ReviewNational science review2024
Wet-spinning of carbon nanotube fibers: dispersion, processing and properties.
Review in National science review, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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.
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.
Who cites it
6 citing papers in PubMed.
- Low-Density Materials for Particle Accelerator Applications: Challenges, Capabilities, and Future Directions.Materials (Basel, Switzerland) · 2026Article
- Wearable Tailored Passive Radiative Cooling Textile for Flexible Electronic Integration.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Article
- Synergistic nitrogen and endohedral MoClNature communications · 2026Article
- Carbon-Based Functional Nanomaterials: Preparation, Properties and Applications.Materials (Basel, Switzerland) · 2026Article
- Advancing Carbon Nanotube Fibers: Addressing Challenges from Production to Application.ACS central science · 2025Review
- Shaping the future of fiber technology: exploring functional and smart innovations.National science review · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Owing to the intrinsic excellent mechanical, electrical, and thermal properties of carbon nanotubes (CNTs), carbon nanotube fibers (CNTFs) have been expected to become promising candidates for the next-generation of high-performance fibers. They have received considerable interest for cutting-edge applications, such as ultra-light electric wire, aerospace craft, military equipment, and space elevators. Wet-spinning is a broadly utilized commercial technique for high-performance fiber manufacturing. Thus, compared with array spinning from drawable CNTs vertical array and direct dry spinning from floating catalyst chemical vapor deposition (FCCVD), the wet-spinning technique is considered to be a promising strategy to realize the production of CNTFs on a large scale. In this tutorial review, we begin with a summative description of CNTFs wet-spinning process. Then, we discuss the high-concentration CNTs wet-spinning dope preparation strategies and corresponding non-covalent adsorption/charge transfer mechanisms. The filament solidification during the coagulation process is another critical procedure for determining the configurations and properties for derived CNTFs. Next, we discuss post-treatment, including continuous drafting and thermal annealing, to further optimize the CNTs orientation and compact configuration. Finally, we summarize the physical property-structure relationship to give insights for further performance promotion in order to satisfy the prerequisite for detailed application. Insights into propelling high-performance CNTFs production from lab-scale to industry-scale are proposed, in anticipation of this novel fiber having an impact on our lives in the near future.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.