Evidence map›Paper›PMID 41969914›Full record

ArticleGlobal challenges (Hoboken, NJ)2026

Photo-Assisted Charge-Discharge Behavior of NMC622 Cathode.

Meltem Çayirli, Ersu Lökçü, Reşat Can Özden, Mustafa Anik

Abstract read
In one paragraph

Article in Global challenges (Hoboken, NJ), 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

4 authors.

Meltem ÇayirliDepartment of Metallurgical and Materials Engineering Eskisehir Osmangazi University Eskisehir Turkey.
Ersu LökçüDepartment of Metallurgical and Materials Engineering Eskisehir Osmangazi University Eskisehir Turkey.ORCID https://orcid.org/0000-0002-1972-627X
Reşat Can ÖzdenDepartment of Metallurgical and Materials Engineering Eskisehir Osmangazi University Eskisehir Turkey.ORCID https://orcid.org/0000-0002-9242-3136
Mustafa AnikDepartment of Metallurgical and Materials Engineering Eskisehir Osmangazi University Eskisehir Turkey.ORCID https://orcid.org/0000-0003-0166-7862

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In this study, a nitrogen (N)-doped graphene film was synthesized on copper foil via chemical vapor deposition (CVD) and employed as a photocatalytic electrode for the photo-assisted charging and discharging of lithium-ion batteries (LIBs). By integrating the photocatalyst as a separate electrode and allowing the cathode to function solely in its conventional role, this configuration mitigated the long-term degradation of light-harvesting efficiency commonly observed in semiconductor-based cathodes and eliminated the constraint of using only semiconductor materials in LIBs. The photo-charging response of the LIB under 1 Sun illumination yielded a photo-conversion efficiency (η%) of 0.152% for the N-doped graphene. Photo-assisted operation enhanced the discharge capacity by at least 15%, improved capacity retention to 90%, and maintained a Coulombic efficiency of 100% over 100 cycles in NMC622 half-cells. The photo-generated electrons effectively accelerated interfacial charge transfer kinetics, thereby facilitating redox reactions at the electrode-electrolyte interface during cycling. Overall, this photo-assisted strategy not only improves LIB performance but also offers a promising route for integrating solar energy conversion directly into energy storage technologies.

Indexed as

chemical vapor depositionLi‐ion batteriesN‐Doped grapheneNMC622photo‐assistance

Identifiers

PMID41969914
PMCPMC13066908

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.