Defect Passivation and Surface Modification for Efficient and Stable Organic-Inorganic Hybrid Perovskite Solar Cells and Light-Emitting Diodes
Bibliographic record
Abstract
Defect passivation and surface modification of perovskite semiconductors play a key role in achieving highly efficient and stable perovskite solar cells (PSCs) and light-emitting diodes (LEDs). This dissertation describes three novel strategies for such defect passivation and surface modification. In the first strategy, we demonstrate a facile approach using inorganic perovskite quantum dots (QDs) to supply bulk- and surface-passivation agents to combine high power conversion efficiency (PCE) with high stability in CH3NH3PbI3 (MAPbI3) inverted PSCs. This strategy utilizes inorganic perovskite QDs to distribute elemental dopants uniformly across the MAPbI3 film and attach ligands to the film’s surface. Compared with pristine MAPbI3 films, MAPbI3 films processed with QDs show a reduction in tail states, smaller trap-state density, and an increase in carrier recombination lifetime. The strategy results in reduced voltage losses and an improvement in PCE from 18.3% to 21.5%, which is among the highest efficiencies for MAPbI3 devices. The devices maintain 80% of their initial PCE under 1-sun continuous illumination for 500 h and show improved thermal stability. In the second strategy, we reduce the efficiency gap between the inverted PSCs and regular PSCs using a trace amount of surface-anchoring, long-chain alkylamine ligands (AALs) as grain and interface modifiers. We show that long-chain AALs suppress nonradiative carrier recombination and improve the optoelectronic properties of mixed-cation mixed-halide perovskite films. These translate into a certified stabilized PCE of 22.3% (23.0% PCE for lab-measured champion devices). The devices operate for over 1000 hours at the maximum power point (MPP), under simulated AM1.5 illumination, without loss of efficiency. Finally, we report a strategy to passivate Cl vacancies in mixed halide perovskite (MHP) QDs using non-polar-solvent-soluble organic pseudohalide (n-dodecylammonium thiocyanate (DAT)), enabling blue MHP LEDs with enhanced efficiency. Density-function-theory calculations reveal that the thiocyanate (SCN-) groups fill in the Cl vacancies and remove deep electron traps within the bandgap. DAT-treated CsPb(BrxCl1-x)3 QDs exhibit near unity (~100%) photoluminescence quantum yields; and their blue (~470 nm) LEDs are spectrally stable with an external quantum efficiency (EQE) of 6.3% – a record for perovskite LEDs emitting at the 460-480 nm range relevant to Rec. 2020 display standards.
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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".