Polymers are the preferred materials for dielectrics in high-energy-density capacitors. The
electrification of transport and growing demand for advanced electronics require polymer …

Artificial intelligence (AI) based approaches are beginning to impact several domains of
human life, science and technology. Polymer informatics is one such domain where AI and …

Synthetic polymers are versatile and widely used materials. Similar to small organic
molecules, a large chemical space of such materials is hypothetically accessible …

Polymer Genome is a web-based machine-learning capability to perform near-
instantaneous predictions of a variety of polymer properties. The prediction models are …

In the field of polymer informatics, utilizing machine learning (ML) techniques to evaluate the
glass transition temperature T g and other properties of polymers has attracted extensive …

Polymers are a vital part of everyday life. Their chemical universe is so large that it presents
unprecedented opportunities as well as significant challenges to identify suitable application …

Data driven or machine learning (ML) based methods have been recently used in materials
science to provide quick material property predictions. Although powerful and robust, these …

The design rules for materials are clear for applications with a single objective. For most
applications, however, there are often multiple, sometimes competing objectives where …

Polymer dielectrics have been proved to be critical materials for film capacitors with high
energy density. However, the harsh operating environment requires dielectrics with high …

This study employs various machine learning algorithms to model the electrical conductivity
and gas sensing responses of polyaniline/graphene (PANI/Gr) nanocomposites based on a …