Evidence map›Paper›PMID 38921510›Full record

ArticleMembranes2024

On the Maximum Obtainable Purity and Resultant Maximum Useful Membrane Selectivity of a Membrane Separator.

Sean-Thomas B Lundin, Ayumi Ikeda, Yasuhisa Hasegawa

Abstract read
In one paragraph

Article in Membranes, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Development of COMembranes · 2026
    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

3 authors.

Sean-Thomas B LundinResearch Institute of Chemical Process Technology, National Institute of Advanced Industrial Science and Technology (AIST), 4-2-1 Nigatake, Miyagino-ku, Sendai 983-8551, Japan.ORCID 0000-0001-6372-8953
Ayumi IkedaResearch Institute of Chemical Process Technology, National Institute of Advanced Industrial Science and Technology (AIST), 4-2-1 Nigatake, Miyagino-ku, Sendai 983-8551, Japan.ORCID 0000-0001-8413-8522
Yasuhisa HasegawaResearch Institute of Chemical Process Technology, National Institute of Advanced Industrial Science and Technology (AIST), 4-2-1 Nigatake, Miyagino-ku, Sendai 983-8551, Japan.ORCID 0000-0001-8851-3561

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Design considerations concerning the maximum purity of a membrane separator, and the resultant maximum effective selectivity of the membranes were explored by modeling a binary gas membrane separator (pressure-driven permeance) using a dimensionless form. Although the maximum purity has an analytical solution at the limit of zero recovery or stage cut, this solution over-predicts the obtained purity as the recovery is increased. Furthermore, at combinations of high recovery, low feed mole fraction, and low pressure ratio, the maximum purity becomes independent of selectivity above some critical selectivity. As a consequence of this purity limitation, a maximum selectivity is defined at which further increases in selectivity will result in less than a 1% change in the final purity. An equation is obtained that specifies the region in which a limiting purity is less than unity (indicating the existence of a limiting selectivity); operating at less than the limiting pressure ratio results in a purity limitation less than unity. This regime becomes larger and more significant as the inlet mole fraction decreases (e.g., inlet feed mole fraction of 10% and pressure ratio of 100 results in a maximum useful membrane selectivity of only 130 at 95% recovery). These results suggest that membrane research should focus on increasing permeance rather than selectivity for low-concentration separations. The results found herein can be used to set benchmarks for membrane development in various gas separation applications.

Indexed as

binary gas separationcarbon capture and utilization (CCUS)CO2 separationmembrane separator modelingprocess optimization

Identifiers

PMID38921510
PMCPMC11206096

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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.