Self‐Aligned Non‐Centrosymmetric Conjugated Molecules Enable Electro‐Optic Perovskites
Bibliographic record
Abstract
Abstract Solution‐processed organic electro‐optic (EO) chromophores are well suited for integration in optical modulators on silicon photonics chips. They contain highly conjugated molecules with polar functional groups offering large dipoles and a large nonlinear optical response. However, these molecules form centrosymmetric aggregates that hinder poling efficiency and the resultant macroscopic EO response. Furthermore, at elevated temperatures, the alignment of poled molecules can be lost, leading to a reduction in the EO response. Inorganic EO materials exhibit excellent thermal stability but lower performance. Here 2D metal halide perovskite scaffolds that align EO molecules are reported. The approach heralds a material design strategy that combines the features of organic and inorganic EO materials. The EO material exhibits promising thermal stability with a performance approaching that of organic EO materials. Anchor diammonium non‐centrosymmetric molecules are anchored inside a 2D metal halide perovskite scaffold, thereby avoiding aggregation. The authors lever the thermal stability of this compound and pole the organic molecules under an electric field at 533 K. The 2D perovskites exhibit a macroscopic EO coefficient of 68 pm V−1—a twofold increase over LiNbO3. Density functional theory calculations show that the in‐plane alignment of the molecular dipole moments can account for the EO response.
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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) | 0.002 | 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".