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Record W4401969605 · doi:10.1002/cjce.25472

Composite nanocapsules of phase change materials using a supercritical carbon dioxide (<scp>SC</scp>‐<scp>CO<sub>2</sub></scp>) assisted process

2024· article· en· W4401969605 on OpenAlexvenueno aff
Ida Palazzo, Gianluca Viscusi, Giuliana Gorrasi, Ernesto Reverchon

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2024
Typearticle
Languageen
FieldEngineering
TopicPhase Change Materials Research
Canadian institutionsnot available
FundersUniversità degli Studi di Salerno
KeywordsNanocapsulesSupercritical carbon dioxideSupercritical fluidCarbon dioxideComposite numberChemical engineeringMaterials scienceProcess (computing)Phase (matter)Phase changeNanotechnologyChemistryNanoparticleOrganic chemistryComposite materialComputer scienceEngineering physicsEngineering

Abstract

fetched live from OpenAlex

Abstract This work reports the production of polymeric nanocapsules of polymethyl methacrylate (PMMA)/phase change materials (PCM), using continuous supercritical emulsion extraction (SEE‐C). Five fatty acids (FAs) were tested: capric (CA), lauric (LA), myristic (MA), palmitic (PA), and stearic (SA) acid, using supercritical carbon dioxide (SC‐CO 2 ) operating at 80 bar and 38°C in a tower apparatus. The two fatty acids with lower molecular weight (CA and LA) were extracted by the supercritical solvent and capsules were not obtained. The other three FAs formed spherical, non‐coalescing nanocapsules characterized by mean diameters ranging between 134 and 252 nm, as shown by scanning electron microscope (SEM) images and dynamic light scattering (DLS) analysis, with a sharp particles size distribution and encapsulation efficiencies up to 99.8%. Differential scanning calorimetric analysis (DSC), thermogravimetric analysis (TGA) and derivative thermogravimetric analysis (DTG) analyses confirmed the successful encapsulation, allowing the measurement of the energy storage properties of produced capsules. Stability analysis performed over 5 months showed that the nanocapsules were stable in this time interval. Thermal cycles experiments confirmed the thermal stability of the capsules. The best performance was obtained for PA based nanocapsules, which showed a stability reduction of only 0.43% after 25 thermal cycles.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
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 score0.024
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.037
GPT teacher head0.277
Teacher spread0.240 · 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.

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

Citations1
Published2024
Admission routes1
Has abstractyes

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