Selective adsorption of block copolymers on patterned surfaces
Bibliographic record
Abstract
Adsorption of copolymers on patterned surfaces is studied using lattice modeling and multiple Markov chain Monte Carlo methods. The copolymer is composed of alternating blocks of A and B monomers, and the adsorbing surface is composed of alternating square blocks containing C and D sites. Effects of interaction specificity on the adsorbed pattern of the copolymer and the sharpness of the adsorption transition are investigated by comparing three different models of copolymer-surface interactions. Analyses of the underlying energy distribution indicate that adsorption transitions in our models are not two-state-like. We show how the corresponding experimental question may be addressed by calorimetric measurements as have been applied to protein folding. Although the adsorption transitions are not "first order" or two-state-like, the sharpness of the transition increases when interaction specificity is enhanced by either including more attractive interaction types or by introducing repulsive interactions. Uniformity of the pattern of the adsorbed copolymer is also sensitive to the interaction scheme. Ramifications of the results from the present minimalist models of pattern recognition on the energetic and statistical mechanical origins of undesirable nonspecific adsorption of synthetic biopolymers in cellular environments are discussed.
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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) | 0.000 | 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".