Simulation of Small Molecules Permeation Through Polymer Matrix
Bibliographic record
Abstract
New technologies deeply depend on the ability of chemists to synthesize new functional materials. However, this synthetic step requires great efforts. Moreover, it is very likely that the ensuing compound does not fit the expected properties. With the advent of simulation, associated with the increase in computer performance and efficiency of codes, a screening of the best potential candidates to be synthesized becomes available. Accordingly, getting a polymer with a specific permeability, and also understanding the molecular reasons underlying this process, are some of the assets of molecular simulation. Nevertheless, representation of a material from a molecular perspective is not straightforward. A specific protocol must be established. It takes into account the fact that calculations are carried out on very tiny systems. An accurate depiction and perpetual validations confronting simulated results with experimental data make the protocol relevant. The computation of the penetrants’ diffusion coefficient and solubility is then introduced, in order to reveal the simulation of the permeation of a small molecule through an amorphous polymer system. The paper concludes with the most recent studies on the subject.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".