Machine learning in combinatorial polymer chemistry
AJ Gormley, MA Webb - Nature Reviews Materials, 2021 - nature.com
The design of new functional polymers depends on the successful navigation of their
structure-function landscapes. Advances in combinatorial polymer chemistry and machine …
structure-function landscapes. Advances in combinatorial polymer chemistry and machine …
Machine learning for polymeric materials: an introduction
Polymers are incredibly versatile materials and have become ubiquitous. Increasingly,
researchers are using data science and polymer informatics to design new materials and …
researchers are using data science and polymer informatics to design new materials and …
Polymer informatics at scale with multitask graph neural networks
Artificial intelligence-based methods are becoming increasingly effective at screening
libraries of polymers down to a selection that is manageable for experimental inquiry. The …
libraries of polymers down to a selection that is manageable for experimental inquiry. The …
Polymer informatics: opportunities and challenges
DJ Audus, JJ de Pablo - ACS macro letters, 2017 - ACS Publications
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 …
computational advances, can reduce both the time and cost of developing new materials …
Data-driven methods for accelerating polymer design
TK Patra - ACS Polymers Au, 2021 - ACS Publications
Optimal design of polymers is a challenging task due to their enormous chemical and
configurational space. Recent advances in computations, machine learning, and increasing …
configurational space. Recent advances in computations, machine learning, and increasing …
Polymer informatics with multi-task learning
Modern data-driven tools are transforming application-specific polymer development cycles.
Surrogate models that can be trained to predict properties of polymers are becoming …
Surrogate models that can be trained to predict properties of polymers are becoming …
Polymer genome: a data-powered polymer informatics platform for property predictions
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 …
for data-centric informatics approaches in several subfields of materials research, including …
Challenges and opportunities of polymer design with machine learning and high throughput experimentation
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 …
first explore how research in polymer design is conducted today, which is both time …
Emerging trends in machine learning: a polymer perspective
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 …
intelligence as applied to polymer science. Here, we highlight the unique challenges …
Polymer informatics: Current status and critical next steps
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 …
human life, science and technology. Polymer informatics is one such domain where AI and …