Direct Measurement of Electronic Band Structure in Single Quantum Dots of Metal Chalcogenide Composites
Bibliographic record
Abstract
Metal chalcogenide quantum dots (QDs) are among the most promising materials as light harvesters in all-inorganic systems for applications in solar cells and production of solar fuels. The electronic band structure of composite QDs formed by lead and cadmium chalcogenides directly grafted on highly oriented pyrolytic graphite surfaces through successive ionic layer absorption and reaction is investigated. Atomic force microscopy and Kelvin probe force microscopy (KPFM) are applied to investigate PbS, CdS, and PbS/CdS QD systems. The variation of the surface potential of individual QDs is measured, investigating the evolution of the electronic band structure as a function of QD size and composition. A shift of the Fermi level toward more negative values occurs when QD size is increased. The shift is more pronounced in CdS than in PbS, while the composite PbS/CdS exhibits an intermediate behavior. The calculated shift is in good agreement with the experiments. These results highlight the ability of KPFM to directly measure the electronic band structure in individual QDs of metal chalcogenide composites. This feature regulates charge dynamics in composite systems, thereby affecting device performance. This work provides valuable insights for applications in several fields, in which charge injection plays a major role.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".