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

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

Polymers are an important class of materials with vast arrays of physical and chemical
properties and have been widely used in many applications and industrial products …

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 …

The design of new functional polymers depends on the successful navigation of their
structure-function landscapes. Advances in combinatorial polymer chemistry and machine …

Under the guidance of the material genome initiative (MGI), the use of data‐driven methods
to discover new materials has become an innovation of materials science. The polymer …

We are entering an era where large volumes of scientific data, coupled with algorithmic and
computational advances, can reduce both the time and cost of developing new materials …

In the last five years, there has been tremendous growth in machine learning and artificial
intelligence as applied to polymer science. Here, we highlight the unique challenges …

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 …

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 …