Machine learning (ML) has emerged as a transformative tool in polymer science, enabling researchers to predict material properties and guide polymer design with unprecedented speed and precision.

With rapid advances in high-throughput computing, machine learning (ML), and artificial intelligence (AI) applications, polymer informatics is emerging as a promising tool to ensure breakthrough ...

Machine learning, a tool increasingly used for the discovery and design of new materials, has now been adopted by researchers to design polymer brush films with desirable protein adsorption properties ...

A research group has developed SPACIER, an advanced polymer material design tool that integrates machine learning with molecular simulations. As a proof of concept, the group successfully synthesized ...

Hundreds of millions of tons of polymer materials are produced globally for use in a vast and ever-growing application space with new material demands such as green chemistry polymers, consumer ...

Polymer-based dielectrics are widely used in different electrical and electronic devices like capacitors, power transmission cables, and microchips. To adapt to different working conditions, a range ...

How can AI enhance polymers to develop the next generation of bioelectronics? This is what a recent study published in the journal Matter hopes to address as a team of researchers investigated new ...

Polymer brush films consists of monomer chains grown in close proximity on a substrate. The monomers, which look like “bristles” at the nanoscale, form a highly functional and versatile coating such ...