Molecular Insights into the Protic Organic Ionic Plastic Crystal (POIPC): Effect of Dopants and Vacancies
Bibliographic record
Abstract
High Resolution Image Download MS PowerPoint Slide In recent years, significant research effort has been dedicated to the development of robust, high-performance solid electrolyte batteries. A wide range of materials, including polymers, ceramics, and glasses, etc., have been tested and characterized as potential solid electrolyte candidates. In this respect, organic ionic plastic crystals (OIPCs) have attracted significant research attention owing to their promising properties. However, the OIPCs from different crystal classes, composed of distinct cations and anions, may display widely different phase behaviors and properties. Herein, following our previous work on pure POIPC, we conduct extensive molecular dynamics simulations, in conjunction with experimental methods, to investigate the effect of dopants and vacancies on the structural, thermodynamic, and dynamical properties of POIPC [DBUH]-[FSI], consisting of the protic [DBUH] + cation with labile proton (H + ) on the nitrogen atom. Simulations have been performed for the LiFSI doping fractions of 1.31%, 2.52%, 5.39%, and 10.55%. Additionally, the effect of Schottky vacancies was examined at concentrations of 0.23% and 0.46% for the 1.31% and 2.52% doped systems. The simulated solid–solid and the solid–liquid phase transition temperatures are in very good agreement with the DSC data. Our findings indicate that the effect of the vacancy is more pronounced at the lower doping levels. Hydrogen bonding analysis reveals that the protic N2–H1 site forms the strongest hydrogen bond in the system, with N2–H1--O being the dominant hydrogen bond. Using rotational autocorrelation functions (RACFs), we identify distinct solid phases associated with different rotational modes in the systems, confirming the presence of at least three distinct solid phases across the doping range. Translational dynamics analysis affirms that the [FSI] anion is the most mobile component of the system. The activation energy ( E a ) computed using the Arrhenius plot, is in considerable agreement with the experimental data. The lithium cation transference number ( t Li + ) agrees very well with the experimental analysis.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".