The influence of water on the structural and transport properties of model ionic liquids
Bibliographic record
Abstract
Molecular dynamics simulations are used to investigate the influence of water on model ionic liquids. Several models, where the ions vary in size, and in the location of the charge with respect to the center of mass, are considered. Particular attention is focused on the variation in transport properties (diffusion coefficients, shear viscosity, and electrical conductivity) with water concentration. An effort is made to identify the underlying physical reasons for water's influence. The results for our model ionic liquids fall loosely into two categories, depending on the molecular characteristics of the constituent ions. If the ion size disparity is not too large (cation:anion diameter ratio < or approximately 2:1), and if the ion charge location is such that directional ion pair bonds are relatively weak, then we find that the ionic diffusion coefficients and the electrical conductivity increase, and the viscosity decreases with increasing water concentration. This agrees with what is commonly observed experimentally for room temperature ionic liquids (RTILs). For these systems, we do not find changes in the equilibrium structure that can account for the strong influence of water on the transport properties. Rather, by varying the molecular mass of water in our simulations, we demonstrate that the dominant effect of water can be dynamical in origin. In RTIL-water mixtures, the molecular mass of water is generally much less than that of the ions it replaces. These lighter water molecules tend to displace much heavier counterions from the ion coordination shells. This reduces caging and increases the diffusivity, which leads to higher conductivities and lower viscosities. For models with a larger ion size disparity (3:1), or in charge-off-center systems, where strong directional ion pairs are important in the pure ionic liquid, the behavior can be quite different. In these systems, the diffusion coefficients and electrical conductivity can still display conventional behavior and increase when water is added even though the reasons for this can be more complex than in the simpler cases noted above. However, in these systems the viscosity can increase, sometimes quite steeply, with increasing water concentration. We trace this unusual behavior to the formation of associated structures, extended anion-water chains that can weave among the cations in the size disparate case, and strongly bound cation-water-anion clusters in the charge-off-center systems.
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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".