A Chemically Orthogonal Hole Transport Layer for Efficient Colloidal Quantum Dot Solar Cells
Bibliographic record
Abstract
Colloidal quantum dots (CQDs) are of interest in light of their solution-processing and bandgap tuning. Advances in the performance of CQD optoelectronic devices require fine control over the properties of each layer in the device materials stack. This is particularly challenging in the present best CQD solar cells, since these employ a p-type hole-transport layer (HTL) implemented using 1,2-ethanedithiol (EDT) ligand exchange on top of the CQD active layer. It is established that the high reactivity of EDT causes a severe chemical modification to the active layer that deteriorates charge extraction. By combining elemental mapping with the spatial charge collection efficiency in CQD solar cells, the key materials interface dominating the subpar performance of prior CQD PV devices is demonstrated. This motivates to develop a chemically orthogonal HTL that consists of malonic-acid-crosslinked CQDs. The new crosslinking strategy preserves the surface chemistry of the active layer beneath, and at the same time provides the needed efficient charge extraction. The new HTL enables a 1.4× increase in charge carrier diffusion length in the active layer; and as a result leads to an improvement in power conversion efficiency to 13.0% compared to EDT standard cells (12.2%).
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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".