Structure and aggregation in model tetramethylurea solutions
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Bibliographic record
Abstract
The structure of model aqueous tetramethylurea (TMU) solutions is investigated employing large-scale (32,000, 64,000 particles) molecular dynamics simulations. Results are reported for TMU mole fractions, X(t), ranging from infinite dilution up to 0.07, and for two temperatures, 300 and 330 K. Two existing force fields for TMU-water solutions are considered. These are the GROMOS 53A6 united-atom TMU model combined with SPC/E water [TMU(GROMOS-UA)/W(SPC/E)], and the more frequently employed AMBER03 all-atom force field for TMU combined with the TIP3P water model [TMU(AMBER-AA)/W(TIP3P)]. It is shown that TMU has a tendency towards aggregation for both models considered, but the tendency is significantly stronger for the [TMU(AMBER-AA)/W(TIP3P)] force field. For this model signs of aggregation are detected at X(t) = 0.005, aggregation is a well established feature of the solution at X(t) = 0.02, and the aggregates increase further in size with increasing concentration. This is in agreement with at least some experimental studies, which report signals of aggregation in the low concentration regime. The TMU aggregates exhibit little structure and are simply loosely ordered, TMU-rich regions of solution. The [TMU(GROMOS-UA)/W(SPC/E)] model shows strong signs of aggregation only at higher concentrations (X(t) ≳ 0.04), and the aggregates appear more loosely ordered, and less well-defined than those occurring in the [TMU(AMBER-AA)/W(TIP3P)] system. For both models, TMU aggregation increases when the temperature is increased from 300 to 330 K, consistent with an underlying entropy driven, hydrophobic interaction mechanism. At X(t) = 0.07, the extra-molecular correlation length expected for microheterogeneous solutions has become comparable with the size of the simulation cell for both models considered, indicating that even the systems simulated here are sufficiently large only at low concentrations.
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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 it