Highly stable photoelectrochemical cells for hydrogen production using a SnO<sub>2</sub>–TiO<sub>2</sub>/quantum dot heterostructured photoanode
Bibliographic record
Abstract
Photoelectrochemical (PEC) water splitting implementing colloidal quantum dots (QDs) as sensitizers is a promising approach for hydrogen (H2) generation, due to the QD's size-tunable optical properties. However, the challenge of long-term stability of the QDs is still unresolved. Here, we introduce a highly stable QD-based PEC device for H2 generation using a photoanode based on a SnO2-TiO2 heterostructure, sensitized by CdSe/CdS core/thick-shell "giant" QDs. This hybrid photoanode architecture leads to an appreciable saturated photocurrent density of ∼4.7 mA cm-2, retaining an unprecedented ∼96% of its initial current density after two hours, and sustaining ∼93% after five hours of continuous irradiation under an AM 1.5G (100 mW cm-2) simulated solar spectrum. Transient photoluminescence (PL) measurements demonstrate that the heterostructured SnO2-TiO2 photoanode exhibits faster electron transfer compared with the bare TiO2 photoanode. The lower electron transfer rate in the TiO2 photoanode can be attributed to slow electron kinetics in the ultraviolet regime, revealed by ultrafast transient absorption spectroscopy. Graphene microplatelets were further introduced into the heterostructured photoanode, which boosted the photocurrent density to ∼5.6 mA cm-2. Our results demonstrate that the SnO2-TiO2 heterostructured photoanode holds significant potential for developing highly stable PEC cells.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".