2022
DOI: 10.1021/jacs.2c03099
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Acids at the Edge: Why Nitric and Formic Acid Dissociations at Air–Water Interfaces Depend on Depth and on Interface Specific Area

Abstract: Whether the air-water interface weakens or strengthens the acidity of simple organic and inorganic acids compared to the bulk has a critical importance in a broad range of environmental and biochemical processes. However, consensus has not yet been achieved on this key question. Here we use machine learning-based reactive molecular dynamics simulations to study the dissociation of the paradigmatic nitric and formic acids at the air-water interface. We show that the local acidity profile across the interface is… Show more

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Cited by 47 publications
(52 citation statements)
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“…In fact, there have been tremendous reports that chemical and photochemical reactions are dramatically accelerated when they occur at aqueous interfaces, in comparison to when the same reactions occur in the gas phase or bulk water. This phenomenon is designated as “on-water” catalysis. Several enthalpic or entropic solvation effects, such as dangling OH groups and surface electrostatic potentials, may cause transition-state stabilization and reaction acceleration.…”
Section: Resultsmentioning
confidence: 99%
“…In fact, there have been tremendous reports that chemical and photochemical reactions are dramatically accelerated when they occur at aqueous interfaces, in comparison to when the same reactions occur in the gas phase or bulk water. This phenomenon is designated as “on-water” catalysis. Several enthalpic or entropic solvation effects, such as dangling OH groups and surface electrostatic potentials, may cause transition-state stabilization and reaction acceleration.…”
Section: Resultsmentioning
confidence: 99%
“…93 Recently, Puente et al applied molecular dynamics simulation based on machine learning to investigate the dissociation of paradigmatic formic and nitric acids at water interfaces. 94 Machine learning may help us to study SFVS of methanol at interfaces.…”
Section: Resultsmentioning
confidence: 99%
“…An early study suggests that approximately nanosecond level simulation is long enough to produce the precise free-profile. 20 Our test simulations indicated that the error caused by four initial configurations is very small (<0.4 kcal•mol −1 , Figure S4). Gibbs-freeenergy change between separated reactants and the corresponding transition state (ΔG TS-SR ) was calculated by subtracting Gibbs-freeenergy at the transition state and the separated reactants.…”
Section: ■ Methodsmentioning
confidence: 99%
“…Despite difficulties in measuring interface phenomena experimentally, 17 recent advances in machine learning make it possible to simulate interfacial reactions. 19,20 In this study, a reactive machine-learning force field (MLFF) that can reach density-functional-theory-level quality with a significant decrease in computational costs was trained based on ab initio data selected from ca. 2,000,000 configurations via an on-the- fly algorithm.…”
Section: ■ Introductionmentioning
confidence: 99%