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Record W4411546047 · doi:10.1002/cjce.70020

Natural wax supported by microporous biochar to create a stable phase change material

2025· article· en· W4411546047 on OpenAlexafffundvenue
David Brassard, Jason R. Tavares

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2025
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsUniversity of OttawaPolytechnique Montréal
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsMicroporous materialBiocharWaxPhase changeMaterials scienceNatural (archaeology)Phase (matter)Phase-change materialChemical engineeringNanotechnologyChemistryComposite materialEngineering physicsEngineeringGeologyOrganic chemistryPyrolysis

Abstract

fetched live from OpenAlex

Abstract Energy storage, exploiting the latent heat of phase change materials, offers an efficient method to store and release heat. Initial developments of phase change materials and their containment targeted performance over environmental impact. This article presents a bio‐sourced, fully compostable, and biodegradable composite phase change material made from hardwood charcoal and beeswax. This material combines effective heat transfer performance with a significant focus on sustainable end‐of‐life waste management, especially when compared to traditional methods that rely on synthetic or heavily modified bio‐sourced phase change materials. We measured a beeswax uptake within charcoal's porous structure of up to 61.2%. This resulted in a composite with a latent heat enthalpy of 77.83 J g −1 , with cyclability tested up to 20 cycles without any reduction in performance. The process was scaled from millimetre‐scale particles up to centimetre‐scale particles with similar adsorption capacities. The Laplace–Young equation confirmed that adsorption of beeswax is mostly driven by a capillary pressure, of at least 2.2 × 10 4 N m −2 , caused by the naturally occurring porous structure of charcoal. These beeswax‐loaded charcoal particles could find applications for heat recovery in HVAC systems or in packed bed heat storage systems.

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 score0.005
Threshold uncertainty score0.698

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 head0.015
GPT teacher head0.249
Teacher spread0.234 · 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

Citations0
Published2025
Admission routes3
Has abstractyes

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