ArticleNature communications2024
Molecular-scale insights into the electrical double layer at oxide-electrolyte interfaces.
Article in Nature communications, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed.
- Developing adsorption regulated energy storage interface for nanostructured ceramic composites.Discover nano · 2026Review
- Discriminating Between Living and Dead Bacteria With a Field-Effect Transistor Based on Nano-Channels.Small (Weinheim an der Bergstrasse, Germany) · 2026Article
- Electric Field-Empowered Nanozymes: From Passive Adaptation to Active Precision Therapy.Advanced materials (Deerfield Beach, Fla.) · 2026Review
- Understanding Adsorption and Reactions at Aqueous Oxide Interfaces with Neural Network Potential Molecular Dynamics.Accounts of materials research · 2026Article
- A hydrogel-based iontronic-reservoir-enabled neuromorphic prosthetic system.Nature materials · 2026Article
- Ion Distribution and Cation Exchange at Mica-Electrolyte Interfaces Probed with Deep Potential Molecular Dynamics.Chemistry of materials : a publication of the American Chemical Society · 2026Article
- The Role of Local pH in Electrocatalysis: Measurement, Impact, and Control Strategies.ACS electrochemistry · 2026Review
- Methodological Frameworks for Computational Electrocatalysis: From Theory to Practice.Small methods · 2026Review
- Multiscale Theoretical Calculations Empower Robust Electric Double Layer Toward Highly Reversible Zinc Anode.Nano-micro letters · 2025Article
- Modeling the potential energy surface by force fields for heterogeneous catalysis: classification, applications, and challenges.Chemical science · 2025Review
- All-Atomic Computational Perspectives for Understanding Morphable Electric Double Layers: A Review.Small (Weinheim an der Bergstrasse, Germany) · 2025Review
- Machine learning of charges and long-range interactions from energies and forces.Nature communications · 2025Article
- Tuning water dissociation at oxide-electrolyte interfaces with electric fields.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Article
- Molecular-scale insights into the electrical double layer at oxide-electrolyte interfaces.Nature communications · 2024Article
- Machine learning demonstrates the impact of proton transfer and solvent dynamics on COChemical science · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
The electrical double layer (EDL) at metal oxide-electrolyte interfaces critically affects fundamental processes in water splitting, batteries, and corrosion. However, limitations in the microscopic-level understanding of the EDL have been a major bottleneck in controlling these interfacial processes. Herein, we use ab initio-based machine learning potential simulations incorporating long-range electrostatics to unravel the molecular-scale picture of the EDL at the prototypical anatase TiO
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.