Evidence map›Paper›PMID 40842253›Full record

ArticleAngewandte Chemie (International ed. in English)2025

Accelerated Porosity Screening Using a Multichannel Colorimetric Array.

Yushu Han, Isaiah Borne, Biplab Dutta, Rob Clowes, Hang Qu, Alex James, Charlotte E Boott, Marc A Little, Andrew I Cooper

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Angewandte Chemie (International ed. in English), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing 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

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Accelerated Porosity Screening Using a Multichannel Colorimetric Array.Angewandte Chemie (International ed. in English) · 2025
    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

9 authors.

Yushu HanDepartment of Chemistry and Materials Innovation Factory, University of Liverpool, 51 Oxford Street, Liverpool, L7 3NY, UK.ORCID https://orcid.org/0009-0004-1990-0196
Isaiah BorneDepartment of Chemistry and Materials Innovation Factory, University of Liverpool, 51 Oxford Street, Liverpool, L7 3NY, UK.
Biplab DuttaDepartment of Chemistry and Materials Innovation Factory, University of Liverpool, 51 Oxford Street, Liverpool, L7 3NY, UK.
Rob ClowesDepartment of Chemistry and Materials Innovation Factory, University of Liverpool, 51 Oxford Street, Liverpool, L7 3NY, UK.ORCID https://orcid.org/0009-0002-4686-2119
Hang QuDepartment of Chemistry and Materials Innovation Factory, University of Liverpool, 51 Oxford Street, Liverpool, L7 3NY, UK.ORCID https://orcid.org/0000-0001-8726-3062
Alex JamesDepartment of Chemistry and Materials Innovation Factory, University of Liverpool, 51 Oxford Street, Liverpool, L7 3NY, UK.
Charlotte E BoottDepartment of Chemistry and Materials Innovation Factory, University of Liverpool, 51 Oxford Street, Liverpool, L7 3NY, UK.ORCID https://orcid.org/0000-0003-0902-030X
Marc A LittleDepartment of Chemistry and Materials Innovation Factory, University of Liverpool, 51 Oxford Street, Liverpool, L7 3NY, UK.ORCID https://orcid.org/0000-0002-1994-0591
Andrew I CooperDepartment of Chemistry and Materials Innovation Factory, University of Liverpool, 51 Oxford Street, Liverpool, L7 3NY, UK.ORCID https://orcid.org/0000-0003-0201-1021

Funding

China Sponsorship CouncilEngineering and Physical Sciences Research Council EP/V038117/1)H2020 European Research Council 856405Royal Society RSRP∖S2∖232003
6 · The paper itself

Abstract

Porous materials are important for many technologies, but the measurement of porosity by gas adsorption isotherms is slow, taking around one day per sample using a single-port gas sorption analyzer, even when using a "quick" analysis method with relatively few data points. With the increased use of automated platforms for material generation, porosity analysis is now frequently the bottleneck in the discovery of new porous materials. Here, we present a semiautomated pre-screening strategy that uses dye adsorption to create a colorimetric array that is combined with computer vision analysis for porosity screening. By using a six-dye multichannel array and a defined porosity threshold, our method rapidly screened 50 candidate materials that spanned molecular solids, polymers, and metal-organic frameworks. The method showed a 98-100% classification accuracy compared with gas uptake measurements. While this method is more qualitative than quantitative, it is more than 30 times faster than conventional gas sorption measurements, and it has the scope to be made much faster with greater parallelization and automation. This makes this colorimetric method suitable for pre-screening arrays of materials to choose samples that merit more detailed conventional porosity analysis.

Indexed as

ColorimetryDye adsorptionGas adsorptionHigh throughputPorosity

Identifiers

PMID40842253
PMCPMC12462744

What OpenQuestion holds

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LicenceCC BY
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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.