Coupled Synergistic Pathway of FeOOH/CeF

Ziyi Gao, Yonghu Ma, Fu Ma, Guolin Feng, Xiaoyan Zhong, Hui Su, Hongjian Zhao

Abstract read

In one paragraph

Article in Small (Weinheim an der Bergstrasse, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing 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

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

7 authors.

Ziyi GaoNingxia Key Laboratory of Green Catalytic Materials and Technology, College of Chemistry and Chemical Engineering, Ningxia Normal University, Guyuan, Ningxia, China.

Yonghu MaNingxia Key Laboratory of Green Catalytic Materials and Technology, College of Chemistry and Chemical Engineering, Ningxia Normal University, Guyuan, Ningxia, China.

Fu MaNingxia Key Laboratory of Green Catalytic Materials and Technology, College of Chemistry and Chemical Engineering, Ningxia Normal University, Guyuan, Ningxia, China.

Guolin FengNingxia Key Laboratory of Green Catalytic Materials and Technology, College of Chemistry and Chemical Engineering, Ningxia Normal University, Guyuan, Ningxia, China.

Xiaoyan ZhongHunan Key Laboratory of Light Energy Conversion Materials, College of Chemistry and Chemical Engineering, Hunan Normal University, Changsha, Hunan, China.

Hui SuHunan Key Laboratory of Light Energy Conversion Materials, College of Chemistry and Chemical Engineering, Hunan Normal University, Changsha, Hunan, China.ORCID https://orcid.org/0000-0001-7653-3426

Hongjian ZhaoNingxia Key Laboratory of Green Catalytic Materials and Technology, College of Chemistry and Chemical Engineering, Ningxia Normal University, Guyuan, Ningxia, China.

Funding

2025 College Student Innovation and Entrepreneurship Training Program of Ningxia Normal University X202510753330Natural Science Foundation of Ningxia 2026AAC030896Ningxia Key Laboratory of Green Catalytic Materials and Technology 2025SYSZD-17

6 · The paper itself

Abstract

Designing effective and durable electrocatalysts for the oxygen evolution reaction (OER) that can operate sustainably under high current densities remains a critical challenge. A significant obstacle lies in overcoming the inherent trade-off between activity and stability, primarily caused by the linear scaling relationships of adsorbates in multi-step reactions and the formation of oxygen vacancies associated with lattice oxygen participation. Herein, we report a FeOOH/CeF

Indexed as

coupling of reaction mechanismselectronic structureheterojunctionhigh current densityoxygen evolution reaction

Identifiers

PMID42489095

DOI10.1002/smll.74741

PMCPMC13580234

What OpenQuestion holds

Textmetadata

Read underepoch 390

Registered trials

None linked

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.