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Record W2806003610 · doi:10.5539/eer.v8n1p73

Studying and Evaluating Sustainable Materials for Converting Plastic Waste to Fuel

2018· article· en· W2806003610 on OpenAlexvenueno aff
Ameen Abdelrahman, Hassan A. Dosky, Hamdy F. M. Mohamed, Aly Moustafa Radwan, Asmaa S. Hamouda

Bibliographic record

VenueEnergy and Environment Research · 2018
Typearticle
Languageen
FieldMaterials Science
TopicFlame retardant materials and properties
Canadian institutionsnot available
Fundersnot available
KeywordsIncinerationWaste managementRenewable energyMaterials sciencePlastic wasteEnvironmental scienceRefuse-derived fuelProcess (computing)PolyethyleneProcess engineeringComposite materialComputer scienceEngineering

Abstract

fetched live from OpenAlex

Gasification is one of the most important solutions for plastic waste management. We researched the conversion of plastic waste to fuel using sustainable material (Nano Clay) modified with Nano transition metals (TiO2, MnO, and ZnO). This was processed in a fix bed reactor design. After studying the reaction mechanism of the gasification process, we evaluated the optimize (reactor temperature, reaction time and feeding ratio of the modified catalyst) on the gasification process with its application for the modified catalyst on the degradation of polyethylene high density(PEHD), other waste plastic to fuel (CH4, H2, and other light component gasses). This method can be used as an important resource for renewable energy (like generating electricity and clean fuel), rather than waste for landfills and the incineration process which is the main source of CO2 emissions.

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 score0.003

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 communication0.0000.001
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 head0.079
GPT teacher head0.327
Teacher spread0.249 · 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

Citations3
Published2018
Admission routes1
Has abstractyes

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