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Record W4406727644 · doi:10.1002/anie.202422609

Ruthenium‐Catalyzed Deconstruction of Polyolefins: A Strategy to Up‐cycle Waste Polyethylene to Value‐Added Alkene

2025· article· en· W4406727644 on OpenAlexaff
Ganeshdev Padhi, Kishor V. Khopade, Nageswararao Moyilla, Raghavendrakumar Rangappa, Samir H. Chikkali, Nagaraju Barsu

Bibliographic record

VenueAngewandte Chemie International Edition · 2025
Typearticle
Languageen
FieldChemistry
TopicOrganometallic Complex Synthesis and Catalysis
Canadian institutionsUniversity of Toronto
FundersNational Chemical LaboratoryScience and Engineering Research BoardDepartment of Science and Technology, Ministry of Science and Technology, IndiaDepartment of Scientific and Industrial Research, Ministry of Science and Technology, India
KeywordsPolyethyleneDehydrogenationCatalysisAlkenePolyolefinRutheniumChemistryDifferential scanning calorimetryMetathesisPolymer chemistryOrganic chemistryAcyclic diene metathesisMaterials sciencePolymerPolymerization

Abstract

fetched live from OpenAlex

Synthesis of value-added products from post-consumer waste polyolefins is fascinating as well as challenging. Here we report ruthenium-catalyzed up-cycling of the polyethylene to long-chain alkene derivatives. The developed methodology mainly involves two steps i.e., dehydrogenation of polyethylene through hydrogen atom transfer and its metathesis using the HG-II catalyst. The dehydrogenation of polyethylene using ruthenium catalysis derived up to 3.38 %, of double bonds; with 90 % of the recovered polyolefin material. The obtained unsaturated polyethylene was subjected to cross-metathesis with ethylene using HG-II catalytic system. This resulted in the synthesis of predominantly dodecene (C12) derivatives, with 58 % selectivity, along with other derivatives of varying chain lengths. The overall reaction produced terminal and internal olefins in the ratio 1:0.8 respectively. The dehydrogenation of polyethylene and its deconstruction was confirmed by NMR spectroscopy, Gel Permeation Chromatography (GPC) and Differential Scanning Calorimetry (DSC). The origin of C12 selectivity has been demonstrated by control experiments. The scope of the methodology was extended to post-consumer waste polyethylene which gave high conversion to value-added dodecene derivatives as a major product.

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 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 score0.047
Threshold uncertainty score0.994

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)0.0070.000

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 head0.010
GPT teacher head0.259
Teacher spread0.248 · 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

Citations15
Published2025
Admission routes1
Has abstractyes

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