Dielectric Constants for Quantum Chemistry and Li-Ion Batteries: Solvent Blends of Ethylene Carbonate and Ethyl Methyl Carbonate
Bibliographic record
Abstract
This work reports measurements of the dielectric constants of ethylene carbonate (EC)/ethyl methyl carbonate (EMC) blends between 25 and 60 °C. Dielectric constants were measured using a cylindrical capacitance cell and a frequency response analyzer. EC and EMC form nonideal mixtures that cannot be described by a simple linear mixing model. A quadratic mixing rule was instead adopted, and the mixing parameter is reported for 25–60 °C. The results of this research may be used to calculate the dielectric constant of any EC/EMC mixture over this temperature range with ≤4% estimated error. By modeling the ionic dissociation of lithium hexafluorophosphate (LiPF 6 ) in various solvents, the significance of the dielectric constant on quantum chemistry simulations of chemical processes is explored. The effect of the dielectric constant accuracy on electrochemical processes was similarly evaluated by calculating the solvation energy of neutral and singly oxidized vinylene carbonate in various solvents. It is demonstrated that the exact value of the dielectric constant can significantly affect calculation accuracy when ε < 40, which is the case for the most commonly used EC/EMC blends.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 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".