Evidence map›Paper›PMID 41779116›Full record

ArticleNano-micro letters2026

Eco-Friendly, Multi-Mode Processable Highly Moldable Wood Enabled by the Reconstruction of Hydrogen-Bonding Domain.

Rui Yang, Linghui Qi, Xiaoli Wu, Zhipeng Liu, Huiyang Bian, Changlei Xia, Changtong Mei, Shuaicheng Jiang, Meng Yao, Jianzhang Li

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Nano-micro letters, 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

10 authors.

Rui YangJiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, International Innovation Center for Forest Chemicals and Materials, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing, 210037, People's Republic of China. yangrui@njfu.edu.cn.
Linghui QiJiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, International Innovation Center for Forest Chemicals and Materials, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing, 210037, People's Republic of China.
Xiaoli WuSchool of Mechanical and Electronic Engineering, Nanjing Forestry University, Nanjing, 210037, People's Republic of China.
Zhipeng LiuJiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, International Innovation Center for Forest Chemicals and Materials, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing, 210037, People's Republic of China.
Huiyang BianJiangsu Provincial Key Lab of Sustainable Pulp and Paper Technology and Biomass Materials, Nanjing Forestry University, Nanjing, 210037, People's Republic of China.
Changlei XiaJiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, International Innovation Center for Forest Chemicals and Materials, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing, 210037, People's Republic of China.
Changtong MeiJiangsu Co-Innovation Center of Efficient Processing and Utilization of Forest Resources, International Innovation Center for Forest Chemicals and Materials, College of Materials Science and Engineering, Nanjing Forestry University, Nanjing, 210037, People's Republic of China.
Shuaicheng JiangState Key Laboratory of Efficient Production of Forest Resources & MOE Key Laboratory of Wood Material Science and Application, Beijing Forestry University, Beijing, 100091, People's Republic of China. jiangsc@bjfu.edu.cn.
Meng YaoCollege of Materials Science and Engineering, Sichuan University, Chengdu, 610065, People's Republic of China. yaomeng@scu.edu.cn.
Jianzhang LiState Key Laboratory of Efficient Production of Forest Resources & MOE Key Laboratory of Wood Material Science and Application, Beijing Forestry University, Beijing, 100091, People's Republic of China. lijzh@bjfu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The production of advanced 3D engineering materials relies on energy-intensive moldable materials such as metals and plastics, making it difficult to cope with the increasingly severe global energy crisis. Wood, as a sustainable material, can be molded through hydrothermal treatment, but the limited plasticity hinders its ability to manufacture precision devices. Herein, the process of hydrogen-bond domain reorganization is used in the manufacture of highly moldable wood to enhance the plasticity of wood and ensure the stability of the cellulose structure. The native hydrogen-bond network in the wood cell wall is disrupted and liberated the cellulose fibril matrix through delignification. Subsequent epoxidized soybean oil acrylate (AESO) plasticization enables significantly enhanced plasticity. Hydrogen-bond domains between fibers are reconstructed through moisture variation. Meanwhile, AESO forms a protective layer on the surface of the fibers, preventing excessive moisture from entering and causing the collapse of the fiber framework. This process allows the material to be shaped into complex 3D geometries, including origami cranes or honeycombs, through low-energy hydrothermal processing. This strategy addresses both dimensional stability challenges and environmental instability associated with wood composite materials and offers an eco-friendly alternative to functionalized structures in aviation and transportation.

Indexed as

3D structuresFlexible and moldable woodReconstruction of hydrogen-bonding domainsWood modification

Identifiers

PMID41779116
PMCPMC12961088

What OpenQuestion holds

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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.