Remote Molecular Doping of Colloidal Quantum Dot Photovoltaics
Bibliographic record
Abstract
In recent years colloidal quantum dot (CQD) photovoltaics have developed rapidly because of novel device architectures and robust surface passivation schemes. Achieving controlled net doping remains an important unsolved challenge for this field. Herein we present a general molecular doping platform for CQD solids employing a library of metal–organic complexes. Low effective ionization energy and high electron affinity complexes are shown to produce n- and p-doped CQD solids. We demonstrate the obvious advantage in solar cells by p-doping the CQD absorber layer. Employing photoemission spectroscopy, we identify two doping concentration regimes: lower concentrations lead to efficient doping, while higher concentrations also cause large surface dipoles creating energy barriers to carrier flow. Utilizing the lower concentration regime, we remove midgap electrons leading to 25% enhancement in the power conversion efficiency relative to undoped cells. Given the vast number of available metal–organic complexes, this approach opens new and facile routes to tuning the properties of CQDs for various applications without necessarily resorting to new ligand chemistries.
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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".