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Record W1989536840 · doi:10.1080/02773810903477621

Photoprotection of Wood Using Polyester-Type UV-Absorbers Derived from the Reaction of 2-hydroxy-4(2,3-epoxypropoxy)-benzophenone with Dicarboxylic Acid Anhydrides

2010· article· en· W1989536840 on OpenAlexaff
Philip D. Evans, Mohammed Jahangir A. Chowdhury

Bibliographic record

VenueJournal of Wood Chemistry and Technology · 2010
Typearticle
Languageen
FieldEngineering
TopicLignin and Wood Chemistry
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsPhthalic anhydrideBenzophenonePolyesterSuccinic anhydrideChemistryMaleic anhydridePolymer chemistryPhthalic acidFourier transform infrared spectroscopyOrganic chemistryMaterials scienceChemical engineeringCopolymerPolymer

Abstract

fetched live from OpenAlex

Abstract Polyester-type UV absorbers were created by reacting the epoxy-functionalized UV absorber 2-hydroxy-4(2,3-epoxypropoxy)-benzophenone (HEPBP) with maleic, phthalic, or succinic anhydride. The ability of the UV absorbers to photostabilize wood was then examined. Fourier transform infra-red (FTIR) spectroscopy confirmed that HEPBP reacted with phthalic anhydride to create a polyester that preserved the UV-absorbing benzophenone group. There was less evidence that the polyester was formed when HEPBP was reacted with maleic or succinic anhydride. HEPBP-phthalic anhydride was the most effective UV absorber at photostabilising wood. This UV absorber showed increased UV absorption around 270 nm, formed a leach-resistant film at wood surfaces and was able to restrict both weight and tensile strength losses of thin wood veneers during accelerated weathering, unlike chromium trioxide and a UV absorber-hindered amine light stabilizer. We conclude that polymeric polyester-type UV absorbers show promise as a way of photostabilizing wood and briefly discuss how more effective systems could be developed in future.

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 score0.001
Threshold uncertainty score0.565

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 integrity0.0000.001
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 head0.005
GPT teacher head0.187
Teacher spread0.182 · 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

Citations20
Published2010
Admission routes1
Has abstractyes

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