Evidence map›Paper›PMID 39518227›Full record

ArticlePolymers2024

A Sustainable and Eco-Friendly Membrane for PEM Fuel Cells Using Bacterial Cellulose.

Xiaozhen Yang, Lin Huang, Qiang Deng, Weifu Dong

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Polymers, 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
–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

2 citing papers in PubMed.

  1. Article
  2. Review
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

4 authors.

Xiaozhen YangThe Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, 1800 Lihu Road, Wuxi 214122, China.
Lin HuangThe Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, 1800 Lihu Road, Wuxi 214122, China.
Qiang DengThe Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, 1800 Lihu Road, Wuxi 214122, China.ORCID 0009-0006-2304-0859
Weifu DongThe Key Laboratory of Synthetic and Biological Colloids, Ministry of Education, School of Chemical and Material Engineering, Jiangnan University, 1800 Lihu Road, Wuxi 214122, China.

Funding

National Natural Science Foundation of China 52273089
6 · The paper itself

Abstract

Bacterial cellulose (BC) is an advantageous polymer due to its renewable nature, low cost, environmental compatibility, biocompatibility, biodegradability, chemical stability, and ease of modification. With these advantages, BC is an interesting candidate for the development of novel eco-friendly materials for proton-exchange membrane (PEM) applications. However, its practical applications have been limited by its relatively high dispersion in water, which usually occurs during the operation of proton-exchange membrane fuel cells (PEMFCs). In addition, the proton conductivity of bacterial cellulose is poor. In this study, functionalized BC modified with 3-aminopropyltriethoxysilane (APTES) was prepared using a solvent casting method to enhance its performance. The results showed that the water stability of the modified BC membrane was significantly improved, with the contact angle increasing from 54.9° to 103.3°. Furthermore, the optimum ratio of BC and APTES was used to prepare a proton-exchange membrane with a maximum proton conductivity of 62.2 mS/cm, which exhibited a power generation performance of 4.85 mW/cm

Indexed as

alkaline proton carrierbacterial cellulosefuel cellsfully bio-based membranePEMproton conductivity

Identifiers

PMID39518227
PMCPMC11548236

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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.