Evidence map›Paper›PMID 42713719›Full record

ArticleChemSusChem2026

Electronic Modulation of NiO by Cu Doping Toward Enhanced Electrocatalytic Ethylene Glycol Oxidation to Formate.

Huiyan Pan, Jiaming Ding, Yongshuai Lu, Zhao Zhang, Xueguo Liu, Yi Ma, Jing Yu, Liang Xu, Jialing Tang, Yongfa Zhu and 1 more

Abstract read
In one paragraph

Article in ChemSusChem, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

11 authors.

Huiyan PanSchool of Biological and Chemical Engineering, Nanyang Institute of Technology, Nanyang, China.
Jiaming DingInstitute for Advanced Study, Chengdu University, Chengdu, China.
Yongshuai LuSchool of Biological and Chemical Engineering, Nanyang Institute of Technology, Nanyang, China.
Zhao ZhangSchool of Biological and Chemical Engineering, Nanyang Institute of Technology, Nanyang, China.
Xueguo LiuSchool of Biological and Chemical Engineering, Nanyang Institute of Technology, Nanyang, China.
Yi MaInstitute for Advanced Study, Chengdu University, Chengdu, China.ORCID https://orcid.org/0009-0003-5402-8981
Jing YuCatalonia Institute for Energy Research - IREC, Sant Adrià de Besòs, Catalonia, Spain.ORCID https://orcid.org/0000-0002-7620-745X
Liang XuHenan Fusen New Energy Technology Co., LTD, Nanyang, China.
Jialing TangDepartment of Environmental Engineering, School of Architecture and Civil Engineering, Chengdu University, Chengdu, China.ORCID https://orcid.org/0000-0002-8873-9023
Yongfa ZhuDepartment of Chemistry, Tsinghua University, Beijing, China.ORCID https://orcid.org/0000-0001-8528-509X
Junshan LiInstitute for Advanced Study, Chengdu University, Chengdu, China.ORCID https://orcid.org/0000-0002-1482-1972

Funding

National Natural Science Foundation of China 22579020Natural Science Foundation of Sichuan Province 2025YFHZ0127
6 · The paper itself

Abstract

Electrocatalytic upgrading of waste polyethylene terephthalate (PET) into value-added chemicals not only alleviates environmental pressure but also offers significant economic benefits. In this work, Cu was successfully incorporated into NiO structure with varying contents and applied to the ethylene glycol oxidation reaction (EGOR). Among all the synthesized samples, the electrode based on the optimized 4Cu-NiO sample exhibited significantly enhanced electrochemical performance, delivering a high current density of 113.4 mA cm

Indexed as

dopingethylene glycol oxidation reactionformatepolyethylene terephthalatewaste upgrading

Identifiers

PMID42713719
PMCPMC13555519

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.