Photothermal Catalytic Polyester Upcycling over Cobalt Single‐Site Catalyst
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.
Bibliographic record
Abstract
Abstract Photothermal catalytic conversion of waste plastics into fuels and/or feedstocks using renewable solar energy can achieve solar‐to‐chemical conversion, resource sustainability, and environmental remediation simultaneously. However, the construction of photothermal catalysts with strong light absorption and high catalytic activity remains a great challenge. In this work, integrated cobalt single‐site catalysts (Co SSCs), coupled with strong photothermal conversion, high catalytic activity, and stability, are employed to catalyze the glycolysis of polyesters. The unique coordination‐unsaturated CoO 5 single‐site can coordinate with the carbonyl groups in polyester, thus boosting the nucleophilic addition elimination processes. As a result, the space‐time yield of Co SSCs is an order of magnitude higher than that of general catalysts. In addition, the polyethylene terephthalate (PET) conversion and bis(2‐hydroxyethyl) terephthalate yield in photothermal catalysis are 5.4 and 6.6 times higher than those of thermal catalysis under the same conditions, which are contributed by the localized heating effect. Technical economic analysis shows that the recycling of 10 5 tons of waste PET by photothermal catalysis consumes 146.4 GW·h electrical energy and misses 7.44 × 10 4 tons of CO 2 emission. Therefore, a high‐efficient photothermal catalytic plastic recycling system is of great significance for waste plastic valorization.
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 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 | 0.000 | 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) | 0.035 | 0.001 |
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 it