Evidence map›Paper›PMID 36146016›Full record

ArticlePolymers2022

Effect of Impregnation with Natural Shellac Polymer on the Mechanical Properties of Fast-Growing Chinese Fir.

Qinzhi Zeng, Xiya Yu, Nianfeng Wei, Zhiyong Wu, Qisong Liu, Nairong Chen, Weigang Zhao

Open access · goldAbstract read
PubMed Full text at PMC Publisher
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 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 37% of its field
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, 5 citations in OpenAlex.

  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

7 authors at 2 institutions in 1 country.

Qinzhi ZengCollege of Material Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002, China.ORCID 0000-0003-4045-806X
Xiya YuCollege of Material Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Nianfeng WeiFujian Provincial Forestry Survey and Design Institute, Fuzhou 350001, China.
Zhiyong WuFujian Provincial Forestry Survey and Design Institute, Fuzhou 350001, China.
Qisong LiuFujian Provincial Forestry Survey and Design Institute, Fuzhou 350001, China.
Nairong ChenCollege of Material Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
Weigang ZhaoCollege of Material Engineering, Fujian Agriculture and Forestry University, Fuzhou 350002, China.
State Forestry and Grassland Administration · CNFujian Agriculture and Forestry University · CN

Funding

Forestry Science and Technology Research Project by Forestry Department of Fujian Province No. 2018-26National Natural Science Foundation of China 31971593, 32071688Science and Technology Innovation Special Fund Project of Fujian Agriculture and Forestry University CXZX2019111S
6 · The paper itself

Abstract

Fast-growing Chinese fir wood has shortfalls such as loose structure and low strength because it grows faster than natural trees. Resin impregnation is a great way to increase the strength of fast-growing fir. However, the resin used for impregnation is a kind of urea-formaldehyde resin, phenolic formaldehyde resin, melamine formaldehyde resin, and the like, which introduce harmful substances such as formaldehyde or phenolic into the wood. In this paper, Chinese fir wood was impregnated with natural shellac polymer, and the effects of impregnation variables on the mechanical properties of the wood were examined. The increase in strength in compression perpendicular to grain (

Indexed as

fast-growing Chinese firimpregnationmechanical propertiesresponse face methodshellac

Identifiers

PMID36146016
PMCPMC9506486
OpenAlexW4296350783

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.