Modelling proton transfer in [HEIM][TFSI] ionic liquid
Bibliographic record
Abstract
Protic ionic liquids, PILs, are promising materials for energy storage applications, in part due to their ability to decouple proton transport from ion diffusion. In this work, we model the proton transfer mechanism in 1-ethylimidazolium bis(trifluoromethanesulfonyl)imide ([HEIM][TFSI]) IL by means of Neural Network Force Field simulations. The latter are combined with classi- cal polarizable molecular dynamics simulations to explore the structure and dynamics of the fully ionized system and Density Functional Theory calculations to estimate the energy barriers for the different proton transfer reactions. Our results show that proton transfer is indeed possible when doping the ionic liquid with an excess of deprotonated cations, but not with an excess of proto- nated anions. We highlight the importance of the formation of dimers between donor and acceptor species for the the reaction to occur, and we identify the main driving factor for the reaction to be the energy cost for reaching a suitable coordination environment and form such dimers, which is higher than that for the transfer reaction.
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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 | 0.000 |
| 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 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".