(Invited) Using Synchrotron Techniques to Pry into Lithium-Ion Batteries Limitations
Bibliographic record
Abstract
Li-ion batteries have been highly successful since they were introduced commercially some 30 years ago. However, there are still improvement to be made to reduce cost, charging times, energy density etc. In this talk, we will present the some of our recent synchrotron radiation-based work on the sub-processes that must work in unison for lithium battery operation, in particular at high current densities. Specifically, we will present work at the particle level on high power charging, illustrating how under favorable conditions some commercial cathode materials may be fully charged within tens of seconds. Moving towards the electrode scale, our latest technique development include an x-ray fluorescence technique that permits the determination of the electrolyte concentration within the electrode during battery operation. As such, this represent a major step forward towards validating mesoscale modeling as well as testing novel electrode architectures specifically designed for improved electrolyte transport. The importance of the electrode design is that in theory it can provide higher active material loading per area without losss of power capabilities. As such, the mass and volume of separator as well as current collector could be minimized improving both energy density and cost.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.053 | 0.024 |
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".