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Record W3165760318 · doi:10.1002/cssc.202100874

Current Developments in the Chemical Upcycling of Waste Plastics Using Alternative Energy Sources

2021· review· en· W3165760318 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueChemSusChem · 2021
Typereview
Languageen
FieldEnvironmental Science
TopicRecycling and Waste Management Techniques
Canadian institutionsUniversité LavalInstitut National de la Recherche Scientifique
FundersSingapore National Academy of ScienceAgency for Science, Technology and ResearchNational Research Foundation
KeywordsIncinerationEnvironmentally friendlyWaste managementPyrolysisCircular economyEnvironmental scienceMaterials scienceEngineering

Abstract

fetched live from OpenAlex

Abstract The management of plastics waste is one of the most urgent and significant global problems now. Historically, waste plastics have been predominantly discarded, mechanically recycled, or incinerated for energy production. However, these approaches typically relied on thermal processes like conventional pyrolysis, which are energy‐intensive and unsustainable. In this Minireview, some of the latest advances and future trends in the chemical upcycling of waste plastics by photocatalytic, electrolytic, and microwave‐assisted pyrolysis processes are discussed as more environmentally friendly alternatives to conventional thermal reactions. We highlight how the transformation of different types of plastics waste by exploiting alternative energy sources can generate value‐added products such as fuels (H 2 and other carbon‐containing small molecules), chemical feedstocks, and newly functionalized polymers, which can contribute to a more sustainable and circular economy.

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.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Other design · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.997
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
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 head0.075
GPT teacher head0.339
Teacher spread0.263 · 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