Evidence map›Paper›PMID 39946686›Full record

ArticleJournal of chemical theory and computation2025

Structure and Dynamics of the Magnetite(001)/Water Interface from Molecular Dynamics Simulations Based on a Neural Network Potential.

Salvatore Romano, Pablo Montero de Hijes, Matthias Meier, Georg Kresse, Cesare Franchini, Christoph Dellago

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Article in Journal of chemical theory and computation, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

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0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Review
  2. Review
  3. Fenton-like Reactivity on FeSmall (Weinheim an der Bergstrasse, Germany) · 2026
    Article
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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

6 authors.

Salvatore RomanoFaculty of Physics, University of Vienna, Kolingasse 14-16, 1090 Vienna, Austria.ORCID 0000-0002-9762-9125
Pablo Montero de HijesFaculty of Physics, University of Vienna, Kolingasse 14-16, 1090 Vienna, Austria.ORCID 0000-0001-8873-8445
Matthias MeierFaculty of Physics, University of Vienna, Kolingasse 14-16, 1090 Vienna, Austria.ORCID 0000-0003-0198-1392
Georg KresseFaculty of Physics, University of Vienna, Kolingasse 14-16, 1090 Vienna, Austria.ORCID 0000-0001-9102-4259
Cesare FranchiniFaculty of Physics, University of Vienna, Kolingasse 14-16, 1090 Vienna, Austria.ORCID 0000-0002-7990-2984
Christoph DellagoFaculty of Physics, University of Vienna, Kolingasse 14-16, 1090 Vienna, Austria.ORCID 0000-0001-9166-6235

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The magnetite/water interface is commonly found in nature and plays a crucial role in various technological applications. However, our understanding of its structural and dynamical properties at the molecular scale remains still limited. In this study, we developed an efficient Behler-Parrinello neural network potential (NNP) for the magnetite/water system, paying particular attention to the accurate generation of reference data with density functional theory. Using this NNP, we performed extensive molecular dynamics simulations of the magnetite (001) surface across a wide range of water coverages, from single molecules to bulk water. Our simulations revealed several new ground states of low coverage water on the Subsurface Cation Vacancy (SCV) model and yielded a density profile of water at the surface that exhibits marked layering. By calculating mean square displacements, we obtained quantitative information on the diffusion of water molecules on the SCV for different coverages, revealing significant anisotropy. Additionally, our simulations provided qualitative insights into the dissociation mechanisms of water molecules at the surface.

Identifiers

PMID39946686
PMCPMC11866917

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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.