14.1% CsPbI<sub>3</sub> Perovskite Quantum Dot Solar Cells via Cesium Cation Passivation
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Surface manipulation of quantum dots (QDs) has been extensively reported to be crucial to their performance when applied into optoelectronic devices, especially for photovoltaic devices. In this work, an efficient surface passivation method for emerging CsPbI 3 perovskite QDs using a variety of inorganic cesium salts (cesium acetate (CsAc), cesium idodide (CsI), cesium carbonate (Cs 2 CO 3 ), and cesium nitrate (CsNO 3 )) is reported. The Cs‐salts post‐treatment can not only fill the vacancy at the CsPbI 3 perovskite surface but also improve electron coupling between CsPbI 3 QDs. As a result, the free carrier lifetime, diffusion length, and mobility of QD film are simultaneously improved, which are beneficial for fabricating high‐quality conductive QD films for efficient solar cell devices. After optimizing the post‐treatment process, the short‐circuit current density and fill factor are significantly enhanced, delivering an impressive efficiency of 14.10% for CsPbI 3 QD solar cells. In addition, the Cs‐salt‐treated CsPbI 3 QD devices exhibit improved stability against moisture due to the improved surface environment of these QDs. These findings will provide insight into the design of high‐performance and low‐trap‐states perovskite QD films with desirable optoelectronic properties.
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.
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 | 0.001 |
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 it