Evidence map›Paper›PMID 40959779›Full record

ArticleThe journal of physical chemistry. C, Nanomaterials and interfaces2025

ECE vs DISP Mechanisms in Anodic Electrolysis of Benzyl Alcohols: Computational Prediction of Microscopic Rate Constants.

John H Hymel, Jesse G McDaniel

Abstract read
In one paragraph

Article in The journal of physical chemistry. C, Nanomaterials and interfaces, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

2 authors.

John H HymelSchool of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, United States.ORCID https://orcid.org/0000-0002-4917-7865
Jesse G McDanielSchool of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia 30332-0400, United States.ORCID https://orcid.org/0000-0002-9211-1108

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The heterogeneous nature of electrochemical reactions entails unique kinetic control of product yield/selectivity as compared with corresponding homogeneous oxidation/reduction reactions. In direct electrolysis, subsequent elementary steps following the initiating electron transfer may also occur heterogeneously at the electrode surface or homogeneously within the bulk electrolyte, often via a disproportionation step for secondary electron transfer; kinetic control of this branching may have important consequences for product selectivity/yield, due to differences in lifetimes of reactive radical intermediates. In this work, we use computer simulations to predict microscopic rate constants governing the heterogeneous "ECE" electrochemical oxidation of para-methoxybenzyl alcohol to its corresponding aldehyde at a working carbon anode within an aqueous electrolyte. Molecular dynamics simulations are conducted to model the full electrochemical cell at atomistic resolution under conditions approximating controlled potential electrolysis, from which rate constants are predicted via a combination of direct dynamics and free energy sampling methods. Density functional theory-based quantum mechanics/molecular mechanics (DFT-QM/MM) simulations are performed to predict free energy barriers for deprotonation of the cation radical intermediate within the electrical double layer environment. We demonstrate how strong solvophobic forces lead to residence times of ten(s) of nanoseconds for the electrogenerated cation radical intermediates to reside within the anodic double layer, and the relative deprotonation rate is a key factor dictating the heterogeneous vs homogeneous reaction branching. We predict a compelling double-layer modulation for the cation radical deprotonation rate with NaOAc aqueous electrolyte, arising from a combination of preformed "encounter pairs" via ionic interactions and reduction in activation barrier via stereoelectronic effects. Our computational study of this prototypical electrolysis reaction illustrates the substantial role of reaction conditions (solvent, electrolyte, and overpotential) on the microscopic rate constants that kinetically control the reaction pathway/outcome.

Identifiers

PMID40959779
PMCPMC12434723

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.