Machine learning for electrocatalyst and photocatalyst design and discovery

H Mai, TC Le, D Chen, DA Winkler… - Chemical …, 2022 - ACS Publications
Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels,
reducing the impact of global warming, and providing solutions to environmental pollution …

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 …

Emerging materials intelligence ecosystems propelled by machine learning

R Batra, L Song, R Ramprasad - Nature Reviews Materials, 2021 - nature.com
The age of cognitive computing and artificial intelligence (AI) is just dawning. Inspired by its
successes and promises, several AI ecosystems are blossoming, many of them within the …

Data‐Driven Materials Innovation and Applications

Z Wang, Z Sun, H Yin, X Liu, J Wang, H Zhao… - Advanced …, 2022 - Wiley Online Library
Owing to the rapid developments to improve the accuracy and efficiency of both
experimental and computational investigative methodologies, the massive amounts of data …

Polymer informatics: Current status and critical next steps

L Chen, G Pilania, R Batra, TD Huan, C Kim… - Materials Science and …, 2021 - Elsevier
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 …

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 …

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 …

TransPolymer: a Transformer-based language model for polymer property predictions

C Xu, Y Wang, A Barati Farimani - npj Computational Materials, 2023 - nature.com
Accurate and efficient prediction of polymer properties is of great significance in polymer
design. Conventionally, expensive and time-consuming experiments or simulations are …

Emerging trends in machine learning: a polymer perspective

TB Martin, DJ Audus - ACS Polymers Au, 2023 - ACS Publications
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 …

Alicyclic polyimides with large band gaps exhibit superior high-temperature capacitive energy storage

J Song, H Qin, S Qin, M Liu, S Zhang, J Chen… - Materials …, 2023 - pubs.rsc.org
Flexible polymer dielectrics for capacitive energy storage that can function well at elevated
temperatures are increasingly in demand for continuously advancing and miniaturizing …