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Mechanistic Insights Into Substrate Positioning Across Non-heme Fe(II)/Alpha-Ketoglutarate-Dependent Halogenases and Hydroxylases
Non-heme iron halogenases and hydroxylases activate inert C-H bonds to selectively catalyze the functionalization of a diversity of …
PDF Cite DOI ChemRxiv
Mechanistic Insights Into Substrate Positioning Across Non-heme Fe(II)/Alpha-Ketoglutarate-Dependent Halogenases and Hydroxylases
A Transferable Recommender Approach for Selecting the Best Density Functional Approximations in Chemical Discovery
Approximate density functional theory (DFT) has become indispensable owing to its cost-accuracy trade-off in comparison to more …
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A Transferable Recommender Approach for Selecting the Best Density Functional Approximations in Chemical Discovery
Insights into the deviation from piecewise linearity in transition metal complexes from supervised machine learning models
Virtual high-throughput screening (VHTS) and machine learning (ML) with density functional theory (DFT) suffer from inaccuracies from …
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Insights into the deviation from piecewise linearity in transition metal complexes from supervised machine learning models
Remolding and Deconstruction of Industrial Thermosets via Carboxylic Acid-Catalyzed Bifunctional Silyl Ether Exchange
Convenient strategies for the deconstruction and reprocessing of thermosets could improve the circularity of these materials, but most …
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Remolding and Deconstruction of Industrial Thermosets via Carboxylic Acid-Catalyzed Bifunctional Silyl Ether Exchange
DFT-based Multireference Diagnostics in the Solid State: Application to Metal-organic Frameworks
When a many-body wave function of a system deviates far from a single reference determinant, high-level multireference methods are …
PDF Cite DOI ChemRxiv
DFT-based Multireference Diagnostics in the Solid State: Application to Metal-organic Frameworks
Low-cost machine learning prediction of excited state properties of iridium-centered phosphors
Prediction of the properties of excited states of photoactive iridium complexes challenges ab initio methods such as time-dependent …
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Low-cost machine learning prediction of excited state properties of iridium-centered phosphors
Active Learning Exploration of Transition Metal Complexes to Discover Method-Insensitive and Synthetically Accessible Chromophores
Transition metal chromophores with earth-abundant transition metals are an important design target for their applications in lighting …
PDF Cite DOI arXiv
Active Learning Exploration of Transition Metal Complexes to Discover Method-Insensitive and Synthetically Accessible Chromophores
Effects of MOF Linker Rotation and Functionalization on Methane Uptake and Diffusion
The flexible degrees of freedom in metal–organic frameworks (MOFs) can have significant effects on guest molecule behavior. However, in …
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Effects of MOF Linker Rotation and Functionalization on Methane Uptake and Diffusion
Fluids and Electrolytes under Confinement in Single-Digit Nanopores
Confined fluids and electrolytes in nanopores exhibit rich and surprising physics and chemistry that impact the mass transport and …
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Fluids and Electrolytes under Confinement in Single-Digit Nanopores
Light Emission in 2D Silver Phenylchalcogenolates
Silver phenylselenolate (AgSePh, also known as “mithrene”) and silver phenyltellurolate (AgTePh, also known as …
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Light Emission in 2D Silver Phenylchalcogenolates