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Record W2044319069 · doi:10.1155/2015/630905

Visualizing the Microdistribution of Zinc Borate in Oriented Strand Board Using X-Ray Microcomputed Tomography and SEM-EDX

2015· article· en· W2044319069 on OpenAlexafffund
Philip D. Evans, Vinicius Lube, Holger Averdunk, Ajay Limaye, Michael L. Turner, Andrew Kingston, Tim J. Senden

Bibliographic record

VenueJournal of Composites · 2015
Typearticle
Languageen
FieldEngineering
TopicWood Treatment and Properties
Canadian institutionsUniversity of British Columbia
FundersUniversity of British ColumbiaFPInnovationsAustralian National University
KeywordsZincZinc borateOriented strand boardMaterials scienceComposite materialLeaching (pedology)BoronBiocideMetallurgyChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Oriented strand board (OSB) is an important wood composite used in situations where fungal decay and termite attack can occur. To counter these threats, powdered zinc borate biocide is commonly added to OSB. The effectiveness of biocides depends on their even distribution within composites and resistance to leaching, but little is known about the distribution of zinc borate in OSB. Zinc is denser than wood and it should be possible to map its distribution in OSB using X-ray micro-CT. We test this hypothesis and chemically register zinc in OSB using SEM-EDX. Zinc borate particles aggregated at the wood-adhesive interface in OSB, creating interrupted lines of zinc oriented in the x - y plane. Zinc borate particles were also found in the lumens of wood cells. Zinc was distributed throughout OSB, although slightly less was present in the core of the composite than in surface layers. A network of zinc remained in OSB after leaching in water. The resistance of zinc to leaching may be due to its incorporation in glue-lines within OSB, in addition to its low water-solubility. We conclude that X-ray micro-CT is a powerful tool for studying the distribution of zinc in OSB and other wood composites containing zinc borate.

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 score0.034
Threshold uncertainty score0.265

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 head0.018
GPT teacher head0.234
Teacher spread0.216 · 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

Citations17
Published2015
Admission routes2
Has abstractyes

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