Student or educator? Sign up with your school email and get 6 months of Pro free.
Cited by 232

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Dense, Self‐Formed Char Layer Enables a Fire‐Retardant Wood Structural Material

Gan, Wentao, Chen, Chaoji, Wang, Zhengyang, Song, Jianwei, Kuang, Yudi, He, Shuaiming, Mi, Ruiyu, Sunderland, Peter B., Hu, Liangbing·2019·Advanced Functional Materials

Abstract

Wood is one of the most abundant, sustainable, and aesthetically pleasing structural materials and is commonly used in building and furniture construction. Unfortunately, the fire hazard of wood is a major safety concern for its practical applications. Herein, an effective and environmentally friendly method is demonstrated to substantially improve the fire‐retardant properties of wood materials by delignification and densification. The densification process eliminates the spaces between the cell walls, leading to a highly compact laminated structure that can block oxygen from infiltrating the material. In addition, an insulating wood char layer self‐formed during the burning process obstructs the transport of heat and oxygen diffusion. These synergistic effects contribute to the material's excellent fire‐retardant and self‐extinguished properties, including a 2.08‐fold enhancement in ignition time (tig) and 34.6% decrease in maximum heat release rate. Meanwhile, the densified wood shows a more than 82‐fold enhancement in compressive strength compared with natural wood after exposure to flame for 90 s, which could effectively prevent the collapse and destruction of wooden structures, and gain precious rescue time when a fire occurs. The facile top‐down chemical delignification and densification process enabling both substantially enhances fire‐retardant performance and mechanical robustness represents a promising direction toward fire‐retardant and high‐strength structural materials.

Overview

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Integrity signals

Registry

Crossref · 10.1002/adfm.201807444

Cites

1 of 1 references verified0 citation errors · 0 not checkable

Statistics

Verification

Claims the paper makes

The claims and statistics of this paper haven’t been checked yet.

Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.

A few free checks a day · papers already verified open instantly · results are public

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

The self-check needs the paper’s full text.

Citations

Cites

Show all 1 references

Cited by

See all 232

Metadata

Authors
Gan, W., Chen, C., Wang, Z., Song, J., Kuang, Y., He, S., Mi, R., Sunderland, P. B., & Hu, L.
Venue
Advanced Functional Materials
Publisher
Wiley
Published
2019-02-15
Volume
29
Issue
14
ISSN
  • 1616-301X (ISSN-L)
  • 1616-3028
OpenAlex
W2912574923
Cited by
232
References
1
FWCI
9.08
Type
journal article
Language
en
Open access
closed

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review

How to cite

Cite CoChat for the checks on this page, and the paper for its own findings.

This page
CoChat. (2026). Citation check: Dense, Self‐Formed Char Layer Enables a Fire‐Retardant Wood Structural Material. https://app.cochat.ai/papers/10.1002/adfm.201807444
The paper
Gan, W., Chen, C., Wang, Z., Song, J., Kuang, Y., He, S., Mi, R., Sunderland, P. B., & Hu, L. (2019). Dense, Self‐Formed Char Layer Enables a Fire‐Retardant Wood Structural Material. Advanced Functional Materials. https://doi.org/10.1002/adfm.201807444

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.