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Record W4387392409 · doi:10.1002/anie.202313174

Entropy Confinement Promotes Hydrogenolysis Activity for Polyethylene Upcycling

2023· article· en· W4387392409 on OpenAlexaff
Qingyun Kang, Mingyu Chu, Panpan Xu, Xuchun Wang, Shiqi Wang, Muhan Cao, Oleksandr Ivasenko, Tsun‐Kong Sham, Qiao Zhang, Qiming Sun, Jinxing Chen

Bibliographic record

VenueAngewandte Chemie International Edition · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicMicroplastics and Plastic Pollution
Canadian institutionsWestern University
Fundersnot available
KeywordsCatalysisPolymerHydrogenolysisMaterials scienceMesoporous materialAdsorptionPolyethyleneChemical engineeringNanoparticleNanotechnologyChemistryOrganic chemistryComposite material

Abstract

fetched live from OpenAlex

Abstract Chemical upcycling that catalyzes waste plastics back to high‐purity chemicals holds great promise in end‐of‐life plastics valorization. One of the main challenges in this process is the thermodynamic limitations imposed by the high intrinsic entropy of polymer chains, which makes their adsorption on catalysts unfavorable and the transition state unstable. Here, we overcome this challenge by inducing the catalytic reaction inside mesoporous channels, which possess a strong confined ability to polymer chains, allowing for stabilization of the transition state. This approach involves the synthesis of p‐Ru/SBA catalysts, in which Ru nanoparticles are uniformly distributed within the channels of an SBA‐15 support, using a precise impregnation method. The unique design of the p‐Ru/SBA catalyst has demonstrated significant improvements in catalytic performance for the conversion of polyethylene into high‐value liquid fuels, particularly diesel. The catalyst achieved a high solid conversion rate of 1106 g ⋅ g Ru −1 ⋅ h −1 at 230 °C. Comparatively, this catalytic activity is 4.9 times higher than that of a control catalyst, Ru/SiO 2 , and 14.0 times higher than that of a commercial catalyst, Ru/C, at 240 °C. This remarkable catalytic activity opens up immense opportunities for the chemical upcycling of waste plastics.

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 score0.066
Threshold uncertainty score0.999

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)0.0020.000

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 head0.016
GPT teacher head0.250
Teacher spread0.234 · 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

Citations65
Published2023
Admission routes1
Has abstractyes

Explore more

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