In the last five years, there has been tremendous growth in machine learning and artificial
intelligence as applied to polymer science. Here, we highlight the unique challenges …

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 …

Language models exhibit a profound aptitude for addressing multimodal and multidomain
challenges, a competency that eludes the majority of off-the-shelf machine learning models …

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

Predicting and understanding the phase equilibria or phase separation in polymer–solvent
solutions represent unresolved fundamental problems in polymer science. The phase …

Synthetic polymers are highly customizable with tailored structures and functionality, yet this
versatility generates challenges in the design of advanced materials due to the size and …

Polymers with exceptional heat resistance are critically valuable in numerous domains,
particularly as essential components of flexible organic light-emitting diodes. Among these …

Thermal stability is an invaluable aspect in assessing polymer properties, especially for
polyimides (PIs), which are known for their excellent heat resistance. However, empirically …

Unique structure representation of polymers plays a crucial role in developing models for
polymer property prediction and polymer design by data-centric approaches. Currently …

Lower critical solution temperature (LCST) and upper critical solution temperature (UCST)
are key thermodynamic properties of binary polymer solutions. In this work, quantitative …