ArticleChemical science2023
Neural network potentials for accelerated metadynamics of oxygen reduction kinetics at Au-water interfaces.
Article in Chemical science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed.
- Efficient Parallelization of Message Passing Neural Network Potentials for Large-Scale Molecular Dynamics.JACS Au · 2026Article
- A Stereoscopic Perspective on the Triple-Phase Interface Microenvironment in Electrochemical CONano-micro letters · 2026Article
- Reactive Machine Learning Interatomic Potentials for Chemistry and Materials Science.Chemical reviews · 2026Review
- Accelerating Catalyst Materials Discovery With Large Artificial Intelligence Models.Angewandte Chemie (International ed. in English) · 2026Review
- Optimizing cross-domain transfer for universal machine learning interatomic potentials.Nature communications · 2026Article
- Article
- Active learning meets metadynamics: automated workflow for reactive machine learning interatomic potentials.Digital discovery · 2026Article
- Electrochemical potential-driven water dynamics control CONature communications · 2025Article
- All-Atomic Computational Perspectives for Understanding Morphable Electric Double Layers: A Review.Small (Weinheim an der Bergstrasse, Germany) · 2025Review
- Dataset exploring the atomic scale structure and ionic dynamics of polyanion sodium cathode materials.Scientific data · 2025Article
- Data Generation for Machine Learning Interatomic Potentials and Beyond.Chemical reviews · 2024Review
- Capturing Dichotomic Solvent Behavior in Solute-Solvent Reactions with Neural Network Potentials.Journal of chemical theory and computation · 2024Article
- Leveraging Machine Learning Potentials for In-Situ Searching of Active sites in Heterogeneous Catalysis.Precision chemistry · 2024Review
- Challenges for Kinetics Predictions via Neural Network Potentials: A Wilkinson's Catalyst Case.Molecules (Basel, Switzerland) · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The application of
Identifiers
What OpenQuestion holds
Registered trials
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.