Design and modeling of a nanocomposite system for demineralization of sweet whey.

Mina Rezapour, Mohsen Esmaiili, Mehdi Mahmoudian, Alireza Behrooz Sarand

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In one paragraph

Article in Scientific reports, 2025. 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.

Mina RezapourFood Science and Technology Department, Agricultural Faculty, Urmia University, P.O. Box 165, Urmia, 57159-44931, Iran.

Mohsen EsmaiiliFood Science and Technology Department, Agricultural Faculty, Urmia University, P.O. Box 165, Urmia, 57159-44931, Iran. m.esmaiili@urmia.ac.ir.

Mehdi MahmoudianNanotechnology Department, Faculty of Chemistry, Urmia University, Urmia, Iran.

Alireza Behrooz SarandChemical Engineering Department, Urmia University of Technology, Urmia, Iran.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This research investigates the design of a nanofiltration (NF) system based on a nanocomposite membrane containing graphene oxide (GO) for the demineralization of sweet whey and the modeling the NF process. The effects of various process variables, including, transmembrane pressure (TMP), Reynolds number, feed pH, and temperature, on the rejection of the minerals were surveyed. Consequently, the recovery of whey proteins from industrial whey using fabricated membranes in a cross-flow membrane module was also investigated. Among the input variables, the pH of the whey solution has the greatest effect on membrane flux and salt rejection performance. In the dead-end filtration system, the highest flux was achieved for the GO-modified membrane under laboratory conditions with a pressure of 10 bar and a pH of 6. The dynamic flux behavior of whey output and salt rejection from whey was modeled using convolutional neural network (CNN) machine learning tools. Linear and non-linear correlations demonstrated that the CNN model correlates well with experimental data on dynamic flux (R

Indexed as

NanocompositesWheyWhey ProteinsFiltrationGraphiteHydrogen-Ion ConcentrationMembranes, ArtificialMineralsNeural Networks, Computergraphene oxideGraphiteMembranes, ArtificialMineralsWhey ProteinsConvolutional neural networkDemineralizationGraphene oxideModelingNanofiltrationWhey

Identifiers

PMID39924563

DOI10.1038/s41598-025-89009-w

PMCPMC11808072

What OpenQuestion holds

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LicenceCC BY-NC-ND

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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.