Evidence map›Paper›PMID 39339050›Full record

ArticlePolymers2024

Carboxyalkylated Lignin as a Sustainable Dispersant for Coal Water Slurry.

Hussein Ahmad Qulatein, Weijue Gao, Pedram Fatehi

Abstract read
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 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
  2. Article
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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.

Hussein Ahmad QulateinFaculty of Science and Technology, University of Lille, 59000 Lille, France.ORCID 0000-0002-3258-7921
Weijue GaoGreen Process Research Centre, Department of Chemical Engineering, Lakehead University, 955 Oliver Road, Thunder Bay, ON P7B 5E1, Canada.
Pedram FatehiGreen Process Research Centre, Department of Chemical Engineering, Lakehead University, 955 Oliver Road, Thunder Bay, ON P7B 5E1, Canada.ORCID 0000-0002-3874-5089

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Coal water slurry (CWS) has been considered a cleaner and sustainable alternative to coal. However, the challenging suspension of coal particles in CWS has created a major obstacle to its use in industry. This study presents a novel approach to enhance the stability and rheological properties of coal water slurry (CWS) through the utilization of carboxyalkylated lignin (CL) as a dispersant. The generated CL samples had high water solubility of around 9 g/L and a charge density of around 2 mmol/g. All CLs were able to stabilize the coal suspension, and their performance decreased due to the increase in the alkyl chain length of carboxyalkylated lignin. Carboxymethylated lignin (CL-1) improved the stability of the coal suspensions with the lowest instability index of less than 0.6. The addition of CLs reduced the contact angle of the coal surface from 45.3° to 34.6°, and the increase in the alkyl chain length hampered its effect on contact angle changes. The zeta potential measurements confirmed that the adsorption of CL enhanced the electrostatic repulsion between coal particles in suspensions, and the zeta potential decreased with the increased alkyl chain length of CLs due to increased steric hindrance. The rheology results indicated that CLs demonstrated shear thinning behavior. This innovative method showcases the affinity of carboxyalkylated lignin to improve the performance of CWS, offering an environmentally friendly alternative for producing a cleaner product, i.e., sustainable coal water slurry, with improved suspension stability.

Indexed as

coal water slurrydispersantfuelligninsustainable product

Identifiers

PMID39339050
PMCPMC11435015

What OpenQuestion holds

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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.