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Record W4281563340 · doi:10.1002/cjce.24472

Value‐added products from waste: Slow pyrolysis of used polyethylene‐lined paper coffee cup waste

2022· article· en· W4281563340 on OpenAlexaffvenue
Heejin Lee, Sadegh Papari, Giulio Bernardini, Riccardo Gallorini, Luca Rosi, Franco Berruti

Bibliographic record

VenueThe Canadian Journal of Chemical Engineering · 2022
Typearticle
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsWestern University
Fundersnot available
KeywordsPyrolysisLevoglucosanCharPyrolysis oilAdsorptionAcetic acidActivated carbonBiocharHeat of combustionChemistryWaste managementYield (engineering)Chemical engineeringOrganic chemistryPulp and paper industryMaterials scienceNuclear chemistryComposite material

Abstract

fetched live from OpenAlex

Abstract The objectives of this study were to examine how to recycle cup waste efficiently and effectively and to determine if cup waste can be converted into liquid, solid, and gas value‐added products by slow pyrolysis. The characteristics and potential utilizations of the pyrolysis products were investigated. The study included the effects of temperature, heating rate, and different feedstocks. The yield of pyrolysis oil derived from cup waste increased from 42% at 400°C to 47% at 600°C, while the yield of char decreased from 26% at 400°C to approximately 20% at 600°C. Acetic acid and levoglucosan were identified as the main components of the pyrolysis oil. The char obtained at 500°C was physically activated at 900°C for 3 h with CO 2 . The adsorption capacity of the activated char was investigated with model compounds, such as methyl orange, methylene blue, ibuprofen, and acetaminophen. The results showed that the adsorption capacity of the activated char was similar to that of commercial activated carbon produced from peat. The higher heating value of the produced gas stream calculated at 400°C was 19.59 MJ/Nm 3 . Also, conventional slow pyrolysis (CSP) and microwave‐assisted pyrolysis (MAP) technologies were compared to determine the differences in terms of products yields, composition and characteristics of the pyrolysis oil, and their potential applications. The CSP yields higher liquid products than MAP. Also, the pyrolysis oil obtained from the CSP had significantly more levoglucosan and acetic acid compared to that of the MAP.

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 score0.093
Threshold uncertainty score0.515

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 science0.0010.000
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 head0.007
GPT teacher head0.175
Teacher spread0.168 · 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
Published2022
Admission routes2
Has abstractyes

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