Machine learning for electrocatalyst and photocatalyst design and discovery
Electrocatalysts and photocatalysts are key to a sustainable future, generating clean fuels,
reducing the impact of global warming, and providing solutions to environmental pollution …
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 …
products is similarly pervasive. Despite this, the diversity in commercial polymers used in …
Emerging materials intelligence ecosystems propelled by machine learning
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 …
successes and promises, several AI ecosystems are blossoming, many of them within the …
Data‐Driven Materials Innovation and Applications
Owing to the rapid developments to improve the accuracy and efficiency of both
experimental and computational investigative methodologies, the massive amounts of data …
experimental and computational investigative methodologies, the massive amounts of data …
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 …
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 …
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 …
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 …
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 …
temperatures are increasingly in demand for continuously advancing and miniaturizing …