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Matthew L. Mendonca

Researcher at Northwestern University

Publications -  8
Citations -  815

Matthew L. Mendonca is an academic researcher from Northwestern University. The author has contributed to research in topics: Catalysis & Surface plasmon resonance. The author has an hindex of 7, co-authored 8 publications receiving 620 citations. Previous affiliations of Matthew L. Mendonca include College of William & Mary.

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Metal–organic frameworks for the removal of toxic industrial chemicals and chemical warfare agents

TL;DR: This paper reviews recent experimental and computational work pertaining to the capture of several industrially-relevant toxic chemicals, including NH3, SO2, NO2, H2S, and some volatile organic compounds, with particular emphasis on the challenging issue of designing materials that selectively adsorb these chemicals in the presence of water.
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Insights into Catalytic Hydrolysis of Organophosphate Warfare Agents by Metal–Organic Framework NU-1000

TL;DR: In this article, the authors adopt density functional theory calculations to study the catalytic effects of metal-organic frameworks (MOFs) on the CWA simulant methylparaoxon on the Zr-based MOF NU-1000.
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Computational Screening of Metal–Organic Framework-Supported Single-Atom Transition-Metal Catalysts for the Gas-Phase Hydrolysis of Nerve Agents

TL;DR: In this paper, the authors used density functional theory to perform a comprehensive screening of single-atom transition-metal catalysts, in varying oxidation states, deposited on NU-1000 nodes for the gas-phase hydrolysis of the nerve agent sarin.
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Elucidating the mechanism of the UiO-66-catalyzed sulfide oxidation: activity and selectivity enhancements through changes in the node coordination environment and solvent

TL;DR: In this paper, the authors show that the labile Zr-μ1-OH groups on these open sites are likely converted into Zr6-oxo-hydroxo species that are active in oxidizing the sulfide as well as its sulfoxide product.
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Screening for Improved Nerve Agent Simulants and Insights into Organophosphate Hydrolysis Reactions from DFT and QSAR Modeling

TL;DR: Density functional theory calculations were performed to identify improved simulants for the G-series nerve agents soman and sarin, based on low toxicity and similarity to nerve agent hydrolysis energetics and degradation mechanism, and it was shown that the model trained on G- series agents can reliably predict ener getics for other organophosphate classes as well, including VX.