Dependence of fullerene aggregation on lipid saturation due to a balance between entropy and enthalpy
Bibliographic record
Abstract
Abstract It is well-known that fullerenes aggregate inside lipid membranes and that increasing the concentration may lead to (lethal) membrane rupture. It is not known, however, how aggregation and rupture depend on the lipid type, what physical mechanisms control this behavior and what experimental signatures detect such changes in membranes. In this paper, we attempt to answer these questions with molecular simulations, and we show that aggregation and membrane damage depend critically on the degree of saturation of the lipid acyl chains: unsaturated bonds, or "kinks", impose a subtle but crucial compartmentalization of the bilayer into core and surface regions leading to three distinct fullerene density maxima. In contrast, when the membrane has only fully saturated lipids, fullerenes prefer to be located close to the surface under the head groups until the concentration becomes too large and the fullerenes begin clustering. No clustering is observed in membranes with unsaturated lipids. The presence of "kinks" reverses the free energy balance; although the overall free energy profiles are similar, entropy is the dominant component in unsaturated bilayers whereas enthalpy controls the fully saturated ones. Fully saturated systems show two unique signatures: 1) membrane thickness behaves non-monotonously while the area per lipid increases monotonously. We propose this as a potential reason for the observations of low fullerene concentrations being effective against bacteria. 2) The fullerene-fullerene radial distribution function (RDF) shows splitting of the second peak indicating the emergence short-range order and the importance of the second-nearest neighbor interactions. Similar second peak splitting has been reported in metal glasses.
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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".