MOF-Templated Metal Oxides Sensitized with Quantum Dots Heterojunction for Efficient Solar Fuels Generation
Bibliographic record
Abstract
The separation and transport of photogenerated charges carriers are two of the most crucial factors that determine the overall efficiency of photoelectrochemical (PEC) systems. Various strategies have been exploited for achieving efficient charge separation and transfer. Among them, the design of semiconductor heterojunction has been shown to be one of the most effective approaches. Metal oxides, such as TiO2, are the among the most common materials for water splitting. However, the control of phase alignment and the interface structure remains a challenge. A promising solution is to use a template approach by employing metal-organic frameworks (MOF) which are of broad interest as a new class of organic-inorganic hybrid materials and have been intensely exploited in various fields due to their unique physical and chemical properties. Furthermore, common metal oxides, such TiO2 or NiO have limited absorption of sunlight due to their large intrinsic band gap (i.e. TiO2 anatase: 3.2 eV) which hinders effective use in solar water splitting. To extend the absorption range of the MOF-templated metal oxides in the visible and near-infrared range, we employed metal chalcogenide QDs as sensitizers. In this presentation, for example, we explore a simple metal organic framework (MOF)-derived synthesis to obtain a controlled mixed-phase (anatase and rutile) of TiO2 nanoparticles, which retain the MOF crystal morphology. After sensitization with core@shell CdSe@CdS QDs, the mixed-phase TiO2 film exhibited a remarkable photocurrent of 10.72 mA/cm2 and long-term stability, with a retained value of more than 78.1% after two hours. Compared with commercial TiO2 films, the MOF-derived TiO2 film sensitized by core-shell CdSe@CdS QDs, showed an enhanced PEC device stability of +42.1% and PEC performance of +47.6%. The enhanced performance is due to the presence of mixed rutile/anatase phases, that creates a favorable band energy alignment for the separation of the photogenerated charges. The proposed photoanode based on MOF-derived metal oxide is an efficient strategy to improve the efficiency of the heterojunction-based PEC system for hydrogen generation. Furthermore, the combined use of QDs can extend the absorption range exploiting a larger part of the sun spectrum. Figure 1
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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".