Strain rate sensitivity of NASICON-type Li-ion conductors: Competing mechanism between plastic deformation and crack propagation
Bibliographic record
Abstract
NASICON-type lithium conductors are promising for their high ionic conductivity and thermal stability. However, their mechanical failure is one of the major challenges that impedes their usage in solid-state lithium-ion batteries. So far, their mechanical behavior under strain rates relevant to battery operation has not been fully understood. This study investigates the strain-rate-dependent mechanical behavior of two NASICON-type Li-ion conductors, Li 1.5 Al 0.5 Ge 1.5 P 3 O 12 (LAGP) and LATGP (the combination of Li 1.3 Al 0.3 Ti 1.7 P 3 O 12 (LATP) and LAGP) using nanoindentation. Averaged from at least 3 tests at a target load of 500 mN and strain rate of 0.12 s −1 , LAGP exhibits a higher Young's modulus (141.2 GPa), nanohardness (10.6 GPa), but lower toughness (0.52 MPa m 1/2 ) compared to LATGP (119.3 GPa, 9.5 GPa and 0.64 MPa m 1/2 , respectively). These differences result from variations in both atomic structures and microstructures. Both materials display decreasing hardness and increasing toughness with increasing strain rate, governed by a competition between plastic deformation and crack propagation. At low strain rates, plasticity enabled by dislocation movement dissipates stress and suppresses crack growth, while high strain rates limit plasticity, concentrating stress and promoting fracture. These findings provide mechanistic insights that guide the mechanical design and operational strategies for durable NASICON-type solid-state batteries.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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) | 0.001 | 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".