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 …
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 …
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 …
The rise of machine learning in polymer discovery
In the recent decades, with rapid development in computing power and algorithms, machine
learning (ML) has exhibited its enormous potential in new polymer discovery. Herein, the …
learning (ML) has exhibited its enormous potential in new polymer discovery. Herein, the …
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 …
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 …
Innovative materials science via machine learning
C Gao, X Min, M Fang, T Tao, X Zheng… - Advanced Functional …, 2022 - Wiley Online Library
Nowadays, the research on materials science is rapidly entering a phase of data‐driven
age. Machine learning, one of the most powerful data‐driven methods, have been being …
age. Machine learning, one of the most powerful data‐driven methods, have been being …
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 …
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 …
Machine learning in materials genome initiative: A review
Y Liu, C Niu, Z Wang, Y Gan, Y Zhu, S Sun… - Journal of Materials …, 2020 - Elsevier
Discovering new materials with excellent performance is a hot issue in the materials
genome initiative. Traditional experiments and calculations often waste large amounts of …
genome initiative. Traditional experiments and calculations often waste large amounts of …