Evidence map›Paper›PMID 39916817›Full record

ArticleSensing and Bio-Sensing Research2024

Printing technologies for the fabrication of ion-selective electrodes.

Logan Li, Shelby Hughes, Reyna Osborne, Xuewei Wang

Abstract read
In one paragraph

Article in Sensing and Bio-Sensing Research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

5 citing papers in PubMed.

  1. Review
  2. Nanomaterial-Based Inkjet Printing for Electrochemical Sensing.Small (Weinheim an der Bergstrasse, Germany) · 2026
    Review
  3. Review
  4. Review
  5. 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.

Logan LiDepartment of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, United States.
Shelby HughesDepartment of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, United States.
Reyna OsborneDepartment of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, United States.
Xuewei WangDepartment of Chemistry, Virginia Commonwealth University, Richmond, Virginia 23284, United States.

Funding

Self-calibrated ionophore-based ion-selective electrodes for at-home measurements of blood electrolytesR21EB034113 · NIBIB · VIRGINIA COMMONWEALTH UNIVERSITY · PI WANG, XUEWEI · 2023 to 2023
$427k
NIBIB NIH HHS R21 EB034113
6 · The paper itself

Abstract

The fabrication of ion-selective electrodes (ISEs) via printing technologies such as screen-printing, inkjet printing, and 3D printing is attracting increasing attention due to the superb reproducibility and scalability of these technologies. In contrast to traditional manual casting, coating, and assembling procedures often used in research labs, printing methods are much more compatible with manufacturing processes in industry and, therefore, are easier to scale up. In this paper, we first summarized and compared the printing mechanisms and ink requirements of screen printing, inkjet printing, and 3D printing technologies. Then we present an overview of how different printing technologies can create sensor components, such as electrical contact layers, ion-to-electron transduction layers, ion sensing membranes, reference electrode membranes, insulation layers, and microfluidic/detection housings. The printing protocol, ink material, and sensor performance are highlighted for a few selected ISEs. This review concludes with a summary of the advantages and drawbacks of various printing technologies.

Indexed as

3D printinginkjet printingion-selective electrodepotentiometryscreen printing

Identifiers

PMID39916817
PMCPMC11800639

What OpenQuestion holds

Textmetadata
LicenceTDM
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.