Evidence map›Paper›PMID 38380021›Full record

ArticleHeliyon2024

Response surface methodology for optimization of nitrocellulose preparation from nata de coco bacterial cellulose for propellant formulation.

Nursyafiqah Jori Roslan, Siti Hasnawati Jamal, Jahwarhar Izuan Abdul Rashid, Mohd Nor Faiz Norrrahim, Keat Khim Ong, Wan Md Zin Wan Yunus

Open access · goldAbstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Heliyon, 2024. 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
3.3field-weighted citation impact, top 8% 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

4 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Review
  3. Review
  4. 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.

Nursyafiqah Jori RoslanDepartment of Defence Science, Faculty of Defence Science and Technology, National Defence University of Malaysia, 57000, Kuala Lumpur, Malaysia.
Siti Hasnawati JamalCentre for Tropicalization, Defence Research Institute, National Defence University of Malaysia, 57000, Kuala Lumpur, Malaysia.
Jahwarhar Izuan Abdul RashidDepartment of Chemistry and Biology, Centre for Defence Foundation Studies, National Defence University of Malaysia, 57000, Kuala Lumpur, Malaysia.
Mohd Nor Faiz NorrrahimResearch Center for Chemical Defence, Defence Research Institute, National Defence University of Malaysia, 57000, Kuala Lumpur, Malaysia.
Keat Khim OngDepartment of Chemistry and Biology, Centre for Defence Foundation Studies, National Defence University of Malaysia, 57000, Kuala Lumpur, Malaysia.
Wan Md Zin Wan YunusDepartment of Defence Science, Faculty of Defence Science and Technology, National Defence University of Malaysia, 57000, Kuala Lumpur, Malaysia.
National Defence University of Malaysia · MY

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nitrocellulose (NC) has garnered significant interest among researchers due to its versatile applications, contingent upon the degree of nitration that modifies the cellulose structure. For instance, NC with a high nitrogen content, exceeding 12.5%, finds utility as a key ingredient in propellant formulations, while variants with lower nitrogen content prove suitable for a range of other applications, including the formulation of printing inks, varnishes, and coatings. This communication aims to present the outcomes of our efforts to optimize the nitration reaction of bacterial cellulose to produce high-nitrogen-content NC, employing the response surface methodology (RSM). Our investigation delves into the influence of the mole ratio of sulfuric and nitric acids, reaction temperature, and nitration duration on the nitrogen content of the resultant products. Utilizing a central composite design (CCD), we identified the optimal conditions for NC synthesis. Analysis of variance (ANOVA) underscored the substantial impact of these reaction conditions on the percentage of nitrogen content (%N) yield. By implementing the predicted optimal conditions-namely, a H

Indexed as

Bacterial celluloseCelluloseNitrocelluloseResponse surface methodology (RSM)

Identifiers

PMID38380021
PMCPMC10877292
OpenAlexW4391760870

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.