Enhanced Production of Liquid Alkanes from Waste Polyethylene via the Electronic Effect‐Favored C<sub>secondary</sub>−C<sub>secondary</sub> Bond Cleavage
Bibliographic record
Abstract
Abstract Catalytic hydrogenolysis of polyethylene to liquid alkanes has drawn particular attention. However, it remains not very clear about the factors influencing the positions (internal Csecondary−Csecondary and terminal Csecondary−Cprimary bonds) of C−C bond cleavage. Here, we clarify the influence of Ru chemical state on the positions of C−C bond cleavage by designing two Ru/CeO2 catalysts with different Ru chemical states tuned by the metal‐support interaction. It is found that the positively charged Ru species favor the hydrogenolysis of the internal Csecondary−Csecondary bond, inhibiting methane production, because these Ruδ+ species enable the selective bonding with the internal Csecondary containing higher electron density through the electron‐donating effect of adjacent alkyl species instead of the terminal Cprimary. Furthermore, a simple Ru/CeO2−I catalyst with plenty of Ruδ+ species was designed and was efficient for the hydrogenolysis of real waste polyethylene plastics. This work would guide catalyst design to enhance the selective production of liquid alkanes.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".