Highly efficient and selective pressure-assisted photon-induced polymerization of styrene
Bibliographic record
Abstract
The polymerization process of condensed styrene to produce polystyrene as an industrially important polymeric material was investigated using a novel approach by combining external compression with ultraviolet radiation. The reaction evolution was monitored as a function of time and the reaction products were characterized by in situ Fourier transform infrared spectroscopy. By optimizing the loading pressures, we observed highly efficient and selective production of polystyrene of different tacticities. Specifically, at relatively low loading pressures, infrared spectra suggest that styrene monomers transform to amorphous atactic polystyrene (APS) with minor crystalline isotactic polystyrene. In contrast, APS was found to be the sole product when polymerization occurs at relatively higher loading pressures. The time-dependent reaction profiles allow the examination of the polymerization kinetics by analyzing the rate constant and activation volume as a function of pressure. As a result, an optimized pressure condition, which allows a barrierless reaction to proceed, was identified and attributed to the very desirable reaction yield and kinetics. Finally, the photoinitiated reaction mechanism and the growth geometry of the polymer chains were investigated from the energy diagram of styrene and by the topology analysis of the crystal styrene. This study shows strong promise to produce functional polymeric materials in a highly efficient and controlled manner.
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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) | 0.001 | 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".