Effective Mass Transport Properties in Lithium Battery Electrodes
Bibliographic record
Abstract
Lithium ion battery performance becomes increasingly limited by ionic transport as the current demand increases. Especially detrimental is the transport within the liquid electrolyte that fills the porous electrode, yet reliable measurement of practical lithium diffusivity within this complex structure has been a longstanding challenge. In this work, we have developed a “single sided” analytical technique to determine the diffusivity in porous networks using scanning electrochemical microscopy (SECM) and a molecular redox marker. SECM surface mapping of porous films shows measurement consistency, and diffusion limited currents through a test structure with well-defined geometry matches the results of numerical modeling within 10%. Diffusivity measurement shows significant deviation from the Bruggeman model for porosities below 60%. The developed technique is applicable to all porous structures independent of their electronic conductivity. Importantly, for lithium-ion batteries the technique does not require free-standing electrodes and therefore is applicable to industrially relevant high power electrodes as a tool for optimization as well as for quality control.
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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 | 0.001 |
| 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 | 0.001 |
| 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".