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Record W3003469516 · doi:10.37358/mp.19.1.5119

Comparative Study on Plastic Materials as a New Source of Energy

2019· article· en· W3003469516 on OpenAlexfundno aff
Marius Constantinescu, Felicia Bucura, Roxana Elena Ionete, Violeta‐Carolina Niculescu, Eusebiu Ilarian Ionete, Anca Maria Zaharioiu, Simona Oancea, Marius Gheorghe Miricioiu

Bibliographic record

VenueMateriale Plastice · 2019
Typearticle
Languageen
FieldEngineering
TopicThermochemical Biomass Conversion Processes
Canadian institutionsnot available
FundersMinisterul Cercetării şi InovăriiCanada Excellence Research Chairs, Government of Canada
KeywordsPyrolysisHeat of combustionPolyethyleneDiesel fuelGas chromatographyLow-density polyethyleneFuel oilMaterials sciencePolystyrenePyrolysis–gas chromatography–mass spectrometryPolymerSulfurWaste managementFuel gasHigh-density polyethyleneChemical engineeringChemistryOrganic chemistryCombustionComposite materialChromatographyEngineering

Abstract

fetched live from OpenAlex

The pyrolysis can be an attractive way to reduce the plastic waste and, in the same time, to obtain alternative conventional fuels. In this respect, four polymers (low-density polyethylene, high-density polyethylene, propylene and polystyrene) were used in the pyrolysis process. The experiments were carried out by using an in-house plant, which allowed a maximum test temperature of 450 �C. The product oil and the derived gas from the pyrolysis process were evaluated using different techniques, such as elemental analysis (EA), calorimetry, gas chromatography (GC), gas chromatography coupled with mass spectrometry (GC-MS). Furthermore, for a comparative study two catalysts, zeolite and lignite, were also used for the pyrolysis process, in order to observe their influences on the final products. The higher heating value obtained for the oil was in the 40.17-45.35 MJ/kg range, acceptable for the use of these oil as an alternative fuel for diesel engine. Also, the sulphur content from the obtained oil does not cause environment problems, being lower than the allowed limits (10 mg/L). In addition, the pyrolysis derived gas was rich in hydrocarbons, conducting to a high calorific value, in the 73.42 - 121.18 MJ/kg range.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
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 score1.000

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)0.0020.001

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 head0.010
GPT teacher head0.214
Teacher spread0.204 · 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; both teacher heads agree on what is shown here.

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

Citations22
Published2019
Admission routes1
Has abstractyes

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