ArticleACS central science2023
Human-Machine Collaboration for Accelerated Discovery of Promising Oxygen Evolution Electrocatalysts with On-Demand Elements.
Article in ACS central science, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed.
- Rare Earth-Modified Electrocatalysts for Water Splitting: Material Design, Synthetic Strategies and Mechanistic Insight.Small methods · 2026Review
- Accelerated Discovery-to-Unveiling of High-Performance and Affordable Ammonia Electrode Process by Human-Machine Collaboration Framework.Angewandte Chemie (International ed. in English) · 2026Article
- Interpretable data-driven discovery of high-performance multielement metal oxide electrocatalysts for oxygen evolution reaction from a small hybrid dataset.Science and technology of advanced materials · 2026Article
- Machine-Learning-Guided Design of Nanostructured Metal Oxide Photoanodes for Photoelectrochemical Water Splitting: From Material Discovery to Performance Optimization.Nanomaterials (Basel, Switzerland) · 2025Review
- Data-Driven Approach Considering Imbalance in Data Sets and Experimental Conditions for Exploration of Photocatalysts.ACS omega · 2025Article
- Guided electrocatalyst design through in-situ techniques and data mining approaches.Nano convergence · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A drastically efficient method for identifying electrocatalysts with desirable functionality is a pressing necessity for making a breakthrough in advanced water-electrolyzers toward large-scale green hydrogen production and addressing the significant challenge of carbon neutrality. Despite extensive investigations over the last several centuries, it remains a time-consuming task to identify even one promising affordable electrocatalyst without platinum-group-metal (PGM) for one electrochemical reaction due to its great complexities, particularly for the key anode reaction in the water-electrolyzer of the oxygen evolution reaction (OER). In this study, we demonstrate that a human-machine collaboration based on stepwise-evolving artificial intelligence (se-AI) can significantly shorten the development period of PGM-free multimetal OER electrocatalysts with performance beyond a PGM of RuO
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.