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Accelerating Chemical Discovery with Machine Learning: Simulated Evolution of Spin Crossover Complexes with an Artificial Neural Network
Machine learning (ML) has emerged as a powerful complement to simulation for materials discovery by reducing time for evaluation of …
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Accelerating Chemical Discovery with Machine Learning: Simulated Evolution of Spin Crossover Complexes with an Artificial Neural Network
Understanding and Breaking Scaling Relations in Single-Site Catalysis: Methane to Methanol Conversion by FeIV═O
Computational high-throughput screening is an essential tool for catalyst design, limited primarily by the efficiency with which …
PDF Cite DOI ChemRxiv
Understanding and Breaking Scaling Relations in Single-Site Catalysis: Methane to Methanol Conversion by FeIV═O
Where Does the Density Localize in the Solid State? Divergent Behavior for Hybrids and DFT+U
Approximate density functional theory (DFT) is widely used in chemistry and physics, despite delocalization errors that affect …
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Where Does the Density Localize in the Solid State? Divergent Behavior for Hybrids and DFT+U
Large-scale QM/MM free energy simulations of enzyme catalysis reveal the influence of charge transfer
Hybrid quantum mechanical–molecular mechanical (QM/MM) simulations provide key insights into enzyme structure–function relationships. …
PDF Cite DOI ChemRxiv
Large-scale QM/MM free energy simulations of enzyme catalysis reveal the influence of charge transfer
Communication: Recovering the flat-plane condition in electronic structure theory at semi-local DFT cost
The flat-plane condition is the union of two exact constraints in electronic structure theory: (i) energetic piecewise linearity with …
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Communication: Recovering the flat-plane condition in electronic structure theory at semi-local DFT cost
Quantifying Electronic Effects in QM and QM/MM Biomolecular Modeling with the Fukui Function
Multi-scale quantum-mechanical/molecular-mechanical (QM/MM) and large-scale QM simulation provide valuable insight into enzyme …
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Quantifying Electronic Effects in QM and QM/MM Biomolecular Modeling with the Fukui Function
Resolving Transition Metal Chemical Space: Feature Selection for Machine Learning and Structure–Property Relationships
Machine learning (ML) of quantum mechanical properties shows promise for accelerating chemical discovery. For transition metal …
PDF Cite DOI arXiv
Resolving Transition Metal Chemical Space: Feature Selection for Machine Learning and Structure–Property Relationships
Unifying Exchange Sensitivity in Transition-Metal Spin-State Ordering and Catalysis through Bond Valence Metrics
Accurate predictions of spin-state ordering, reaction energetics, and barrier heights are critical for the computational discovery of …
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Unifying Exchange Sensitivity in Transition-Metal Spin-State Ordering and Catalysis through Bond Valence Metrics
Leveraging Cheminformatics Strategies for Inorganic Discovery: Application to Redox Potential Design
Virtual high throughput screening, typically driven by first-principles, density functional theory calculations, has emerged as a …
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Leveraging Cheminformatics Strategies for Inorganic Discovery: Application to Redox Potential Design
Density functional theory for modelling large molecular adsorbate–surface interactions: a mini-review and worked example
First-principles simulation has played an ever-increasing role in the discovery and interpretation of the chemical properties of …
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Density functional theory for modelling large molecular adsorbate–surface interactions: a mini-review and worked example