Applied machine learning as a driver for polymeric biomaterials design
SM McDonald, EK Augustine, Q Lanners… - Nature …, 2023 - nature.com
Polymers are ubiquitous to almost every aspect of modern society and their use in medical
products is similarly pervasive. Despite this, the diversity in commercial polymers used in …
products is similarly pervasive. Despite this, the diversity in commercial polymers used in …
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 …
Machine learning enables interpretable discovery of innovative polymers for gas separation membranes
Polymer membranes perform innumerable separations with far-reaching environmental
implications. Despite decades of research, design of new membrane materials remains a …
implications. Despite decades of research, design of new membrane materials remains a …
A graph representation of molecular ensembles for polymer property prediction
Synthetic polymers are versatile and widely used materials. Similar to small organic
molecules, a large chemical space of such materials is hypothetically accessible …
molecules, a large chemical space of such materials is hypothetically accessible …
Artificial intelligence driven design of catalysts and materials for ring opening polymerization using a domain-specific language
Advances in machine learning (ML) and automated experimentation are poised to vastly
accelerate research in polymer science. Data representation is a critical aspect for enabling …
accelerate research in polymer science. Data representation is a critical aspect for enabling …
Featurization strategies for polymer sequence or composition design by machine learning
The emergence of data-intensive scientific discovery and machine learning has dramatically
changed the way in which scientists and engineers approach materials design …
changed the way in which scientists and engineers approach materials design …
Understanding and modeling polymers: The challenge of multiple scales
F Schmid - ACS Polymers Au, 2022 - ACS Publications
Polymer materials are multiscale systems by definition. Already the description of a single
macromolecule involves a multitude of scales, and cooperative processes in polymer …
macromolecule involves a multitude of scales, and cooperative processes in polymer …
Polymer graph neural networks for multitask property learning
O Queen, GA McCarver, S Thatigotla… - npj Computational …, 2023 - nature.com
The prediction of a variety of polymer properties from their monomer composition has been a
challenge for material informatics, and their development can lead to a more effective …
challenge for material informatics, and their development can lead to a more effective …
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 …
Discovery of multi-functional polyimides through high-throughput screening using explainable machine learning
Polyimides have been widely used in modern industries because of their excellent
mechanical and thermal properties, eg, high-temperature fuel cells, displays, and aerospace …
mechanical and thermal properties, eg, high-temperature fuel cells, displays, and aerospace …