Dataset design for building models of chemical reactivity
Models can codify our understanding of chemical reactivity and serve a useful purpose in
the development of new synthetic processes via, for example, evaluating hypothetical …
the development of new synthetic processes via, for example, evaluating hypothetical …
Computational methods for asymmetric catalysis
Impressive progress in computational asymmetric catalysis has been made in the past
twenty years owing to advancements in algorithm and method development for predicting …
twenty years owing to advancements in algorithm and method development for predicting …
A data-driven workflow for assigning and predicting generality in asymmetric catalysis
The development of chiral catalysts that can provide high enantioselectivities across a wide
assortment of substrates or reaction range is a priority for many catalyst design efforts. While …
assortment of substrates or reaction range is a priority for many catalyst design efforts. While …
AI for organic and polymer synthesis
Recent years have witnessed the transformative impact from the integration of artificial
intelligence with organic and polymer synthesis. This synergy offers innovative and …
intelligence with organic and polymer synthesis. This synergy offers innovative and …
Towards a comprehensive data infrastructure for redox-active organic molecules targeting non-aqueous redox flow batteries
The shift of energy production towards renewable, yet at times inconsistent, resources like
solar and wind have increased the need for better energy storage solutions. An emerging …
solar and wind have increased the need for better energy storage solutions. An emerging …
Classification of hemilabile ligands using machine learning
Hemilabile ligands have the capacity to partially disengage from a metal center, providing a
strategy to balance stability and reactivity in catalysis, but they are not straightforward to …
strategy to balance stability and reactivity in catalysis, but they are not straightforward to …
A genetic optimization strategy with generality in asymmetric organocatalysis as a primary target
A catalyst possessing a broad substrate scope, in terms of both turnover and
enantioselectivity, is sometimes called “general”. Despite their great utility in asymmetric …
enantioselectivity, is sometimes called “general”. Despite their great utility in asymmetric …
COMPAS-2: a dataset of cata-condensed hetero-polycyclic aromatic systems
Polycyclic aromatic systems are highly important to numerous applications, in particular to
organic electronics and optoelectronics. High-throughput screening and generative models …
organic electronics and optoelectronics. High-throughput screening and generative models …
Leveraging chemistry foundation models to facilitate structure focused retrieval augmented generation in multi-agent workflows for catalyst and materials design
Molecular property prediction and generative design via deep learning models has been the
subject of intense research given its potential to accelerate development of new, high …
subject of intense research given its potential to accelerate development of new, high …
Combining molecular quantum mechanical modeling and machine learning for accelerated reaction screening and discovery
Molecular quantum mechanical modeling, accelerated by machine learning, has opened the
door to high‐throughput screening campaigns of complex properties, such as the activation …
door to high‐throughput screening campaigns of complex properties, such as the activation …