Evidence map›Paper›PMID 36771960›Full record

ReviewPolymers2023

Modified Cellulose Proton-Exchange Membranes for Direct Methanol Fuel Cells.

Gowthami Palanisamy, Tae Hwan Oh, Sadhasivam Thangarasu

Abstract readReview
In one paragraph

Review in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. 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

3 authors.

Gowthami PalanisamySchool of Chemical Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea.
Tae Hwan OhSchool of Chemical Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea.ORCID 0000-0003-4922-5000
Sadhasivam ThangarasuSchool of Chemical Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea.ORCID 0000-0002-8431-233X

Funding

Core Research Support Center for Natural Products and Medical Materials (CRCNM) in Yeungnam UniversityKorean Ministry of Trade, Industry, and Energy 20008490
6 · The paper itself

Abstract

A direct methanol fuel cell (DMFC) is an excellent energy device in which direct conversion of methanol to energy occurs, resulting in a high energy conversion rate. For DMFCs, fluoropolymer copolymers are considered excellent proton-exchange membranes (PEMs). However, the high cost and high methanol permeability of commercial membranes are major obstacles to overcome in achieving higher performance in DMFCs. Novel developments have focused on various reliable materials to decrease costs and enhance DMFC performance. From this perspective, cellulose-based materials have been effectively considered as polymers and additives with multiple concepts to develop PEMs for DMFCs. In this review, we have extensively discussed the advances and utilization of cost-effective cellulose materials (microcrystalline cellulose, nanocrystalline cellulose, cellulose whiskers, cellulose nanofibers, and cellulose acetate) as PEMs for DMFCs. By adding cellulose or cellulose derivatives alone or into the PEM matrix, the performance of DMFCs is attained progressively. To understand the impact of different structures and compositions of cellulose-containing PEMs, they have been classified as functionalized cellulose, grafted cellulose, acid-doped cellulose, cellulose blended with different polymers, and composites with inorganic additives.

Indexed as

cellulose membranecost-effectivedirect methanol fuel cellfuel cellhigh performancehydrocarbon membranemethanol permeabilityNafion membraneproton conductivityproton-exchange membrane

Identifiers

PMID36771960
PMCPMC9920170

What OpenQuestion holds

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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.