A brief introduction to chemical reaction optimization

CJ Taylor, A Pomberger, KC Felton, R Grainger… - Chemical …, 2023‏ - ACS Publications
From the start of a synthetic chemist's training, experiments are conducted based on recipes
from textbooks and manuscripts that achieve clean reaction outcomes, allowing the scientist …

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 …

Accelerating materials discovery using artificial intelligence, high performance computing and robotics

EO Pyzer-Knapp, JW Pitera, PWJ Staar… - npj Computational …, 2022‏ - nature.com
New tools enable new ways of working, and materials science is no exception. In materials
discovery, traditional manual, serial, and human-intensive work is being augmented by …

Artificial intelligence for science in quantum, atomistic, and continuum systems

X Zhang, L Wang, J Helwig, Y Luo, C Fu, Y **e… - arxiv preprint arxiv …, 2023‏ - arxiv.org
Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural
sciences. Today, AI has started to advance natural sciences by improving, accelerating, and …

Translation between molecules and natural language

C Edwards, T Lai, K Ros, G Honke, K Cho… - arxiv preprint arxiv …, 2022‏ - arxiv.org
We present $\textbf {MolT5} $$-$ a self-supervised learning framework for pretraining
models on a vast amount of unlabeled natural language text and molecule strings. $\textbf …

Unifying molecular and textual representations via multi-task language modelling

D Christofidellis, G Giannone, J Born… - International …, 2023‏ - proceedings.mlr.press
The recent advances in neural language models have also been successfully applied to the
field of chemistry, offering generative solutions for classical problems in molecular design …

[HTML][HTML] De novo molecular design and generative models

J Meyers, B Fabian, N Brown - Drug discovery today, 2021‏ - Elsevier
Molecular design strategies are integral to therapeutic progress in drug discovery.
Computational approaches for de novo molecular design have been developed over the …

Strongly-confined colloidal lead-halide perovskite quantum dots: from synthesis to applications

J Ye, D Gaur, C Mi, Z Chen, IL Fernández… - Chemical Society …, 2024‏ - pubs.rsc.org
Colloidal semiconductor nanocrystals enable the realization and exploitation of quantum
phenomena in a controlled manner, and can be scaled up for commercial uses. These …

Quantifying the advantage of domain-specific pre-training on named entity recognition tasks in materials science

A Trewartha, N Walker, H Huo, S Lee, K Cruse… - Patterns, 2022‏ - cell.com
A bottleneck in efficiently connecting new materials discoveries to established literature has
arisen due to an increase in publications. This problem may be addressed by using named …

[PDF][PDF] An all-round AI-Chemist with a scientific mind

Q Zhu, F Zhang, Y Huang, H **ao… - National Science …, 2022‏ - academic.oup.com
The realization of automated chemical experiments by robots unveiled the prelude to an
artificial intelligence (AI) laboratory. Several AI-based systems or robots with specific …