Nanoscale Control over Phase Separation in Conjugated Polymer Blends Using Mesoporous Silica Spheres
Bibliographic record
Abstract
A method of preparing blended conjugated polymer microparticles using mesoporous silica spheres is described. Poly(3,4-ethylenedioxythiophene) (PEDOT) was blended with poly(furfuryl alcohol) (PFA) by a sequential infiltration-polymerization approach. The materials were evaluated by both scanning and transmission electron microscopy and are shown to retain the overall spherical structure of the silica template. The filling of the mesopores and the polymer distribution within individual particles were determined by a combination of energy-dispersive X-ray microanalysis, X-ray photoelectron spectroscopy, and nitrogen adsorption. The results suggest that when PEDOT is added to the silica host, followed by PFA, the phase separation of the two immiscible polymers is constrained by the dimensions of the silica mesopores, ensuring nanoscale contact between the two phases. The silica template can be removed by etching with 25% hydrofluoric acid, leaving behind a blended polymer microparticle. The etched microparticles exhibit macroporous morphologies different from that of pure PEDOT particles prepared by a similar route. The blended microparticles also appear to undergo limited phase separation; no evidence for distinct polymer domains was observed. Conductivity measurements indicate that the blended particles are above the percolation threshold and support the conclusion that the phase domains are extremely small. Importantly, when PFA is added to the host first, followed by PEDOT, there is a striking difference to the final composition and morphology of the particles. This reversal of the blending order results in a more amorphous, phase-separated material. These results demonstrate the preparation of conjugated polymer blends with engineered nanoscale phase separation and may allow for future improvements in organic device architecture and performance.
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) | 0.001 | 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 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".