Manipulation of electronic band structure by doping colloidal gallium oxide nanocrystals and its impact on photocatalysis
Bibliographic record
Abstract
Semiconductor photocatalyst have been of interest due to its robust nature, non-selectivity, low toxicity, and high tunability. Its various applications such as water splitting, water purification, anti-microbial, etc make this a desirable class of material to explore. However, there are defects in semiconductors that may impact the rate of photocatalysis. This study aims to illuminate the role of defects in photocatalysis. \n\tFor this study, the defect nature of γ- Ga2O3 was manipulated by doping the crystal structure with indium acetylacetonate (In(acac)3) or zinc nitrate (Zn(NO3)2) during colloidal synthesis in oleylamine. The electronic structure was analyzed to determine the correlation with photocatalysis using rhodamine-590 (Rh-590) as a model reactant. These results demonstrate that dopants would decrease the wide band gap of γ- Ga2O3 but maintain the defect spinel structure up to 15%. However, different dopants impact defects differently, which was reflected in photoluminescence (PL) emission spectra and the fast regime in time-resolved PL measurements. PL emission was derived from the recombination of the donor and acceptor pairs (DAP). Doping with In3+ has a maximum PL red shift of 24 nm, while doping with Zn2+ has a maximum PL red shift of 9 nm. This red shift indicates an increase in DAP distance and/or a decrease in defect concentration. Time resolved PL measurements using a TCSPC method with a 200 ns measurement range demonstrates that doping with 15% indium would decrease the average lifetime (LT) from 11.0 ± 0.3 ns to 3.4 ± 0.4 ns, while doping with 15% zinc would increase the LT to 15.1 ± 0.4 ns. Therefore, there was a positive correlation between the average LT and the rate constant derived from photocatalysis with a critical value ca. 8 ns where the apparent rate constant was not impacted from further increasing LT. \n\tIn conclusion, there is a potential to manipulate the electronic structure using dopants to impact photocatalysis. In addition, synthesis of Ga2-xMxO3 (M=In3+ or Zn2+) was successfully synthesized using a colloidal synthesis method. A relationship can also be developed between the average LT calculated from time-resolved PL and the apparent rate constant from the photocatalytic degradation of a model reactant.
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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 | 0.000 | 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) | 0.000 | 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".