Computational discovery of transition-metal complexes: from high-throughput screening to machine learning
Transition-metal complexes are attractive targets for the design of catalysts and functional
materials. The behavior of the metal–organic bond, while very tunable for achieving target …
materials. The behavior of the metal–organic bond, while very tunable for achieving target …
Picking the lock of coordination cage catalysis
The design principles of metallo-organic assembly reactions have facilitated access to
hundreds of coordination cages of varying size and shape. Many of these assemblies …
hundreds of coordination cages of varying size and shape. Many of these assemblies …
Predictive chemistry: machine learning for reaction deployment, reaction development, and reaction discovery
The field of predictive chemistry relates to the development of models able to describe how
molecules interact and react. It encompasses the long-standing task of computer-aided …
molecules interact and react. It encompasses the long-standing task of computer-aided …
Exploiting attractive non-covalent interactions for the enantioselective catalysis of reactions involving radical intermediates
RSJ Proctor, AC Colgan, RJ Phipps - Nature Chemistry, 2020 - nature.com
The past decade has seen unprecedented growth in the development of new chemical
methods that proceed by mechanisms involving radical intermediates. This new attention …
methods that proceed by mechanisms involving radical intermediates. This new attention …
Deep learning for deep chemistry: optimizing the prediction of chemical patterns
Computational Chemistry is currently a synergistic assembly between ab initio calculations,
simulation, machine learning (ML) and optimization strategies for describing, solving and …
simulation, machine learning (ML) and optimization strategies for describing, solving and …
Machine learning-driven catalyst design, synthesis and performance prediction for CO2 hydrogenation
Atmospheric concentrations of CO 2 must be lowered to mitigate climate change and rising
global temperatures. CO 2 utilization is the most promising approach for the sustainable …
global temperatures. CO 2 utilization is the most promising approach for the sustainable …
Automated in silico design of homogeneous catalysts
M Foscato, VR Jensen - ACS catalysis, 2020 - ACS Publications
Catalyst discovery is increasingly relying on computational chemistry, and many of the
computational tools are currently being automated. The state of this automation and the …
computational tools are currently being automated. The state of this automation and the …
Exploring paths of chemical transformations in molecular and periodic systems: An approach utilizing force
S Maeda, Y Harabuchi - Wiley Interdisciplinary Reviews …, 2021 - Wiley Online Library
This article provides an overview on an automated reaction path search method called
artificial force induced reaction (AFIR). The AFIR method induces various chemical …
artificial force induced reaction (AFIR). The AFIR method induces various chemical …
Quantitative structure–selectivity relationships in enantioselective catalysis: past, present, and future
AF Zahrt, SV Athavale, SE Denmark - Chemical reviews, 2019 - ACS Publications
The dawn of the 21st century has brought with it a surge of research related to computer-
guided approaches to catalyst design. In the past two decades, chemoinformatics, the …
guided approaches to catalyst design. In the past two decades, chemoinformatics, the …
Data-driven design of new chiral carboxylic acid for construction of indoles with C-central and C–N axial chirality via cobalt catalysis
Challenging enantio-and diastereoselective cobalt-catalyzed C–H alkylation has been
realized by an innovative data-driven knowledge transfer strategy. Harnessing the statistics …
realized by an innovative data-driven knowledge transfer strategy. Harnessing the statistics …