Impact of Tetrakis(dimethylamido)tin(IV) Degradation on Atomic Layer Deposition of Tin Oxide Films and Perovskite Solar Cells
Bibliographic record
Abstract
Abstract Tin oxide (SnO x ) films synthesized by atomic layer deposition (ALD) are widely explored in a range of optoelectronic devices including electrochemical sensors, transistors, and photovoltaics. However, the integrity of the key ALD‐SnO x precursor, namely tetrakis(dimethylamido)tin (IV) (TDMASn), and its influence on the properties of ultimate films remain unexplored. Here a significant degradation of TDMASn into bis(dimethylamido)tin(II) via the Sn‐imine complex is reported, and its impact on the corresponding films and devices is examined. It is found, surprisingly, that this degradation does not affect the growth kinetics and morphology of ALD‐SnO x films. But it notably deteriorates their electronic properties, resulting in films with twice the electrical resistance due to different oxidation mechanisms of the degradation products. Perovskite solar cells employing such films exhibit a significant loss in power conversion efficiency, primarily due to charge transport and transfer losses. These findings urge strategies to stabilize TDMASn, a critical precursor for ALD‐SnO x films, or to identify alternative materials to achieve efficient and reliable devices.
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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".