Optical Generation and Transport of Charges in Iron Pyrite Nanocrystal Films and Subsequent Injection into SnO<sub>2</sub>
Bibliographic record
Abstract
The low photovoltaic efficiency of iron pyrite-based solar cells is often related to the presence of sulfur deficiencies. In this paper surfur-rich iron pyrite nanocrystals (FeS 2 NCs) are synthesized by the hot injection method and deposited using layer by layer deposition. Optical absorption measurements show substantial sub-bandgap absorption, which is attributed to a sulfur-rich, thin surface layer. Microwave photoconductance measurements show very little signal of films with the original long ligands, while an approximately 100-fold higher signal is observed for films treated with FeCl 2 and 1,2-ethanedithiol (EDT) solutions. In mesoporous hybrid systems of FeS 2 /SnO 2 both sub-band-gap and above-band-gap photons lead to electron injection from FeS 2 into the SnO 2 conduction band. We explain these findings by proposing that pinning of the Fermi level by the surface layer leads to a downward band bending in the direction of the surface within the FeS 2 NC. Hence, photoexcited electrons will first move toward the shell where they relax into empty surface states. As the holes remain behind in the core of the nanocrystals, this results in a charge-separated state with a long lifetime. Interestingly, these surface electrons are able to migrate in the FeS 2 NP layer by interparticle tunneling and can still decay by injection into SnO 2 . Hence, our results indicate that SnO 2 is a suitable electron acceptor for FeS 2 . The long-lived charge-separated electrons and holes could be exploited efficiently in photodetectors.
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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".