Evidence map›Paper›PMID 35808618›Full record

ArticlePolymers2022

Changes in Chemical and Thermal Properties of Bamboo after Delignification Treatment.

Huiling Yu, Chengsheng Gui, Yaohui Ji, Xiaoyan Li, Fei Rao, Weiwei Huan, Luming Li

Abstract read
In one paragraph

Article in Polymers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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.

Huiling YuCollege of Engineering, Yantai Nanshan University, Yantai 265713, China.
Chengsheng GuiZhejiang Shenghua Yunfeng New Material Co., Ltd., Huzhou 313200, China.
Yaohui JiResearch Institute of Wood Industry, Chinese Academy of Forestry, Beijing 100091, China.
Xiaoyan LiChina National Bamboo Research Center, Department of Efficient Utilization of Bamboo and Wood, Wenyi Road 310, Hangzhou 310012, China.
Fei RaoSchool of Art and Design, Zhejiang Sci-Tech University, Hangzhou 310018, China.ORCID 0000-0002-2512-6799
Weiwei HuanCollege of Chemistry and Materials Engineering, Zhejiang A&F University, Hangzhou 311300, China.
Luming LiCollege of Chemistry and Materials Engineering, Zhejiang A&F University, Hangzhou 311300, China.ORCID 0000-0002-3312-2229

Funding

Talent Launching Project of Zhejiang A & F University 2021LFR037
6 · The paper itself

Abstract

Bamboo delignification is a common method for studying its functional value-added applications. In this study, bamboo samples were delignified by treatment with sodium chlorite. The effects of this treatment on the bamboo's microstructure, surface chemical composition, and pyrolysis behaviour were evaluated. Field-emission scanning electron microscopy (FE-SEM), Fourier-transform infrared (FTIR) spectroscopy, X-ray photoelectron spectroscopy (XPS), and X-ray diffraction (XRD) were conducted to evaluate these parameters. The FTIR results demonstrated that the lignin peak decreased or disappeared, and some hemicellulose peaks decreased, indicating that sodium chlorite treatment effectively removed lignin and partly decomposed hemicellulose, although cellulose was less affected. The XPS results showed that, after treatment, the oxygen-to-carbon atomic ratio of delignified bamboo increased from 0.34 to 0.45, indicating a lack of lignin. XRD revealed increased crystallinity in delignified bamboo. Further pyrolysis analysis of treated and untreated bamboo showed that, although the pyrolysis stage of the delignified bamboo did not change, the maximum thermal degradation rate (R

Indexed as

bamboobamboo microstructurechemical changedelignificationpyrolysisthermal property

Identifiers

PMID35808618
PMCPMC9269071

What OpenQuestion holds

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Registered trials

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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.