High-Throughput Screening of Antisolvents for the Deposition of High-Quality Perovskite Thin Films
Bibliographic record
Abstract
One-step solution deposition of high-quality perovskite thin films relies heavily on a small number of antisolvents. Here, we design a simple minimum volume colorimetric solution assay to screen over 100 different solvents. We correctly identify 14 previously reported antisolvents and predict 20 novel candidates. We then refine the assay through analysis of screening results, available solvent properties, and qualitative evaluation of films cast using 50 candidates. Using the refined findings, we successfully demonstrated 15 different antisolvents for characterization and evaluation in inverted devices, including six previously unreported candidates. All candidates produced power conversion efficiencies comparable to chlorobenzene controls without any additional optimization. This work presents the largest scope of antisolvents reported, can be easily adapted to other perovskites, and opens the door to selecting antisolvents based on a wide range of desirable properties including efficiency, usability, safety, and industrial viability.
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 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".