Exploring Defects and Dopability Limits of Solid Electrolytes: a Computational Study
Bibliographic record
Abstract
Negligible electronic conductivity is a crucial requirement that solid electrolytes must meet before they can be considered in all-solid-state lithium batteries. Electronic conductivity is strongly driven by charged defects. Understanding the defect chemistry of solid electrolytes is therefore essential to assess their performance and suitability. In this work, we use first-principles computations to investigate the intrinsic defect chemistry of six solid electrolytes in order to determine their robustness to developing electronic conductivity. We conclude that some electrolytes can be prone to problematic levels of electronic conductivity (e.g., LiTi2(PO4)3) while others such as Li3PS4 have intrinsically low electronic conductivities. We also show that most solid electrolytes are more likely to develop electronic conductivity in S/O-rich|Li-poor environments, translating to more sulfur-rich or oxidative atmospheres and higher electrochemical potentials (> 4 V vs. Li+/Li).
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| 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) | 0.003 | 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".