Scientific discovery in the age of artificial intelligence

H Wang, T Fu, Y Du, W Gao, K Huang, Z Liu… - Nature, 2023‏ - nature.com
Artificial intelligence (AI) is being increasingly integrated into scientific discovery to augment
and accelerate research, hel** scientists to generate hypotheses, design experiments …

Generative models as an emerging paradigm in the chemical sciences

DM Anstine, O Isayev - Journal of the American Chemical Society, 2023‏ - ACS Publications
Traditional computational approaches to design chemical species are limited by the need to
compute properties for a vast number of candidates, eg, by discriminative modeling …

Recent advances and applications of deep learning methods in materials science

K Choudhary, B DeCost, C Chen, A Jain… - npj Computational …, 2022‏ - nature.com
Deep learning (DL) is one of the fastest-growing topics in materials data science, with
rapidly emerging applications spanning atomistic, image-based, spectral, and textual data …

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 …

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 …

Molecular representations in AI-driven drug discovery: a review and practical guide

L David, A Thakkar, R Mercado, O Engkvist - Journal of Cheminformatics, 2020‏ - Springer
The technological advances of the past century, marked by the computer revolution and the
advent of high-throughput screening technologies in drug discovery, opened the path to the …

Molecular characterization of polymer networks

SPO Danielsen, HK Beech, S Wang… - Chemical …, 2021‏ - ACS Publications
Polymer networks are complex systems consisting of molecular components. Whereas the
properties of the individual components are typically well understood by most chemists …

SELFIES and the future of molecular string representations

M Krenn, Q Ai, S Barthel, N Carson, A Frei, NC Frey… - Patterns, 2022‏ - cell.com
Artificial intelligence (AI) and machine learning (ML) are expanding in popularity for broad
applications to challenging tasks in chemistry and materials science. Examples include 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 …

Polymer networks: from plastics and gels to porous frameworks

Y Gu, J Zhao, JA Johnson - Angewandte Chemie International …, 2020‏ - Wiley Online Library
Polymer networks, which are materials composed of many smaller components—referred to
as “junctions” and “strands”—connected together via covalent or non‐covalent …