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 …

Polymer informatics tools have been recently gaining ground to efficiently and effectively
develop, design, and discover new polymers that meet specific application needs. So far …

This article investigates the utility of machine learning (ML) methods for predicting and
analyzing the diverse physical characteristics of polymers. Leveraging a rich dataset of …

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

There has been rapidly growing demand of polymeric materials coming from different
aspects of modern life because of the highly diverse physical and chemical properties of …

Machine learning techniques are being applied in quantifying structure–property
relationships for a wide variety of materials, where the properly represented materials play …

In this perspective, the authors challenge the status quo of polymer innovation. The authors
first explore how research in polymer design is conducted today, which is both time …

Conspectus Polymeric material research is encountering a new paradigm driven by
machine learning (ML) and big data. The ML-assisted design has proven to be a successful …

Modern data-driven tools are transforming application-specific polymer development cycles.
Surrogate models that can be trained to predict properties of polymers are becoming …

The recent successes of the Materials Genome Initiative have opened up new opportunities
for data-centric informatics approaches in several subfields of materials research, including …