Evidence map›Paper›PMID 42506213›Full record

ArticleMembranes2026

Selective Separation of Inorganic and Organic Carbonates in Aqueous Solutions by Reverse Osmosis (RO) and Nanofiltration (NF) Membranes.

Rahma Al Busaidi, Budoor Al Umairi, Zulfiqar Ahmad Rehan, Mohammed Al-Abri

Abstract read
In one paragraph

Article in Membranes, 2026. 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

4 authors.

Rahma Al BusaidiDepartment of Physics, College of Science, Sultan Qaboos University, Al-Khoud, P.O. Box 33, Muscat 123, Oman.ORCID 0000-0003-0169-8642
Budoor Al UmairiDepartment of Chemistry, College of Science, Sultan Qaboos University, Al-Khoud, P.O. Box 33, Muscat 123, Oman.ORCID 0000-0003-3611-9700
Zulfiqar Ahmad RehanDepartment of Chemistry, College of Science, Sultan Qaboos University, Al-Khoud, P.O. Box 33, Muscat 123, Oman.ORCID 0000-0001-8508-3156
Mohammed Al-AbriNanotechnology Research Center, Sultan Qaboos University, Al-Khoud, P.O. Box 33, Muscat 123, Oman.ORCID 0000-0002-5470-8050

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study presents a systematic comparison of commercial reverse osmosis (RO) and nanofiltration (NF) membranes for the separation of inorganic and organic carbonates from aqueous solutions, providing insight into the roles of membrane pore structure and surface charge in governing separation mechanisms. Membrane molecular weight cut-off (MWCO), zeta potential, and thermal stability were characterized and correlated with separation performance. The RO membrane exhibited a lower MWCO and a more negative surface charge than the NF membrane, resulting in superior rejection of both inorganic and organic carbonates. For inorganic carbonates, rejection increased with pH owing to enhanced carbonate ionization and stronger electrostatic repulsion, reaching 91-98% for the RO membrane compared with 60-95% for the NF membrane. In contrast, the rejection of neutral organic carbonates was governed primarily by steric exclusion, with the RO membrane achieving approximately 80% rejection, whereas the NF membrane exhibited negligible removal. These findings demonstrate the combined influence of membrane pore size and surface charge on carbonate separation and provide practical guidance for selecting commercial membranes for efficient carbonate removal in water treatment applications.

Indexed as

carbonate separationinorganic carbonatesmolecular weight cut-offnanofiltrationorganic carbonatesreverse osmosiszeta potential

Identifiers

PMID42506213
PMCPMC13414083

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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.