Evidence map›Paper›PMID 31739426›Full record

ArticlePolymers2019

Quantitative Pore Characterization of Polyurethane Foam with Cost-Effective Imaging Tools and Image Analysis: A Proof-Of-Principle Study.

Shemmira Yunus, Baah Sefa-Ntiri, Benjamin Anderson, Francis Kumi, Patrick Mensah-Amoah, Samuel Sonko Sackey

Abstract read
In one paragraph

Article in Polymers, 2019. 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. An In Situ Characterisation Method for 3-D Electrospun Foams.Nanomaterials (Basel, Switzerland) · 2025
    Article
  3. Article
  4. Review
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.

Shemmira YunusDepartment of Physics, University of Cape Coast, PMB, Ghana.
Baah Sefa-NtiriDepartment of Physics, University of Cape Coast, PMB, Ghana.ORCID 0000-0003-0132-9134
Benjamin AndersonDepartment of Physics, University of Cape Coast, PMB, Ghana.ORCID 0000-0001-8495-9515
Francis KumiDepartment of Agricultural Engineering, University of Cape Coast, PMB, Ghana.
Patrick Mensah-AmoahDepartment of Physics, University of Cape Coast, PMB, Ghana.
Samuel Sonko SackeyDepartment of Physics, University of Cape Coast, PMB, Ghana.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study investigated the pore characterization of polyurethane (PU) foam as a necessary step in water filtration membrane fabrication. Porous material characterization is essential for predicting membrane performance, strength, durability, surface feel, and to understand the transport mechanisms using modeling and simulations. Most existing pore characterization techniques are relatively costly, time-consuming, subjective, and have cumbersome sample preparations. This study focused on using three relatively inexpensive imaging systems: a black box, Canon camera (EOS760D), and LaserJet scanner (M1132 MFP). Two standard, state-of-the-art imaging systems were used for comparison: a stereomicroscope and a scanning electron microscope. Digital images produced by the imaging systems were used with a MATLAB algorithm to determine the surface porosity, pore area, and shape factor of the polyurethane foam in an efficient manner. The results obtained established the compatibility of the image analysis algorithm with the imaging systems. The black box results were found to be more comparable to both the stereomicroscope and SEM systems than those of the Canon camera and scanner imaging systems. Indeed, the current research effort demonstrates the possibility of substrate characterization with inexpensive imaging systems.

Indexed as

image analysisinexpensive imaging systemspolyurethane foampore morphologyporous substrate

Identifiers

PMID31739426
PMCPMC6918242

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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.