely valuable for the molecular
design of copolymers. However, machine learning (ML) models can incorporate both …

This work presents a framework governing the development of an efficient, accurate, and
transferable coarse-grained (CG) model of a polyether material. The framework combines …

Data-driven materials science has realized a new paradigm by integrating materials domain
knowledge and machine-learning (ML) techniques. However, ML-based research has often …