Evidence map›Paper›PMID 40635910›Full record

ReviewFood chemistry: X2025

Nanocellulose/nanocellulose-based membranes in wastewater treatment: a sustainable path forward for environmental protection.

Rinku Rana, Waseem Ahmad, Abhilasha Mishra, Sanjay Kumar, Akil Ahmad

Abstract readReview
In one paragraph

Review in Food chemistry: X, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. 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

5 authors.

Rinku RanaDepartment of Chemistry, Graphic Era (Deemed to be University), Dehradun 248002, India.
Waseem AhmadDepartment of Chemistry, Graphic Era (Deemed to be University), Dehradun 248002, India.
Abhilasha MishraDepartment of Chemistry, Graphic Era (Deemed to be University), Dehradun 248002, India.
Sanjay KumarDepartment of Food Science and Technology, Graphic Era (Deemed to be University), Dehradun, Uttarakhand 248002, India.
Akil AhmadDepartment of Chemistry, College of Science and Humanities in Al-Kharj, Prince Sattam Bin Abdulaziz University, Al-Kharj 11942, Saudi Arabia.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Nanocellulose, derived from cellulose, is a broadly abundant biopolymer which is gaining attention as a sustainable material, particularly in wastewater remediation. This article explores nanocellulose's precise properties, such as mechanical strength, biocompatibility, and large surface area, which make it an ideal substance for advanced environmental and commercial uses. Derived from plants, agricultural residues, and microorganisms, cellulose is converted into cellulose nanocrystals (CNC), bacterial nanocellulose (BNC), and cellulose nanofibrils (CNF), each with unique structures and properties. Nanocellulose-based membranes are fabricated by using different techniques, along with chemical and mechanical treatment, and show outstanding results in water remediation by adsorbing heavy metals, getting rid of natural pollutants, and degrading pharmaceutical residues. Economic viability is mentioned, which specialises in cost reduction and sustainability. Future studies aim to enhance the membrane's overall performance, expand applications, and expand sustainable manufacturing strategies, ensuring nanocellulose's role in addressing worldwide demanding situations.

Indexed as

Bacterial nanocellulose (BNC)Cellulose nanocrystals (CNC)Cellulose nanofibrils (CNF)NanocelluloseNanocellulose-based membranesWater remedy

Identifiers

PMID40635910
PMCPMC12240117

What OpenQuestion holds

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LicenceCC BY-NC-ND
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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.