Friction between Polymer Brushes in Good Solvent Conditions: Steady-State Sliding versus Transient Behavior
Bibliographic record
Abstract
Previous molecular dynamics simulations of friction between polymer brushes in relative sliding motion [Kreer, T.; Müser, M. H.; Binder, K.; Klein, J. Langmuir 2001, 17, 7804] are extended beyond steady-state conditions. We study two different protocols: (i) stop and return and (ii) stop and go. In protocol (i), the relative, lateral motion between the two surfaces is stopped abruptly and reimposed opposite to the initial direction after the system could relax for some time. Protocol (ii) is similar except that the sliding direction is maintained. In the constant-velocity steady state, the average lateral extension l c of the polymers is found to be a power law of the sliding velocity v, namely, l c ∝ v 0.3 . When the sliding direction is inverted, a shear stress maximum is observed after the two walls have slid a relative distance of 2 l c . This maximum occurs when the average inclination of the polymers is 90°, and it is accompanied by brush swelling. In protocol (ii), no brush swelling is found and shear stress maxima are absent in the itinerant stages of the go phase, with the exception of large v . We conclude that dissipation mechanisms for oscillatory shear are similar to those for constant-velocity sliding if the driving amplitude 𝒜 distinctly exceeds 2 l c . Moreover, enhanced loss at 𝒜 ≈ 2 l c is not necessarily related to stick−slip motion.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| 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".