Evidence map›Paper›PMID 42191721›Full record

ArticleNature communications2026

Super-robust and sustainable bamboo structural material enabled by bonding network reconstruction.

Tao Du, Jiali Cheng, Guanyi Hou, Lei Jiang, Yanli Zhou, Yu Wang, Zhengjun Shi, Jikun Xu, Xuepin Liao, Bi Shi and 1 more

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. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

11 authors.

Tao DuCollege of Biomass Science and Engineering, Sichuan University, Chengdu, PR China.ORCID http://orcid.org/0009-0004-1449-3763
Jiali ChengCollege of Biomass Science and Engineering, Sichuan University, Chengdu, PR China.
Guanyi HouCollege of Biomass Science and Engineering, Sichuan University, Chengdu, PR China.
Lei JiangCollege of Biomass Science and Engineering, Sichuan University, Chengdu, PR China.
Yanli ZhouResearch Institute for Biomass Materials, Tianfu Yongxing Laboratory, Chengdu, PR China.
Yu WangInstitute of Advanced Study, Chengdu University, Chengdu, PR China.
Zhengjun ShiKey Laboratory for Forest Resources Conservation and Utilization in the Southwest Mountains of China, Ministry of Education, Southwest Forestry University, Kunming, PR China.
Jikun XuKey Laboratory of Hubei Province for Coal Conversion and New Carbon Materials, School of Chemistry and Chemical Engineering, Wuhan University of Science and Technology, Wuhan, PR China.ORCID http://orcid.org/0000-0001-8886-031X
Xuepin LiaoCollege of Biomass Science and Engineering, Sichuan University, Chengdu, PR China. xpliao@scu.edu.cn.
Bi ShiCollege of Biomass Science and Engineering, Sichuan University, Chengdu, PR China.ORCID http://orcid.org/0000-0003-0870-6043
Xiao XiaoCollege of Biomass Science and Engineering, Sichuan University, Chengdu, PR China. xiao_xiao@scu.edu.cn.ORCID http://orcid.org/0000-0002-4292-9657

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Lightweight, homogeneously high-strength, and sustainable structural materials exert a crucial role in advanced engineering fields. Bamboo can be processed into high-performance structural material if its mechanical strength and homogeneity are remarkably enhanced. Herein, we report a strategy to process natural bamboo into a lightweight, robust, and durable structural material (HoRo-Bamboo) with homogenously high strengths in both longitudinal (L) and transversal (T) directions through bonding network reconstruction technology. The process requires the dispersion of fibers through H

Identifiers

PMID42191721
PMCPMC13389321

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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.