Evidence map›Paper›PMID 42825074›Full record

ArticleACS omega2026

Achieving Highly Efficient Repeatable Hair Perming by Bunte Salt-Thiol Exchange Reaction.

Zhenyu Qin, Kuan Chang, Jing Wang, Timson Chen, Zhizhen Li, Ya Chen, Ling Ma

Abstract read
In one paragraph

Article in ACS omega, 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.

Zhenyu QinKey Laboratory of Synthetic and Biological Colloids, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, Wuxi 214122, China.ORCID https://orcid.org/0009-0003-8384-9105
Kuan ChangKey Laboratory of Synthetic and Biological Colloids, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, Wuxi 214122, China.
Jing WangKey Laboratory of Synthetic and Biological Colloids, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, Wuxi 214122, China.
Timson ChenGuangzhou Aogu Cosmetics Manufacturing Co., Ltd., Guangzhou 510810, China.
Zhizhen LiGuangzhou Aogu Cosmetics Manufacturing Co., Ltd., Guangzhou 510810, China.
Ya ChenGuangzhou Aogu Cosmetics Manufacturing Co., Ltd., Guangzhou 510810, China.
Ling MaGuangzhou Aogu Cosmetics Manufacturing Co., Ltd., Guangzhou 510810, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Conventional chemical perming typically suffers from a gradual decrease in styling efficiency due to the cumulative degradation of original disulfide bonds. To address this issue, this study proposes a novel perming technology based on the Bunte salt-thiol exchange reaction. A bifunctional Bunte salt, sodium hexamethylene-1,6-bisthiosulfate (SHB), was successfully synthesized, with its high purity and structure validated by X-ray diffraction (XRD) and Raman spectroscopy. The perming performance of this Bunte salt method was evaluated and compared against the conventional oxidative perming method on Chinese virgin hair. X-ray photoelectron spectroscopy (XPS) was utilized to calculate the relative content of disulfide bonds and to elucidate their reconstruction mechanism. Furthermore, the hair morphology, surface properties, and mechanical performance were systematically evaluated using scanning electron microscopy (SEM), transmission electron microscopy (TEM), tensile testing, and other auxiliary experiments. The results demonstrated that after six repetitive perming cycles, the SHB-permed hair maintained a high perming efficiency of 920%, whereas that of the H

Identifiers

PMID42825074
PMCPMC13629021

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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.