Copolymer Mediated Engineering of Halide Perovskites and Associated Devices: Current State and Future
Bibliographic record
Abstract
Abstract The field of halide perovskites has advanced significantly within a decade, as engineering strategies are addressing many of the challenges and as a result improved environmental stability and electro‐optical properties have been achieved. The use of the copolymer additive strategy has received significant attention in recent years as a variety of polymers with significant differences in properties such as water affinity, polarity, elastic modulus, ion conductivity and basis for interaction with perovskite can be selected and combined with halide perovskite. As a result, there has been a rapid increase in publications reporting the effectiveness of the inexpensive and readily available copolymer additives in altering the physicochemical, mechanical, and electro‐optical properties of the halide perovskites‐based high‐performance devices. This article is an effort to provide insight into the current state of copolymer‐mediated engineering of halide perovskites with a perspective on the reported improvements in the properties and performance of the perovskite‐based devices. Critical analysis is done on the potential of the copolymer–perovskite materials toward realizing commercial applications.
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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 | 0.001 | 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 | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".