Evidence map›Paper›PMID 41413624›Full record

ArticleScientific reports2025

Mapping defect distribution in transparent single-walled carbon nanotube film with electrical resistance tomography.

Keiya Minakawa, Taiki Nakada, Reiji Kaneko, Takashi Ikuno

Abstract read
In one paragraph

Article in Scientific reports, 2025. 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
–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

2 citing papers in PubMed.

  1. Review
  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.

Keiya MinakawaDepartment of Applied Electronics, Graduate School of Advanced Engineering, Tokyo University of Science, Katsushika, Tokyo, 125-8585, Japan.
Taiki NakadaDepartment of Applied Electronics, Graduate School of Advanced Engineering, Tokyo University of Science, Katsushika, Tokyo, 125-8585, Japan.
Reiji KanekoDepartment of Applied Electronics, Graduate School of Advanced Engineering, Tokyo University of Science, Katsushika, Tokyo, 125-8585, Japan.
Takashi IkunoDepartment of Applied Electronics, Graduate School of Advanced Engineering, Tokyo University of Science, Katsushika, Tokyo, 125-8585, Japan. tikuno@rs.tus.ac.jp.

Funding

Japan Society for the Promotion of Science JP22K04880Japan Society for the Promotion of Science JPMXP1222NM0102
6 · The paper itself

Abstract

We extend the application of electrical resistance tomography (ERT) to visualize IG/ID distribution in transparent single-walled carbon nanotube (SWCNT) thin films. By establishing the correlation between disorder and resistance through experimental measurements, we successfully converted ERT-reconstructed conductivity distributions into IG/ID maps. This approach enabled the detection of a defect region with an IG/ID ratio of approximately 15 embedded in a pristine SWCNT film (IG/ID = 18.1), corresponding to a minimum detectable resistance ratio (R/R0) of 1.59. Moreover, in a sample containing two defect regions introduced by plasma irradiation at 20 and 40 W, ERT successfully distinguished them despite the small difference in IG/ID ratio (1.1). Simulation studies revealed that positional deviations in reconstructed images can be attributed to electrode misalignment, contact resistance variation, and plasma-induced defect expansion. These results demonstrate the feasibility of ERT as a non-destructive, high-resolution technique for evaluating disorder variations in conductive thin films. Furthermore, due to its conductivity-based imaging principle, the method is applicable to other materials such as graphene, indium tin oxide (ITO), and metal nanowire networks, offering promise for real-time monitoring and quality assurance in large-area optoelectronic device manufacturing.

Identifiers

PMID41413624
PMCPMC12775047

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.