Autonomous chemical experiments: Challenges and perspectives on establishing a self-driving lab

M Seifrid, R Pollice, A Aguilar-Granda… - Accounts of Chemical …, 2022 - ACS Publications
Conspectus We must accelerate the pace at which we make technological advancements to
address climate change and disease risks worldwide. This swifter pace of discovery requires …

The evolution of data-driven modeling in organic chemistry

WL Williams, L Zeng, T Gensch, MS Sigman… - ACS central …, 2021 - ACS Publications
Organic chemistry is replete with complex relationships: for example, how a reactant's
structure relates to the resulting product formed; how reaction conditions relate to yield; how …

Material evolution with nanotechnology, nanoarchitectonics, and materials informatics: what will be the next paradigm shift in nanoporous materials?

W Chaikittisilp, Y Yamauchi, K Ariga - Advanced Materials, 2022 - Wiley Online Library
Materials science and chemistry have played a central and significant role in advancing
society. With the shift toward sustainable living, it is anticipated that the development of …

Organic reaction mechanism classification using machine learning

J Burés, I Larrosa - Nature, 2023 - nature.com
A mechanistic understanding of catalytic organic reactions is crucial for the design of new
catalysts, modes of reactivity and the development of greener and more sustainable …

Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation

Y Xie, K Sattari, C Zhang, J Lin - Progress in Materials Science, 2023 - Elsevier
The ever-increasing demand for novel materials with superior properties inspires retrofitting
traditional research paradigms in the era of artificial intelligence and automation. An …

Data science meets physical organic chemistry

JM Crawford, C Kingston, FD Toste… - Accounts of chemical …, 2021 - ACS Publications
Conspectus At the heart of synthetic chemistry is the holy grail of predictable catalyst design.
In particular, researchers involved in reaction development in asymmetric catalysis have …

The case for data science in experimental chemistry: examples and recommendations

J Yano, KJ Gaffney, J Gregoire, L Hung… - Nature Reviews …, 2022 - nature.com
The physical sciences community is increasingly taking advantage of the possibilities
offered by modern data science to solve problems in experimental chemistry and potentially …

Machine learning for design principles for single atom catalysts towards electrochemical reactions

M Tamtaji, H Gao, MD Hossain, PR Galligan… - Journal of Materials …, 2022 - pubs.rsc.org
Machine learning (ML) integrated density functional theory (DFT) calculations have recently
been used to accelerate the design and discovery of heterogeneous catalysts such as single …

[HTML][HTML] Artificial intelligence in pharmaceutical sciences

M Lu, J Yin, Q Zhu, G Lin, M Mou, F Liu, Z Pan, N You… - Engineering, 2023 - Elsevier
Drug discovery and development affects various aspects of human health and dramatically
impacts the pharmaceutical market. However, investments in a new drug often go …

Autonomous optimization of an organic solar cell in a 4-dimensional parameter space

T Osterrieder, F Schmitt, L Lüer, J Wagner… - Energy & …, 2023 - pubs.rsc.org
Optimizing solution-processed organic solar cells is a complex and challenging task due to
the vast parameter space in organic photovoltaics (OPV). Classical Edisonian or one …