Evidence map›Paper›PMID 38248706›Full record

ArticleMembranes2024

Green Preparation and Functional Properties of Reinforced All-Cellulose Membranes Made from Corn Straw.

Wentao Zhang, Tianhao Wang, Zeming Jiang, Xin Gao, Changxia Sun, Liping Zhang

Open access · goldAbstract read
In one paragraph

Article in Membranes, 2024. 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
0.9field-weighted citation impact, top 33% 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, 5 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

6 authors at 1 institution in 1 country.

Wentao ZhangCollege of Materials, Science and Technology, Beijing Forestry University, Beijing 100083, China.ORCID 0000-0002-1496-7437
Tianhao WangCollege of Materials, Science and Technology, Beijing Forestry University, Beijing 100083, China.ORCID 0000-0002-1182-7957
Zeming JiangCollege of Materials, Science and Technology, Beijing Forestry University, Beijing 100083, China.ORCID 0000-0002-7301-8768
Xin GaoCollege of Materials, Science and Technology, Beijing Forestry University, Beijing 100083, China.
Changxia SunCollege of Science, Beijing Forestry University, Beijing 100083, China.
Liping ZhangCollege of Materials, Science and Technology, Beijing Forestry University, Beijing 100083, China.
Beijing Forestry University · CN

Funding

Specialized Research Fund for the Forestry Public Welfare Industry 201504602-2
6 · The paper itself

Abstract

In this study, all-cellulose nanocomposite (ACNC) was successfully prepared through a green and sustainable approach by using corn stalk as raw material, water as regeneration solvent, and recyclable two-component ionic liquid/DMSO as the solvent to dissolve cellulose. The morphology and structural properties of ACNC were determined by scanning electron microscopy, transmission electron microscopy, Fourier transform infrared spectroscopy, and X-ray diffraction analysis, indicating homogeneity and good crystallinity. In addition, a comprehensive characterization of ACNC showed that CNF not only improved the thermal stability and mechanical characteristics of ACNC, but also significantly improved the oxygen barrier performance. The ACNC prepared in this work has a good appearance, smooth surface, and good optical transparency, which provides a potential application prospect for converting cellulose wastes such as corn straws into biodegradable packaging materials and electronic device encapsulation materials.

Indexed as

all-cellulose nanocompositecellulose nanofiberscorn strawregenerated cellulose membrane

Identifiers

PMID38248706
PMCPMC10821472
OpenAlexW4390615429

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.