Constructing the Al deficiency in Si-O(H)-Al units based on Pt/ZSM-5 for enhanced hydrocracking of polyethylene into high-quality liquid fuel
Bibliographic record
Abstract
Hydrocracking catalysis is a controllable route to plastic waste upgrading. However, the mismatched acid site-driven C-C cleavage and C=C hydrogenation process on metal restrict the efficiency and selectivity in conventional metal/acid bi-functional catalyst. Herein, we introduce Al deficiency in Si-O(H)-Al structural units of Pt/zeolite socony mobil-5 (Pt/ZSM-5) through discharge driven reduction (DR) process to precisely control the ratio of metal to acid, achieving hydrocracking of low-density polyethylene (LDPE) waste at 270 °C with 87.7% conversion and liquid fuel (C5-C21) selectivity of 77.8%. Pair distribution function (PDF) and nuclear magnetic resonance (NMR) spectroscopy demonstrate the partial absent Al sites further resulting short-range local disorder Si-O(H)-Al. Upon pyridine infrared spectroscopy (Py-IR) and CO diffuse reflectance Fourier-transform infrared (CO DRIFT) analysis, the extraction of Al modulates Brønsted acid density of Pt/ZSM-5 with DR process (Pt/Z5DR), improves the interaction between Pt and ZSM-5 support, enhances the cationic of Pt. The metal-acid balance and electron-deficient Pt favor the matching speed of light olefins hydrogenation and the cracking of macromolecule intermediates. Moreover, density functional theory (DFT) calculations identify the thermodynamic stability of Pt/Z5DR and moderate adsorption capability towards light olefins. This work confirms the great potential of precisely controlled molar of metal to acid in metal/zeolite catalysts for LDPE upcycling, providing a viable path for dealing with PE plastic wastes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".