MétaCan
Menu
Back to cohort

Carbon-Polyol Coating Using Carbon Produced From Palm Kernel Cake (PKC)

2011· article· en· W1819696192 on OpenAlexvenueno aff
M. H. Selamat, Athirah Ahmad

Bibliographic record

VenueAdvances in natural science/Advances in natural sciences · 2011
Typearticle
Languageen
FieldMaterials Science
TopicNatural Fiber Reinforced Composites
Canadian institutionsnot available
Fundersnot available
KeywordsPalm kernelPolyolMaterials scienceCarbon fibersCoatingComposite materialPolyurethaneChemistryFood sciencePalm oilComposite number

Abstract

fetched live from OpenAlex

In our quest to create awareness in using renewable, sustainable natural resources and efficient waste management, palm kernel cake (PKC) which is the waste from the palm industries was used in preparation of Carbon-polyol coating. PKC was subjected to pyrolisis process and the carbon residue obtained was used as a black pigment. In this work modified Polyol was used as the binder for its ideal properties as vehicle to produce good opacity of paint. Various carbon-polyol dispersant with different weight compositions (wt%) of carbon prepared and tested against its respective rheological properties in order to determine ideal paint/ink system. Two different types of paper material (Brown paper B and white paper W) were chosen as a substrate and characterised. Each of the paper was then proofed with Carbon-polyol using palm kernel carbon (PKC) and commercial carbon (PURE_C). Lightfastness test was carried out on the paper specimens and the results on the total colour difference (dE) are obtained. It was found that the total colour change (dE) in specimens using brown paper (B) coated with Carbon polyol coating using carbon derived from palm kernel carbon (PKC_B) and the commercial carbon (PURE_C_B) is within 10%. The other two specimens, using white paper (PKC_W and PURE_C_W), the total colour change (dE) is 17%. It is expected that the coating system has the potential application in paint or ink. Key words: Carbon-Polyol; Palm Kernal Cake (PKC); Colourant; Lightfast; Coating

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.004

Distilled classifier scores by category (both heads)

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)0.0010.000

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 head0.018
GPT teacher head0.295
Teacher spread0.277 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2011
Admission routes1
Has abstractyes

Explore more

Same venueAdvances in natural science/Advances in natural sciencesSame topicNatural Fiber Reinforced CompositesFrench-language works237,207