MétaCan
Menu
Back to cohort
Record W4404522504 · doi:10.1515/ntrev-2024-0119

Structural performance of boards through nanoparticle reinforcement: An advance review

2024· article· en· W4404522504 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.

Bibliographic record

VenueNanotechnology Reviews · 2024
Typearticle
Languageen
FieldMaterials Science
TopicAdvanced Cellulose Research Studies
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsReinforcementNanoparticleMaterials scienceNanotechnologyComposite material

Abstract

fetched live from OpenAlex

Abstract Under the turbulence of global change, the production of boards has been influenced by the rising demand and price of wood-based materials. To improve the structural performance of boards, reinforcement materials have been added, such as nanoparticles. The purpose of this review is to explore the application of nanomaterials, including nano-SiO 2 , nano-Al 2 O 3 , nano-ZnO, nano-Fe 2 O 3 , nano-cellulose, nano-lignin, and nano-chitosan, to evaluate the physical and mechanical properties of particleboards. These nanoparticles have demonstrated their ability to reduce formaldehyde emissions, enhance the dimensional stability, bending strength, bending stiffness, fire resistance, and resistance to thermal conductivity in board production. For example, the addition of nano-SiO 2 , known for its hydrophilicity, attracts and holds water molecules and acts as a thermal barrier due to its high melting point and low thermal conductivity. In contrast, nano-Al 2 O 3 is known for its high compressive strength (up to 3 GPa), hardness strength (9 Mohs scale), and high thermal conductivity, which helps to dissipate heat more effectively. This comprehensive evaluation brings together recent advances in producing particleboards and medium density fiberboard reinforced with nanoparticles, which are essential for future research and industry applications. The study emphasizes how innovative nanoparticles can contribute to sustainable urban development and construction practices, reduce deforestation, preserve natural habitats, and provide affordable housing. The research indicates that nanoparticle boards meet ( e.g. , nanoclay and nanoalumina panels) and in some cases exceed the minimum requirement for general-purpose panels set standards such as the ANSI/A208.1-1999, including water absorption of 8%, thickness swelling of 3% and EN 312 for the bending strength (15–16 MPa) and bending stiffness (2.2–2.4 GPa) for P4 and P6 boards, respectively. These results support the transformative power of nanomaterials in promoting a more sustainable and future solution for boards in the building construction industry.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.334
Threshold uncertainty score0.728

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.001
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 head0.041
GPT teacher head0.354
Teacher spread0.313 · 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