Design of functional and sustainable polymers assisted by artificial intelligence
Artificial intelligence (AI)-based methods continue to make inroads into accelerated
materials design and development. Here, we review AI-enabled advances made in the …
materials design and development. Here, we review AI-enabled advances made in the …
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 …
Rapid inverse design of metamaterials based on prescribed mechanical behavior through machine learning
Designing and printing metamaterials with customizable architectures enables the
realization of unprecedented mechanical behaviors that transcend those of their constituent …
realization of unprecedented mechanical behaviors that transcend those of their constituent …
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 …
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 predictions of polymer properties with Polymer Genome
Polymer Genome is a web-based machine-learning capability to perform near-
instantaneous predictions of a variety of polymer properties. The prediction models are …
instantaneous predictions of a variety of polymer properties. The prediction models are …
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 …
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 …
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 for Predicting the Band Gaps of ABX3 Perovskites from Elemental Properties
The band gap is an important parameter that determines light-harvesting capability of
perovskite materials. It governs the performance of various optoelectronic devices such as …
perovskite materials. It governs the performance of various optoelectronic devices such as …