Bio‐Inspired Cascade Photocatalysis on Fe Single‐Atom Carbon Nitride Upcycles Plastic Wastes for Effective Acetic Acid Production
Bibliographic record
Abstract
ABSTRACT Plastic imposes a critical threat to the environment, ecosystems, and human health because of the low utilization efficiency of plastics. Here, we demonstrate a sustainable, highly efficient cascade photocatalysis for upcycle plastics to value‐added acetic acid using Fe single‐atom catalysts (Fe@C 3 N 4 SAC) at ambient conditions. Inspired by Phanerochaete chrysosporium microbial, the defective Fe@C 3 N 4 SAC acts as a bifunctional cascade photocatalyst for both Fenton‐like and CO 2 reduction reactions. During the reaction, hydroxyl radicals (*OH) form and subsequently oxidize plastics into CO 2 intermediates. These CO 2 intermediates are then photo‐reduced to CH 3 COOH on the same catalyst via cascade photocatalysis. The mechanism is confirmed by in situ multimodal microscopy and spectroscopies, with density functional theory calculations. A state‐of‐art CH 3 COOH yield of 63.8 mg h −1 g cat −1 from PVC, 12.7 mg h −1 g cat −1 from PE, 5.4 mg h −1 g cat −1 from PET, and 5.3 mg h −1 g cat −1 from PP are directly obtained under AM1.5G solar irradiation and further validated under real sunlight (≈0.6 sun), achieving 5.6 mg h −1 g cat −1 from PET, using low‐cost Fe@C 3 N 4 SAC in a sealed reactor by enhancing the photon transport and utilization efficiency. The techno‐economic analysis shows it is promising to practically mitigate plastic based on broader social welfare assessments.
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 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".