Evidence map›Paper›PMID 33260485›Full record

ArticlePolymers2020

Hollow Mesoporous Microspheres Coating for Super-Hydrophobicity Wood with High Thermostability and Abrasion Performance.

Rui Yang, Shida Zuo, Beibei Song, Haiyan Mao, Zhenhua Huang, Yingji Wu, Liping Cai, Shengbo Ge, Hailan Lian, Changlei Xia

Open access · goldAbstract read
In one paragraph

Article in Polymers, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
1.5field-weighted citation impact, top 20% 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

2 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. 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

10 authors at 2 institutions in 2 countries.

Rui YangCo-Innovation Center of Efficient Processing and Utilization of Forest Resources, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing 210037, China.ORCID 0000-0002-2173-8771
Shida ZuoCo-Innovation Center of Efficient Processing and Utilization of Forest Resources, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing 210037, China.
Beibei SongCo-Innovation Center of Efficient Processing and Utilization of Forest Resources, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing 210037, China.
Haiyan MaoCo-Innovation Center of Efficient Processing and Utilization of Forest Resources, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing 210037, China.
Zhenhua HuangDepartment of Mechanical Engineering, University of North Texas, Denton, TX 76207, USA.
Yingji WuCo-Innovation Center of Efficient Processing and Utilization of Forest Resources, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing 210037, China.
Liping CaiDepartment of Mechanical Engineering, University of North Texas, Denton, TX 76207, USA.
Shengbo GeCo-Innovation Center of Efficient Processing and Utilization of Forest Resources, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing 210037, China.
Hailan LianCo-Innovation Center of Efficient Processing and Utilization of Forest Resources, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing 210037, China.
Changlei XiaCo-Innovation Center of Efficient Processing and Utilization of Forest Resources, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing 210037, China.ORCID 0000-0002-7063-774X
Nanjing Forestry University · CNUniversity of North Texas · US

Funding

Jiangsu Province Science and Technology Project SZ-SQ2018017Jiangsu Province Science and Technology Project SZ-SQ2018018National Natural Science Foundation of China 31901372National Natural Science Foundation of China 32071703Natural Science Foundation of Jiangsu Province BK20190758Natural Science Foundation of Jiangsu University 18KJA220002
6 · The paper itself

Abstract

Super-hydrophobic phenomena generally exist in nature, and wood can also obtain hydrophobicity by specific processing on the surface, being like the construction of microscale rough surface or decoration with low surface energy materials. In this research, the formation of hydrophobic layers on wood surface was investigated without breaking the wood's original structure. The core-shell structure particles were prepared by penetrating orthosilicate and polystyrene into the hollow mesoporous microsphere structure with tetrahydrofuran. A wood sample was coated with polydimethylsiloxane (PDMS) resin layer to enhance the adhesion of nano and micron hollow mesoporous microsphere on its surface. According to the surface structure of super-hydrophobic subjects in nature, the nano and micron hollow mesoporous microsphere were sprayed with different ratios several times to form a hydrophobic surface. The water contact angle could reach 150°, revealing that the hydrophobic behavior of the nano and micron hollow mesoporous microsphere coating was achieved. The microstructures of wood samples were examined by the scanning electron microscopy, and the chemical functional groups were investigated by the Fourier transform infrared; both verified that the hydrophobic surface was successfully coated. The thermogravimetric examination revealed the improved thermal stability of the hydrophobic wood. The scratch test was used to measure the abrasion resistance of the nano and micron hollow mesoporous microsphere coatings on wood surface. It was suggested that the nano and micron hollow mesoporous microsphere coating was an effective method to fabricate extremely hydrophobic wood products.

Indexed as

hollow mesoporoushydrophobicmicrospherewood

Identifiers

PMID33260485
PMCPMC7760382
OpenAlexW3108266613

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.