Crystal Structures and Phase Behavior of the Cyclic Carbonates Fluoroethylene Carbonate, Ethylene Carbonate, and Vinylene Carbonate down to 86 K Using Powder Diffraction Data
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide Understanding the behavior of organic electrolytes of lithium-ion batteries is ubiquitous to help overcome the adverse impact of their freezing in cold conditions on impacting the reversibility and durability of lithium-ion batteries. Fundamental studies of the popular, yet corrosive solvent/additive fluoroethylene carbonate (FEC) appear to be few in number outside electrochemical characterization. This powder diffraction study forms what we believe to be the first to specifically probe the nature of its crystalline solid state. The crystal structure was determined ab initio with simulated annealing of powder diffraction data supported by Density Functional Theory calculations. Phase and thermal expansion behavior between 90 and 275 K were studied. Comparison powder diffraction data were obtained from the related ethylene carbonate (EC) and vinylene carbonate (VC). No solid–solid phase transitions were observed in the temperature range studied for any of the samples. FEC was found to form a three-dimensional network structure comprising hydrogen-bonded dimers as opposed to the more layered nature of the EC and VC crystal structures. The weak attractive and repulsive intermolecular interactions in the final crystal structures were examined using the Non-Covalent Interaction method and Bader partial charges.
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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 | 0.001 | 0.001 |
| 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) | 0.003 | 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".