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Record W2990088022 · doi:10.1177/0021998319888734

Influence of pyrolytic thermal history on olive pruning biochar and related epoxy composites mechanical properties

2019· article· en· W2990088022 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

VenueJournal of Composite Materials · 2019
Typearticle
Languageen
FieldMaterials Science
TopicFlame retardant materials and properties
Canadian institutionsOntario Tech University
Fundersnot available
KeywordsBiocharPyrolytic carbonMaterials scienceEpoxyPyrolysisComposite materialPruningThermosetting polymerFiller (materials)Carbon fibersIncinerationPulp and paper industryComposite numberWaste managementBotany

Abstract

fetched live from OpenAlex

Olive pruning is waste from olive cultivation and is generally disposed of through incineration. Olive pruning can, however, be salvaged by pyrolysis, which also produces an interesting carbon-based material known as biochar. Biochar has been proved as a suitable filler which improves the mechanical properties of epoxy composites. Despite this, literature has few studied focused on the relationship between biochar thermal history and the properties it induces in related biochar containing composites. In this work, we report a morphological analysis of biochar produced at different pyrolytic high treatment temperatures (400℃, 600℃, 800℃, and 1000℃) using different heating rates (5℃/min, 15℃/min, and 50℃/min). We investigate the effect of different biochar morphology on the biochar epoxy-related composites, proving the tuneability of the mechanical properties of composites according to the thermal history of the biochar employed.

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: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.816

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.197
Teacher spread0.184 · 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