Comparative Advances in Sulfide and Halide Electrolytes for Commercialization of All‐Solid‐State Lithium Batteries
Bibliographic record
Abstract
Abstract All‐solid‐state lithium batteries (ASSBs) outperform lithium‐ion batteries (LIBs) in safety, energy density, and thermal stability. Their performance depends on high ionic conductivity, chemical/physical stability, and scalable manufacture of solid electrolytes (SEs). This study compares sulfide‐ and halide‐based SEs, two promising next‐generation energy storage options. Soft mechanics permit sulfides with high room‐temperature conductivity, low activation energies, and processability, but high‐voltage cathode instability, moisture sensitivity, and probable hydrogen sulfide (H 2 S) release. Market prospects are favorable as the industry improves crystallinity and elemental substitution, especially for automotive cells. Chloride‐based halides are more environmentally friendly, have adequate voltage stability, and can be used with oxide cathodes without coatings. Despite traditionally low conductivity, high‐entropy, and oxyhalide chemistries currently reach 10 mS cm −1 , and scalable solvent syntheses and dry processing are driving adoption. Mechanical compliance and the use of rare elements (In, Sc) continue to cause integration and cost issues. Composition, microstructure, synthesis techniques, interfacial behavior, mechanical characteristics, and scalability are evaluated. The findings show sulfides have better conductivity and Li‐metal compatibility, but halides are more stable and manufacturable, recommending hybrid or tailored material selection based on application. Optimizing ASSB systems requires complementary sulfide/chloride utilization due to halides' mechanical constraints.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 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".