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Advancing Discovery in Chemistry with Artificial Intelligence: From Reaction Outcomes to New Materials and Catalysts
Scientists have long benefitted from and contributed to the development of quantitative methods to reveal patterns in …
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Molecular DFT+U: A Transferable, Low-Cost Approach to Eliminate Delocalization Error
While density functional theory (DFT) is widely applied for its combination of cost and accuracy, corrections (e.g., DFT+U) that …
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Molecular DFT+U: A Transferable, Low-Cost Approach to Eliminate Delocalization Error
Protein Dynamics and Substrate Protonation State Mediate the Catalytic Action of Trans-4-Hydroxy-L-Proline Dehydratase
The enzyme trans-4-Hydroxy-L-proline (Hyp) dehydratase (HypD) is among the most abundant glycyl radical enzymes (GREs) in the healthy …
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Protein Dynamics and Substrate Protonation State Mediate the Catalytic Action of Trans-4-Hydroxy-L-Proline Dehydratase
Molecular basis of C-S bond cleavage in the glycyl radical enzyme isethionate sulfite-lyase
Desulfonation of isethionate by the bacterial glycyl radical enzyme (GRE) isethionate sulfite-lyase (IslA) generates sulfite, a …
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Molecular basis of C-S bond cleavage in the glycyl radical enzyme isethionate sulfite-lyase
Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design
The variability of chemical bonding in open-shell transition-metal complexes not only motivates their study as functional materials and …
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Navigating Transition-Metal Chemical Space: Artificial Intelligence for First-Principles Design
Biochemical and crystallographic investigations into isonitrile formation by a nonheme iron-dependent oxidase/decarboxylase
The isonitrile moiety is found in marine sponges and some microbes, where it plays a role in processes such as virulence and metal …
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Biochemical and crystallographic investigations into isonitrile formation by a nonheme iron-dependent oxidase/decarboxylase
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 …
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Computational Discovery of Transition-Metal Complexes: From High-throughput Screening to Machine Learning
Deciphering Cryptic Behavior in Bimetallic Transition Metal Complexes with Machine Learning
We demonstrate an alternative, data-driven approach to uncovering structure–property relationships for the rational design of …
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Deciphering Cryptic Behavior in Bimetallic Transition Metal Complexes with Machine Learning
Machine learning to tame divergent density functional approximations a new path to consensus materials design principles
Virtual high-throughput screening (VHTS) with density functional theory (DFT) and machine-learning (ML)-acceleration is essential in …
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Machine learning to tame divergent density functional approximations a new path to consensus materials design principles
Mapping the Origins of Surface- and Chemistry-Dependent Doping Trends in III-V Quantum Dots with Density Functional Theory
Modifying the optoelectronic properties of nanostructured materials through the introduction of dopant atoms has attracted intense …
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Mapping the Origins of Surface- and Chemistry-Dependent Doping Trends in III-V Quantum Dots with Density Functional Theory