MétaCan
Menu
Back to cohort
Record W4411858270 · doi:10.1016/j.pmatsci.2025.101529

Flame-retardant strategies for lignocellulose: recent progress and prospect

2025· article· en· W4411858270 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueProgress in Materials Science · 2025
Typearticle
Languageen
FieldMaterials Science
TopicFlame retardant materials and properties
Canadian institutionsUniversity of British Columbia
FundersChina Scholarship CouncilMitacsCanada Research Chairs
KeywordsFire retardantMaterials sciencePolymer scienceForensic engineeringComposite materialEngineering

Abstract

fetched live from OpenAlex

Lignocellulose offers significant promise as a renewable and environmentally sustainable material for construction, while its inherent combustibility poses a major challenge to its widespread application, especially in fire-sensitive environments. In this review, the combustion behavior of lignocellulose and the key mechanisms underlying its flame-retardant strategies are examined. Various classes of flame retardants (FRs), categorized based on the functional elements, are discussed in terms of their flame-retardant mechanisms and interactions with lignocellulosic substrates. Emerging approaches that integrate FRs are explored and compared, with a focus on enhancing flame resistance while minimizing their adverse effects on material properties. Finally, the review concludes with an outlook on current challenges and future research directions, shedding the light to develop more effective, durable, and sustainable flame-retardant solutions for lignocellulose-based materials.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.003
Scholarly communication0.0020.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.017
GPT teacher head0.291
Teacher spread0.274 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it