Evidence map›Paper›PMID 36363629›Full record

ArticleMembranes2022

Porous Cellulose Substrate Study to Improve the Performance of Diffusion-Based Ionic Strength Sensors.

Hamid Khosravi, Pouya Mehrdel, Joan Antoni López Martínez, Jasmina Casals-Terré

Open access · goldAbstract read
In one paragraph

Article in Membranes, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.2field-weighted citation impact, top 52% of its field
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

2 citing papers in PubMed, 4 citations in OpenAlex.

  1. Article
  2. 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

4 authors at 1 institution in 1 country.

Hamid KhosraviMechanical Engineering Department-MicroTech Lab., Universitat Politècnica de Catalunya (UPC), C/Colom 7-11, 08222 Terrassa, Barcelona, Spain.ORCID 0000-0002-1687-0196
Pouya MehrdelMechanical Engineering Department-MicroTech Lab., Universitat Politècnica de Catalunya (UPC), C/Colom 7-11, 08222 Terrassa, Barcelona, Spain.ORCID 0000-0003-3496-2833
Joan Antoni López MartínezDepartment of Mining, Industrial and ICT Engineering (EMIT), Universitat Politècnica de Catalunya (UPC), AV. Bases de Manresa 61-73, 08240 Manresa, Barcelona, Spain.ORCID 0000-0002-0082-9770
Jasmina Casals-TerréMechanical Engineering Department-MicroTech Lab., Universitat Politècnica de Catalunya (UPC), C/Colom 7-11, 08222 Terrassa, Barcelona, Spain.ORCID 0000-0002-1368-3950
Universitat Politècnica de Catalunya · ES

Funding

Agency Ministerio de Ciencia e Innovación PID2020-114070RB-I00
6 · The paper itself

Abstract

Microfluidic paper-based analytical devices (µPADs) are leading the field of low-cost, quantitative in-situ assays. However, understanding the flow behavior in cellulose-based membranes to achieve an accurate and rapid response has remained a challenge. Previous studies focused on commercial filter papers, and one of their problems was the time required to perform the test. This work studies the effect of different cellulose substrates on diffusion-based sensor performance. A diffusion-based sensor was laser cut on different cellulose fibers (Whatman and lab-made Sisal papers) with different structure characteristics, such as basis weight, density, pore size, fiber diameter, and length. Better sensitivity and faster response are found in papers with bigger pore sizes and lower basis weights. The designed sensor has been successfully used to quantify the ionic concentration of commercial wines with a 13.6 mM limit of detection in 30 s. The developed µPAD can be used in quantitative assays for agri-food applications without the need for any external equipment or trained personnel.

Indexed as

cellulose-based membranediffusion-based sensorflow behaviormicrofluidic paper-based analytical devicesquantitative assaysisal paper

Identifiers

PMID36363629
PMCPMC9699251
OpenAlexW4307765056

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

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.