Improved Li-Ion Cell Construction and Usage Scheme for Achieving Operation Beyond End-of-Life
Bibliographic record
Abstract
Lithium-ion batteries will contribute to the energy storage needs that will enable the widespread implementation of renewable energy alternatives to fossil fuels. Here the role of cell lifetime in achieving sufficient battery deployment to satisfy these needs is discussed in the context of battery manufacturing limitations and the necessity of developing cells with lifetimes beyond those found in contemporary cells. A cell design, and usage scheme reliant on this design, that demonstrates vastly improved lifetime capability is presented, including usage beyond traditional definitions of end-of-life. Specifically, Li[Ni0.5Mn0.3Co0.2]O2//graphite cells, a technology that is neither exotic nor innovative, can be built to operate to a low charge voltage limit (3.8 V) and hence contain excess positive electrode capacity. Charging to low voltage naturally reduces the rate of capacity loss and the excess positive electrode capacity functions as a lithium reservoir that can be accessed to counteract capacity loss, both of which combine to yield an incredible lifetime. Specifically, the use of the positive electrode lithium reservoir projects to extend high temperature lifetime at 70 °C by an additional factor of between 1.5 and 10 compared to the lifetime achieved by conventional cycling without accessing this reservoir.
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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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".