Evidence map›Paper›PMID 40279424›Full record

ArticleScience advances2025

Recombination of agricultural residues into moldable composites.

Zhenggang Gong, Xianggang Weng, Deli Wu, Zhendong Lei, Guangxu Yang, Li Shuai

Abstract read
In one paragraph

Article in Science advances, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Review
  2. Article
  3. 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

6 authors.

Zhenggang GongCollege of Materials Engineering, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.ORCID 0000-0001-9322-799X
Xianggang WengCollege of Materials Engineering, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.
Deli WuCollege of Environmental Science and Engineering, Tongji University, Shanghai, 200092, China.ORCID 0000-0002-8565-0779
Zhendong LeiCollege of Environmental Science and Engineering, Tongji University, Shanghai, 200092, China.ORCID 0000-0002-8557-5262
Guangxu YangCollege of Materials Engineering, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.ORCID 0000-0001-9916-0765
Li ShuaiCollege of Materials Engineering, Fujian Agriculture and Forestry University, Fuzhou, 350002, China.ORCID 0000-0002-7404-815X

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Increasing efforts have been devoted to developing biobased and biodegradable plastics and composites from lignocellulosic biomass. Current bioplastic production entails multiple challenging steps including monomer production from biomass as well as polymer synthesis and modification. Here, we report a practical recombination strategy to transform agricultural residues into moldable cellulose-reinforced lignin (CRL) composites. The strategy involves deconstruction of biomass particles followed by thermo-compression molding of cellulose fibers and lignin mixtures. The resulting CRL composites demonstrated excellent mechanical and thermal properties as well as water, abrasive, and flame resistance. Mechanistic studies reveal that small particle size, removal of water-soluble fractions, as well as reservation of lignin and its cross-linking reactivity have considerably positive effects on preparation of high-quality composite items. These insights offer a versatile strategy for transforming various types of low-grade biomass, such as corn stover, into eco-friendly and potentially biodegradable or compostable composites that can serve as sustainable alternatives to traditional duroplast materials.

Identifiers

PMID40279424
PMCPMC12024680

What OpenQuestion holds

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LicenceCC BY-NC
Read underepoch 390

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.