Evidence map›Paper›PMID 42680759›Full record

ArticleNature communications2026

Isotope-labeled growth histories reveal persistent chirality in individual carbon nanotubes despite catalyst evolution.

Keigo Otsuka, Ryuji Fujiwara, Shigeo Maruyama

Abstract read
In one paragraph

Article in Nature communications, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

3 authors.

Keigo Otsuka *Department of Mechanical Engineering, The University of Tokyo, Tokyo, Japan. otsuka@photon.t.u-tokyo.ac.jp.ORCID http://orcid.org/0000-0002-6694-0738
Ryuji Fujiwara *Department of Mechanical Engineering, The University of Tokyo, Tokyo, Japan.
Shigeo MaruyamaDepartment of Mechanical Engineering, The University of Tokyo, Tokyo, Japan.ORCID http://orcid.org/0000-0003-3694-3070

Funding

MEXT | Japan Society for the Promotion of Science (JSPS) JP21KK0087MEXT | Japan Society for the Promotion of Science (JSPS) JP22H01411MEXT | Japan Society for the Promotion of Science (JSPS) JP23H05443MEXT | Japan Society for the Promotion of Science (JSPS) JP23K22682MEXT | Japan Society for the Promotion of Science (JSPS) JP26K00883MEXT | JST | Core Research for Evolutional Science and Technology (CREST) JPMJCR20B5
6 · The paper itself

Abstract

In catalytic growth of carbon nanotubes (CNTs), the stability of catalyst structures is critical for achieving structural uniformity and scalability. Continuous synthesis configurations often expose catalysts to spatially varying temperatures and gas compositions along the reactor. The structural integrity along CNTs growing under such dynamic environments remains largely unexplored, due to the inaccessibility of transient catalyst evolution. Here, we use isotope labeling to indirectly read out, from the growth history recorded within each CNT, how its catalyst evolves in a substrate-supported system. The growth rates exhibit hysteresis, varying up to twofold at the same temperature, indicating irreversible catalyst coarsening; nevertheless, the same nanotubes retain atomically identical lattice structures over hundreds of micrometers. This structural robustness, corroborated by molecular dynamics simulations under evolving catalyst conditions, calls for caution against the interpretation of catalyst-CNT structural relationships from static ex situ snapshots. The contrast between structural memory and adaptive growth kinetics further provides a mechanistic design principle of multiple-stage strategies, toward overcoming the conventional quality-quantity trade-off.

Identifiers

PMID42680759
PMCPMC13534721

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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.