Recent progress and future prospects on all-organic polymer dielectrics for energy storage capacitors

QK Feng, SL Zhong, JY Pei, Y Zhao, DL Zhang… - Chemical …, 2021 - ACS Publications
With the development of advanced electronic devices and electric power systems, polymer-
based dielectric film capacitors with high energy storage capability have become particularly …

Machine learning in materials informatics: recent applications and prospects

R Ramprasad, R Batra, G Pilania… - npj Computational …, 2017 - nature.com
Propelled partly by the Materials Genome Initiative, and partly by the algorithmic
developments and the resounding successes of data-driven efforts in other domains …

Designing tailored combinations of structural units in polymer dielectrics for high-temperature capacitive energy storage

R Wang, Y Zhu, J Fu, M Yang, Z Ran, J Li, M Li… - Nature …, 2023 - nature.com
Many mainstream dielectric energy storage technologies in the emergent applications, such
as renewable energy, electrified transportations and advanced propulsion systems, are …

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 …

Design of functional and sustainable polymers assisted by artificial intelligence

H Tran, R Gurnani, C Kim, G Pilania, HK Kwon… - Nature Reviews …, 2024 - nature.com
Artificial intelligence (AI)-based methods continue to make inroads into accelerated
materials design and development. Here, we review AI-enabled advances made in the …

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-assisted discovery of polymers with high thermal conductivity using a molecular design algorithm

S Wu, Y Kondo, M Kakimoto, B Yang… - Npj Computational …, 2019 - nature.com
The use of machine learning in computational molecular design has great potential to
accelerate the discovery of innovative materials. However, its practical benefits still remain …

Polymer genome: a data-powered polymer informatics platform for property predictions

C Kim, A Chandrasekaran, TD Huan… - The Journal of …, 2018 - ACS Publications
The recent successes of the Materials Genome Initiative have opened up new opportunities
for data-centric informatics approaches in several subfields of materials research, including …

Machine-learning predictions of polymer properties with Polymer Genome

H Doan Tran, C Kim, L Chen… - Journal of Applied …, 2020 - pubs.aip.org
Polymer Genome is a web-based machine-learning capability to perform near-
instantaneous predictions of a variety of polymer properties. The prediction models are …

Polymer design using genetic algorithm and machine learning

C Kim, R Batra, L Chen, H Tran… - Computational Materials …, 2021 - Elsevier
Data driven or machine learning (ML) based methods have been recently used in materials
science to provide quick material property predictions. Although powerful and robust, these …