Photochemically Cross-Linked Quantum Well Ligands for 2D/3D Perovskite Photovoltaics with Improved Photovoltage and Stability
Bibliographic record
Abstract
The deployment of perovskite solar cells will rely on further progress in the operating and ambient stability of active layers and interfaces within these materials. Low-dimensional perovskites, also known as perovskite quantum wells (PQWs), utilize organic ligands to protect the perovskite lattice from degradation and offer to improve device stability; combining 2D and 3D perovskites in heterostructures has been shown to take advantage of the high efficiency of the majority 3D active layers and combine it with the improved stability of a thin 2D top layer. Prior PQWs have relied on relatively weak interwell van der Waals bonding between hydrophobic organic moieties of the ligands. Here we instead use the ligand 4-vinylbenzylammonium to form well-ordered PQWs atop a 3D perovskite layer. The ligand's vinyl group is activated using UV light which photochemically forms new covalent bonds among PQWs. UV-cross-linked 2D/3D devices show improved operational stability as well as improved long-term dark stability in air: they retain 90% of their initial efficiency after 2300 h of dark aging compared to a retention of 20% of performance in the case of 3D films. The UV-cross-linked PQWs and 2D/3D interfaces reduce device hysteresis and improve the open-circuit voltages to values up to 1.20 V, resulting in more efficient devices (PCE of up to 20.4%). This work highlights the exploitation of the chemical reactivity of PQW ligands to tailor the molecular properties of PQW interfaces for improved stability and performance in 2D/3D perovskite photovoltaics.
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How this classification was reachedexpand
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 | 0.000 |
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 teacher head, 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".