Evidence map›Paper›PMID 36850251›Full record

ArticlePolymers2023

3D Printed Functionalized Nanocellulose as an Adsorbent in Batch and Fixed-Bed Systems.

Mohd Shaiful Sajab, Wan Nazihah Liyana Wan Jusoh, Denesh Mohan, Hatika Kaco, Rubiyah Baini

Abstract read
In one paragraph

Article in Polymers, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Mohd Shaiful SajabResearch Center for Sustainable Process Technology (CESPRO), Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.ORCID 0000-0001-8400-8090
Wan Nazihah Liyana Wan JusohResearch Center for Sustainable Process Technology (CESPRO), Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.
Denesh MohanResearch Center for Sustainable Process Technology (CESPRO), Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, Bangi 43600, Selangor, Malaysia.ORCID 0000-0002-0867-0055
Hatika KacoKolej GENIUS Insan, Universiti Sains Islam Malaysia, Bandar Baru Nilai, Nilai 71800, Negeri Sembilan, Malaysia.
Rubiyah BainiFaculty of Engineering, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan 94300, Sarawak, Malaysia.

Funding

Ministry of Higher Education GL/F02/MRUN/01/2019Ministry of Higher Education MRUN-RAKAN-RU-2019-004/4
6 · The paper itself

Abstract

Nanocellulose, a refined form of cellulose, can be further functionalized on surface-active sites, with a catalyst as a regenerative agent. Newly developed adsorbents are expected to have the characteristics of good and rapid adsorption performance and regeneration properties with flexible structure using 3D printing technology. In this work, the adsorption performance of 3D printed functionalized nanocellulose was investigated using batch and fixed-bed column adsorption. Kinetics adsorption studies were divided into different adsorption models, with the pseudo-second order model showing a better correlation coefficient than the pseudo-first order and intraparticle diffusion models. The Langmuir and Thomas models were used to calculate the adsorption performance of batch and fixed-bed columns. Given the catalytic activity of Fenton oxidation, the fixed-bed column was regenerated up to five adsorption-desorption cycles, suggesting satisfactory performance of the column, with a slightly reduced adsorption capacity.

Indexed as

3D printingadditive manufacturingcellulosewater remediation

Identifiers

PMID36850251
PMCPMC9958933

What OpenQuestion holds

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LicenceCC BY
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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.