Autonomous chemical experiments: Challenges and perspectives on establishing a self-driving lab
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 …
address climate change and disease risks worldwide. This swifter pace of discovery requires …
The evolution of data-driven modeling in organic chemistry
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 …
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?
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 …
society. With the shift toward sustainable living, it is anticipated that the development of …
Organic reaction mechanism classification using machine learning
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 …
catalysts, modes of reactivity and the development of greener and more sustainable …
Toward autonomous laboratories: Convergence of artificial intelligence and experimental automation
The ever-increasing demand for novel materials with superior properties inspires retrofitting
traditional research paradigms in the era of artificial intelligence and automation. An …
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 …
In particular, researchers involved in reaction development in asymmetric catalysis have …
The case for data science in experimental chemistry: examples and recommendations
The physical sciences community is increasingly taking advantage of the possibilities
offered by modern data science to solve problems in experimental chemistry and potentially …
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
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 …
been used to accelerate the design and discovery of heterogeneous catalysts such as single …
[HTML][HTML] Artificial intelligence in pharmaceutical sciences
Drug discovery and development affects various aspects of human health and dramatically
impacts the pharmaceutical market. However, investments in a new drug often go …
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 …
the vast parameter space in organic photovoltaics (OPV). Classical Edisonian or one …