Bioactive synthetic polymers
Synthetic polymers are omnipresent in society as textiles and packaging materials, in
construction and medicine, among many other important applications. Alternatively, natural …
construction and medicine, among many other important applications. Alternatively, natural …
Machine learning in materials science: From explainable predictions to autonomous design
G Pilania - Computational Materials Science, 2021 - Elsevier
The advent of big data and algorithmic developments in the field of machine learning (and
artificial intelligence, in general) have greatly impacted the entire spectrum of physical …
artificial intelligence, in general) have greatly impacted the entire spectrum of physical …
[HTML][HTML] 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 …
Machine learning on a robotic platform for the design of polymer–protein hybrids
Polymer–protein hybrids are intriguing materials that can bolster protein stability in non‐
native environments, thereby enhancing their utility in diverse medicinal, commercial, and …
native environments, thereby enhancing their utility in diverse medicinal, commercial, and …
Benchmarking machine learning models for polymer informatics: an example of glass transition temperature
In the field of polymer informatics, utilizing machine learning (ML) techniques to evaluate the
glass transition temperature T g and other properties of polymers has attracted extensive …
glass transition temperature T g and other properties of polymers has attracted extensive …
Machine-Learning-Guided Discovery of 19F MRI Agents Enabled by Automated Copolymer Synthesis
M Reis, F Gusev, NG Taylor, SH Chung… - Journal of the …, 2021 - ACS Publications
Modern polymer science suffers from the curse of multidimensionality. The large chemical
space imposed by including combinations of monomers into a statistical copolymer …
space imposed by including combinations of monomers into a statistical copolymer …
[HTML][HTML] polyBERT: a chemical language model to enable fully machine-driven ultrafast polymer informatics
C Kuenneth, R Ramprasad - Nature Communications, 2023 - nature.com
Polymers are a vital part of everyday life. Their chemical universe is so large that it presents
unprecedented opportunities as well as significant challenges to identify suitable application …
unprecedented opportunities as well as significant challenges to identify suitable application …
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 …
[HTML][HTML] TransPolymer: a Transformer-based language model for polymer property predictions
Accurate and efficient prediction of polymer properties is of great significance in polymer
design. Conventionally, expensive and time-consuming experiments or simulations are …
design. Conventionally, expensive and time-consuming experiments or simulations are …
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 …