Molecular Dynamics Simulations of Equilibrium and Transport Properties of Amino Acid-Based Room Temperature Ionic Liquids
Bibliographic record
Abstract
Molecular dynamics simulations are used to study liquid-state equilibrium and transport properties of the 1-ethyl-3-methylimidazolium salts of the 20 naturally occurring amino acids [emim][AA] that all form room temperature ionic liquids. These ionic liquids have been recently synthesized by Ohno and co-workers [J. Am. Chem. Soc. 2005, 127, 2398], but other than measured ionic conductivity at 25 degrees C, there is a dearth of quantitative measurements on the physiochemical properties of these liquids. The goal is to computationally study the density, polarity, transference number, and ionic conductivity of this family of solvents. We also study the spatial correlations among the imidazolium cation and amino acid anions in these liquids by computing atomic and charge radial distribution functions and preparing polarity maps. The microscopic dynamics behavior of these materials is determined by studying the mean square displacements (MSD) and velocity autocorrelation functions (VACF). The diffusion coefficients of the liquids are determined using the MSD and VACF, and the contributions of the anions and cations to the transport of charge in the ionic liquids are studied. Ionic liquids of this family that show strong anion-anion and anion-cation associations in the simulations are experimentally observed to show anomalously low electrical conductivities. Knowledge of the microscopic structures and dynamics of these liquids can allow for an intelligent choice of a solvent from this class that has required polarity and ionic conductivity.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| 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 | 0.001 |
| Research integrity | 0.002 | 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".