The powerful data processing and pattern recognition capabilities of machine learning (ML)
technology have provided technical support for the innovation in computational chemistry …

Polymers are high-molecular-weight compounds constructed by the covalent bonding of
numerous identical or similar monomers so that their 3D structures are complex yet exhibit …

This study examines the effectiveness of generative models in drug discovery, material
science, and polymer science, aiming to overcome constraints associated with traditional …

In the past few decades, polymers, high-molecular-weight compounds formed by bonding
numerous identical or similar monomers covalently, have played an essential role in various …

Machine learning (ML) has become a powerful tool in polymer science, with its success
strongly relying on effective structural representations of polymers. While the Simplified …

Representation systems for polymers are a constant issue in deep-learning models for
polymer property prediction, necessitating a balance between structural accuracy with …