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 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 …
A review on the application of molecular descriptors and machine learning in polymer design
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 …
properties and have been widely used in many applications and industrial products …
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 …
Machine learning in polymer informatics
W Sha, Y Li, S Tang, J Tian, Y Zhao, Y Guo, W Zhang… - InfoMat, 2021 - Wiley Online Library
Polymers have been widely used in energy storage, construction, medicine, aerospace, and
so on. However, the complexity of chemical composition and morphology of polymers has …
so on. However, the complexity of chemical composition and morphology of polymers has …
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 …
New opportunity: machine learning for polymer materials design and discovery
P Xu, H Chen, M Li, W Lu - Advanced Theory and Simulations, 2022 - Wiley Online Library
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 …
to discover new materials has become an innovation of materials science. The polymer …
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 …
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 …