Molecular dynamics simulations of the structure and transport properties of tetra-butylphosphonium amino acid ionic liquids
Bibliographic record
Abstract
Systematic molecular dynamics simulations are used to study the structure, dynamics and transport properties of the ionic liquids composed of the tetra-butylphosphonium ([TBP](+), or [P(C(4)H(9))(4)](+)) cation with six amino acid ([AA](-)) anions. The structural features of these ionic liquids were characterized by calculating the partial site-site radial distribution functions, g(r), and computing the dihedral angle distribution of n-butyl side chains in the [TBP](+) cations. The dynamics of the ionic liquids are described by studying the velocity autocorrelation function (VACF) and the mean-square displacement (MSD) for the centers of mass of the ions at different temperatures. The ionic diffusion coefficients and the electrical conductivities were evaluated from both the Einstein and Green-Kubo methods. The cross-correlation terms in the electric-current autocorrelation functions, which are an indication of the ion pair correlations, are investigated. The cationic transference numbers were also estimated to study the contributions of the anions and cations to the transport of charge in these ionic liquids. We determined the role of the amino acid anion structures on the dynamical behavior and the transport coefficients of this family of ionic liquids. In general, the MSD and self-diffusion coefficients of the relatively heavier non-planar [TBP](+) cations are smaller than those of the lighter amino acid anions. Introducing polar functional groups (acid or amide) in the side chain of [AA](-) decreases the diffusion coefficient and electrical conductivity of AAILs. The major factors for determining the magnitude of the transport coefficients are the chemical functionality and the length of the alkyl side chain of the [AA](-) anion of these [TBP][AA] ionic liquids.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.002 | 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".