A Boron Difluoride Hydrazone (BODIHY) Polymer Exhibits Aggregation‐Induced Emission
Bibliographic record
Abstract
Abstract Polymers that exhibit aggregation‐induced emission (AIE) find use, for example, as cell‐imaging agents and as fluorometric sensors due to their unique optical properties. However, the structural diversity of AIE‐active polymers has not necessarily advanced at the same rate as their applications. In this work, ring‐opening metathesis polymerization is used to synthesize the first example of a polymer (Mn = 61,600 g mol−1, Đ = 1.32) containing boron difluoride hydrazone (BODIHY) heterocycles in its repeating unit. The BODIHY monomer and polymer described absorb and emit in the visible region in solution (λabs = 428 and 429 nm, λem = 528 and 526 nm) and as thin films (λabs = 443 and 440 nm, λem = 535 and 534 nm). Monomer (ΦFilm = 10%) and polymer (ΦFilm = 6%) exhibit enhanced emission as thin films compared to solution (ΦSoln ≤ 1%) as well as AIE upon the addition of water to DMF solutions as a result of restriction of intramolecular motion. Enhancement factors for the monomer and polymer are determined to be 58 and 15, respectively. The title BODIHY polymer exhibited an earlier onset of AIE and enhanced sensitivity to solution viscosity when compared to the parent monomer.
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 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".