Materials development has historically been driven by human needs and desires, and this is
likely to continue in the foreseeable future. The global population is expected to reach ten …

Much effort has been invested for nearly five decades to identify and develop new polymer
capacitor dielectrics for higher than ambient temperature applications. Simultaneous …

Traditional machine learning (ML) metrics overestimate model performance for materials
discovery. We introduce (1) leave-one-cluster-out cross-validation (LOCO CV) and (2) a …

Integrating artificial intelligence (AI) and computer science together with current approaches
in material synthesis and optimization will act as an effective approach for speeding up the …

Abstract The Materials Genome Initiative (MGI) has heralded a sea change in the philosophy
of materials design. In an increasing number of applications, the successful deployment of …

Polymers are incredibly versatile materials and have become ubiquitous. Increasingly,
researchers are using data science and polymer informatics to design new materials and …

The dielectric constant (ϵ) is a critical parameter utilized in the design of polymeric
dielectrics for energy storage capacitors, microelectronic devices, and high-voltage …

The ever-increasing demand for novel polymers with superior properties requires a deeper
understanding and exploration of the chemical space. Recently, data-driven approaches to …

There has been a tremendous increase in demand for virgin and postconsumer recycled
(PCR) polymers due to their wide range of chemical and physical characteristics. Despite …

We propose a chemical language processing model to predict polymers' glass transition
temperature (T g) through a polymer language (SMILES, Simplified Molecular Input Line …