A Donor-Supply Electrode (DSE) for Colloidal Quantum Dot Photovoltaics
Bibliographic record
Abstract
The highest-performing colloidal quantum dot (CQD) photovoltaics (PV) reported to date have relied on high-temperature (>500°C) annealing of electron-accepting TiO2. Room-temperature processing reduces energy payback time and manufacturing cost, enables flexible substrates, and permits tandem solar cells that integrate a small-bandgap back cell atop a low-thermal-budget larger-bandgap front cell. Here we report an electrode strategy that enables a depleted-heterojunction CQD PV device to be fabricated entirely at room temperature. We find that simply replacing the high-temperature-processed TiO2 with a sputtered version of the same material leads to poor performance due to the low mobility of the sputtered oxide. We develop instead a two-layer donor-supply electrode (DSE) in which a highly doped, shallow work function layer supplies a high density of free electrons to an ultrathin TiO2 layer via charge-transfer doping. Using the DSE we build all-room-temperature-processed small-bandgap (1 eV) colloidal quantum dot solar cells having 4% solar power conversion efficiency and high fill factor. These 1 eV bandgap cells are suitable for use as the back junction in tandem solar cells. The DSE concept, combined with control over TiO2 stoichiometry in sputtering, provides a much-needed tunable electrode to pair with quantum-size-effect CQD films.
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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".