Juan Santiago Grassano
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View article: Fenton‐like Reactivity on Fe <sub>3</sub> O <sub>4</sub> Nanozymes Driven by Charge Transfer and Interfacial Water
Fenton‐like Reactivity on Fe <sub>3</sub> O <sub>4</sub> Nanozymes Driven by Charge Transfer and Interfacial Water Open
Magnetite (Fe 3 O 4 ) nanoparticles, widely recognized as inorganic nanozymes due to their enzyme‐like catalytic activity, are emerging as effective heterogeneous catalysts for Fenton‐like reactions, in which lattice iron activates hydroge…
View article: Fenton‐like Reactivity on Fe <sub>3</sub> O <sub>4</sub> Nanozymes Driven by Charge Transfer and Interfacial Water
Fenton‐like Reactivity on Fe <sub>3</sub> O <sub>4</sub> Nanozymes Driven by Charge Transfer and Interfacial Water Open
Magnetite (Fe 3 O 4 ) nanoparticles, widely recognized as inorganic nanozymes due to their enzyme‐like catalytic activity, are emerging as effective heterogeneous catalysts for Fenton‐like reactions, in which lattice iron activates hydroge…
View article: From QM/MM to ML/MM: A new era in multiscale modeling
From QM/MM to ML/MM: A new era in multiscale modeling Open
Hybrid machine-learning/molecular-mechanics (ML/MM) methods extend the classical QM/MM paradigm by replacing the quantum description with neural network interatomic potentials trained to reproduce accurately quantum-mechanical (QM) results…
View article: From QM/MM to ML/MM: A new era in multiscale modeling
From QM/MM to ML/MM: A new era in multiscale modeling Open
Hybrid machine-learning/molecular-mechanics (ML/MM) methods extend the classical QM/MM paradigm by replacing the quantum description with neural network interatomic potentials trained to reproduce accurately quantum-mechanical (QM) results…
View article: Advancing Multiscale Molecular Modeling with Machine Learning-Derived Electrostatics
Advancing Multiscale Molecular Modeling with Machine Learning-Derived Electrostatics Open
We introduce an innovative machine learning (ML)-based framework for multiscale molecular modeling, in which the ML subsystem is treated as an electrostatic entity interacting with its molecular mechanics (MM) environment through classical…
View article: Advancing Multiscale Molecular Modeling with Machine Learning-Derived Electrostatics
Advancing Multiscale Molecular Modeling with Machine Learning-Derived Electrostatics Open
We introduce an innovative machine learning (ML)-based framework for multiscale molecular modeling, in which the ML subsystem is treated as an electrostatic entity interacting with its molecular mechanics (MM) environment through classical…
View article: ANI Neural Networks Meet Electrostatics: A ML/MM Implementation in Amber
ANI Neural Networks Meet Electrostatics: A ML/MM Implementation in Amber Open
We present a novel integration of the ANI neural networks into the Amber software suite, offering a sophisticated machine learning/molecular mechanics (ML/MM) framework. The implementation is designed as a general-purpose tool for the simu…
View article: ANI-aa-qmmm Data set
ANI-aa-qmmm Data set Open
This data set was constructed for our work entitled "Assessment of embedding schemes in a hybrid machine learning/classical potentials (ML/MM) approach" to provide an unbiased insight into the performance of different atomic partial charge…
View article: Assessment of embedding schemes in a hybrid machine learning/classical potentials (ML/MM) scheme
Assessment of embedding schemes in a hybrid machine learning/classical potentials (ML/MM) scheme Open
Machine Learning (ML) methods have reached high accuracy levels for the prediction of in vacuo molecular properties. However, the simulation of large systems through solely ML methods (like those based on neural network potentials) is stil…
View article: Acidity and nucleophilic reactivity of glutathione persulfide
Acidity and nucleophilic reactivity of glutathione persulfide Open
Persulfides (RSSH/RSS-) participate in sulfur trafficking and metabolic processes, and are proposed to mediate the signaling effects of hydrogen sulfide (H2S). Despite their growing relevance, their chemical propertie…