Synergistic Effects of Bipolar Additives on Grain Boundary-Mediated Charge Transport for Efficient Carbon-Based Inorganic Perovskite Solar Cells
Bibliographic record
Abstract
Carbon-based all-inorganic CsPbI x Br 3– x perovskite solar cells offer high stability against heat and humidity and a suitable band gap for tandem and semitransparent photovoltaics. In CsPbI x Br 3– x perovskite films, the defects at grain boundaries (GBs) cause charge trapping, reducing the efficiency of the cell. Electronic deactivation of GB has been a conventional strategy to suppress the trapping, but at the cost of charge carrier transport through the boundaries. Here, we turn the GBs into benign charge transport pathways with the aid of bipolar charge transport semiconductors, namely, Ti 3 C 2 T X (MXene) and Spiro-OMeTAD, respectively. Thanks to the synergistic effects of both n- and p-type transport media, the charge transport is improved and balanced at the GBs. As a result, the cells achieve an efficiency of 12.7%, the highest among all low-temperature-processed carbon-based inorganic perovskite solar cells. Benign GBs also lead to enhanced light and aging stabilities. Our work demonstrates a proof-of-concept strategy of benign electronic modulation of GBs for solution-processed perovskite solar cells.
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".