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Record W4416197568 · doi:10.1016/j.jobab.2025.11.001

Sustainable transparent bamboo/W-VO2 composites for solar modulation and energy-efficient buildings

2025· article· en· W4416197568 on OpenAlexvenueno aff
Zhihan Li, Haibo Huang, Yuxiang Liu, Ying Wu, Ziyi Pan, Yan Qing, Lin Tian, Zeng-Yao Li, Xinpeng Zhao, Yiqiang Wu

Bibliographic record

VenueJournal of Bioresources and Bioproducts · 2025
Typearticle
Languageen
FieldMaterials Science
TopicTransition Metal Oxide Nanomaterials
Canadian institutionsnot available
FundersNational Key Research and Development Program of China
KeywordsBambooOpacityGlazingRenewable energyThermalPapermakingSolar energyComposite numberTransparency (behavior)Polylactic acid

Abstract

fetched live from OpenAlex

Energy-efficient buildings require sustainable materials that combine structural performance with advanced optical and thermal functionalities to minimize energy consumption and greenhouse gas emissions. Here, we reported a new strategy to develop biodegradable transparent bamboo with a dense and ordered structure, achieved through selective delignification followed by directional pressing to align cellulose nanofibrils. This process yielded large-scale transparent bamboo with remarkable mechanical strength, 78% optical transparency in the visible spectrum, and a high haze (> 90%) that ensured uniform daylight distribution and reduced reliance on artificial lighting. To further impart dynamic solar modulation, a thin polylactic acid film containing tungsten-doped vanadium dioxide (W-VO 2 ) nanoparticles was integrated onto the transparent bamboo substrate. The resulting thermochromic bamboo exhibited a solar modulation ability of 9.7% along with effective thermal regulation that lowered indoor heating loads in hot regions. By synergizing biodegradability, mechanical robustness, and active photothermal control, this transparent bamboo/W-VO 2 composite offered a sustainable and high-performance alternative to conventional glass, holding great promise for energy-efficient building applications.

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)0.001
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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.417

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.010
GPT teacher head0.234
Teacher spread0.223 · 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

Citations2
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Bioresources and BioproductsSame topicTransition Metal Oxide NanomaterialsFrench-language works237,207