Evidence map›Paper›PMID 39124294›Full record

ArticleMaterials (Basel, Switzerland)2024

Mathematical Modeling of NaCl Scaling Development in Long-Distance Membrane Distillation for Improved Scaling Control.

Jingcheng Cai, Xingsen Mu, Jian Xue, Jiaming Chen, Zeman Liu, Fei Guo

Abstract read
In one paragraph

Article in Materials (Basel, Switzerland), 2024. 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

6 authors.

Jingcheng CaiSchool of Energy and Power Engineering, Dalian University of Technology, Dalian 116024, China.
Xingsen MuSchool of Energy and Power Engineering, Dalian University of Technology, Dalian 116024, China.
Jian XueGuangdong Provincial Key Laboratory of Green Chemical Product Technology, School of Chemistry and Chemical Engineering, South China University of Technology, Guangzhou 510640, China.
Jiaming ChenSchool of Energy and Power Engineering, Dalian University of Technology, Dalian 116024, China.
Zeman LiuSchool of Energy and Power Engineering, Dalian University of Technology, Dalian 116024, China.
Fei GuoSchool of Energy and Power Engineering, Dalian University of Technology, Dalian 116024, China.ORCID 0000-0002-1802-6490

Funding

Fundamental Research Funds for the Central Universities DUT21JC10
6 · The paper itself

Abstract

Membrane distillation is a novel membrane-based separation technology with the potential to produce pure water from high-salinity brine. It couples transport behaviors along the membrane and across the membrane. The brine in the feed is gradually concentrated due to the permeate flux across the membrane, which is a significant factor in initiating the scaling behavior on the membrane surface along the feed flow direction. It is of great interest to investigate and estimate the development of scaling on the membrane surface. This work specifically focuses on a long-distance membrane distillation process with a sodium chloride solution as the feed. A modeling approach has been developed to estimate the sodium chloride scaling development on the membrane surface along the flow direction. A set of experiments was conducted to validate the results. Based on mathematical simplification and analytical fitting, a simplified model was summarized to predict the initiating position of sodium chloride scaling on the membrane, which is meaningful for scaling control in industrial-scale applications of membrane distillation.

Indexed as

long-distance processmembrane distillationmembrane interfaceNaCl scalingscaling development

Identifiers

PMID39124294
PMCPMC11313132

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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.