Morphology-Dependent Charge-Separated Character in the Photoexcited States of the Photocatalytic Bismuth Oxyiodide Nanocrystals and Nanosheets: Implications for Photodynamic Therapy
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Bismuth oxyiodide (BiOI), a two-dimensional material, is well known for its photocatalytic and photovoltaic properties owing to its low bandgap, efficient charge separation, and suitable work function that facilitates various photocatalytic reactions. However, the performance of BiOI depends on the synthetic methods, as they dictate the growth directions and overall quality of the nanosheets or crystals produced. Herein, we investigated the morphology and the charge-separated character in the photoexcited states of the BiOI nanocrystals/sheets produced from alternative synthetic routes such as hydrothermal, ball milling, and hand grinding methods by using electroabsorption (E-A) spectroscopy. The optical band gaps, absorption, and E-A spectra of BiOI are shown to be sensitive to the synthetic method. The E-A spectra of BiOI nanocrystals/sheets embedded in poly(methyl methacrylate) (PMMA) matrix measured at the second harmonic of the applied field were simulated by using integral method analysis to estimate the changes in electric dipole moment and polarizability following photoexcitation. From the analysis, it is found that BiOI nanosheets prepared using a hand grinding method with a [001] orientation have much larger charge-separated character in the photoexcited states than those in the nanoparticles prepared from hydrothermal and ball milling methods with a [110] orientation, implying the excellent photoelectronic performance in BiOI nanosheets prepared by the hand grinding method in comparison with BiOI nanoparticles prepared by other methods. The present finding may open the gateway for the development of the specific BiOI material, which is suitable for photocatalysis and photodynamic therapy.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".