Evidence map›Paper›PMID 35200458›Full record

ReviewGels (Basel, Switzerland)2022

Gel Chromatography for Separation of Single-Walled Carbon Nanotubes.

Sunwoo Kim, Woo-Jae Kim

Abstract readReview
In one paragraph

Review in Gels (Basel, Switzerland), 2022. 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. Review
  4. 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

2 authors.

Sunwoo KimDepartment of Chemical Engineering and Materials Science, Graduate Program in System Health Science and Engineering, Ewha Womans University, 52, Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Korea.ORCID 0000-0001-9983-2592
Woo-Jae KimDepartment of Chemical Engineering and Materials Science, Graduate Program in System Health Science and Engineering, Ewha Womans University, 52, Ewhayeodae-gil, Seodaemun-gu, Seoul 03760, Korea.ORCID 0000-0001-8761-6809

Funding

National Research Foundation of Korea NRF-2019R1F1A1060734
6 · The paper itself

Abstract

Carbon nanotubes (CNTs), having either metallic or semiconducting properties depending on their chirality, are advanced materials that can be used for different devices and materials (e.g., fuel cells, transistors, solar cells, reinforced materials, and medical materials) due to their excellent electrical conductivity, mechanical strength, and thermal conductivity. Single-walled CNTs (SWNTs) have received special attention due to their outstanding electrical and optical properties; however, the inability to selectively synthesize specific types of CNTs has been a major obstacle for their commercialization. Therefore, researchers have studied different methods for the separation of SWNTs based on their electrical and optical properties. Gel chromatography methods enable the large-scale separation of metallic/semiconducting (m/s) SWNTs and single-chirality SWNTs with specific bandgaps. The core principle of gel chromatography-based SWNT separation is the interaction between the SWNTs and gels, which depends on the unique electrical properties of the former. Controlled pore glass, silica gel, agarose-based gel, and allyl dextran-based gel have been exploited as mediums for gel chromatography. In this paper, the interaction between SWNTs and gels and the different gel chromatography-based SWNT separation technologies are introduced. This paper can serve as a reference for researchers who plan to separate SWNTs with gel chromatography.

Indexed as

anionic surfactantgel chromatographyhydrogelssingle-walled carbon nanotubes

Identifiers

PMID35200458
PMCPMC8871249

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

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.