Dependence of the Surface Structure of Polystyrene on Chain Molecular Weight Investigated by Sum Frequency Generation Spectroscopy
Bibliographic record
Abstract
Sum frequency generation (SFG) spectroscopy is used to probe the surface structure of monodisperse polystyrene (PS). The amplitudes of the ν 20a and ν 2 resonances in SSP polarization are found to depend on polystyrene molecular weight between 6 and 102 kDa, whereas the amplitude of the ν 20b resonance is invariant, which all together indicates a reorientation of the phenyl ring with different chain lengths. The measured resonant amplitudes are consistent with the C 2 axis of the phenyl ring lying flat in the surface plane at the lowest molecular weights and tilting toward the surface normal at the highest molecular weights. Such reorientation is supported by the observation that the SFG intensity increases with polymer molecular weight in SSP polarization, but the spectrum exhibits no significant difference when PPP polarization is used (where the letters indicate the polarization of the SFG, visible and infrared beams). It is clear from these results that molecular weight can influence the surface structure of polystyrene in ways that are important to surface tension and surface segregation of smaller chains. Such understanding is key to providing a fundamental picture of the relationship between polymer molecular weight distribution, local surface structure, and macroscopic properties.
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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 | 0.001 |
| 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".