Self-Assembly of Phosphocholine Derivatives Using the ELBA Coarse-Grained Model: Micelles, Bicelles, and Reverse Micelles
Bibliographic record
Abstract
The ELBA coarse-grained force field was originally developed for lipids, and its water model is described as a single-site Lennard-Jones particle with electrostatics modeled by an embedded point-dipole, while other molecules in this force field have a three (or four)-to-one mapping scheme. Here, ELBA was applied to investigate the self-assembly processes of dodecyl-phosphocholine (DPC) micelle, 1,2- dipalmitoyl-sn-glycero-3-phosphocholine / 1,2-dihexaoyl-sn-glycero-3-phosphocholine (DPPC/DHPC) bicelles, and DPPC/cyclohexane/water reverse micelles through coarse-grained molecular dynamics (MD) simulations. New parameters were obtained using a simplex algorithm-based calibration procedure to determine the Lennard-Jones parameters for cyclohexane, dodecane, and cyclohexane–dodecane cross-interactions. Density, self-diffusion coefficient, surface tension, and mixture excess volume were found to be in fair agreement with experimental data. These new parameters were used in the simulations, and the obtained structures were analyzed for shape, size, volume, and surface area. Except for the shape of DPC micelles, all other properties match well with available experimental data and all-atom simulations. Remarkably, in agreement with experiments the rodlike shape of the DPPC reverse micelle is well described by ELBA, while all-atom data in the literature predicts a disclike shape. To further check the consistency of the force field in reproducing the correct shapes of reverse micelles, additional simulations were performed doubling the system size. Two distinct reverse micelles were obtained both presenting the rodlike shape and correct aggregation number.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".