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Drying and heat treatment of bamboo: Cell collapse and restoration

2025· article· en· W4407306977 on OpenAlexafffund
Yeling Xia, Huijun Dong, Kate Semple, Jingda Huang, Wenbiao Zhang, Chunping Dai

Bibliographic record

VenueConstruction and Building Materials · 2025
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicBamboo properties and applications
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaZhejiang A and F University
KeywordsBambooMaterials scienceComposite materialForensic engineeringEngineering

Abstract

fetched live from OpenAlex

Bamboo is becoming a more competitive supplement material for timber due to its fast growth, high carbon sequestration rate, and superior strength compared to wood. Engineered bamboo manufacturing requires bamboo strips to be first carefully dried, heat treated, and restored for dimensional stability, bond-ability, and durability. This research is an in-depth examination of a typical industrial bamboo strip drying and treatment process at both macro and cellular scales. Unlike lumber, bamboo drying involves five successive lengthy steps: 1) pressurized steam treatment or ‘caramelization’, 2) primary drying, 3) ambient equalization, 4) steam restoration, and 5) secondary drying. Moisture content reduction and equalization take place predominantly during primary drying. In addition to normal shrinkage, low permeability of the thin-walled parenchyma cells with tiny pit connections makes bamboo highly susceptible to cell collapse. The combination of shrinkage and collapse resulted in three patterns of warping in strips: 1) longitudinal bowing, 2) cross-sectional cupping, and 3) differential edge distortion between nodes and internodes. Scanning electron microscopy (SEM) revealed collapse in parenchyma cells, with complex patterns in strip cross-sections governed by the cell locations relative to fiber bundles and inner or outer position in the culm wall. Cell collapse was greatest (43.6 %) near the inner wall, followed by the outer wall (24.1 %) and the middle region (17.3 %). Successful collapse restoration (94.3 %) occurred with steam treatment at 184°C for 80 minutes, while restoration at 100°C (used for wood) led to 88.5 % restoration. Extended steaming duration at 100°C was ineffective and led to more severe re-deformation. • Bamboo is susceptible to cell collapse due to its low permeability. • Bamboo drying process is lengthy to mitigate drying defeats. • Typical bamboo strip warping is characterized. • Distribution and severity of cell collapse are quantified. • Bamboo needs a higher restoration temperature than wood.

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.

How this classification was reachedexpand

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)0.000
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.044
Threshold uncertainty score0.119

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.014
GPT teacher head0.221
Teacher spread0.208 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations8
Published2025
Admission routes2
Has abstractyes

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