Photocatalytic Synergy Between α‐Bi<sub>2</sub>O<sub>3</sub> Nanosphere and Spindle MIL‐88A for Gas‐Phase CO<sub>2</sub> Reduction
Bibliographic record
Abstract
Abstract Visible light‐active photocatalysts play a crucial role in gas‐phase photocatalytic CO 2 reduction, offering significant potential for sustainable energy conversion. Herein, we present the synthesis of spindle‐shaped Iron (Fe)‐based metal‐organic framework (MOF) MIL‐88 A, coupled with distinct α‐Bi 2 O 3 nanospheres. The α‐Bi 2 O 3 /MIL88A heterostructure is formed by interacting opposite surface charges, enhancing visible‐light absorption and efficient interfacial charge‐carrier separation. Such low‐cost photocatalysts have a 1.75 eV band gap and demonstrate enhanced efficacy in converting CO 2 to CO, CH 4 , and H 2 in water without using any sacrificial agents or noble metals compared to pristine MIL88A. In addition, in‐situ Electron Spin Resonance (ESR) analyses revealed that these unique catalysts combination promoted enhanced interfacial charge dynamics, creating efficient trapping sites for photogenerated carriers. Further, in‐situ Diffuse Reflectance Infrared Fourier Transfer Spectroscopy (DRIFTS) investigation elucidates the plausible reaction mechanism and provides an effective methodology for catalyst screening for CO 2 photoreduction. This study offers an effective approach for synthesizing the earth‐abundant heterostructure from metal oxide and low‐cost MOFs, enhancing photocatalytic activity for sustainable carbon dioxide conversion into invaluable chemicals.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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; both teacher heads agree on what is shown here.
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".