Solving Barriers to Commercialization of Cells with Lithium Metal Anodes
Bibliographic record
Abstract
Commercially available Li-ion batteries using graphite or graphite-silicon blended anodes are currently approaching a cell level specific energy of 300 Wh kg −1 . The use of lithium metal instead as an anode an intriguing possibility to further increase cell level specific energies to 400 Wh kg −1 and beyond. Lithium is an ideal anode because it is the lightest metal and highly electronegative. However, attempts to commercialize cells using lithium metal anodes have been slowed by poor cycle life and safety issues. This is because nonuniform lithium plating leads to the growth of dendrites that cause loss of active lithium and can eventually lead to internal cell shorts. Safe cell cycle life must be improved to 50-100 cycles for special purpose applications like unmanned aerial vehicles, >300 cycles for portable power applications and >1000 cycles for electric vehicle applications. This performance must be maintained during the challenge of scaling cell size from <5 mAh coin cells with relative low areal capacities less than 2 mAh cm −2 used in most literature research to larger cell sizes such as (>2000 mAh) pouch cells and 18650/21700 cylindrical cells with practical areal capacities >4.5 mAh cm −2 . The advantages and disadvantages of several potential cell designs will be discussed including using lithium metal with conventional Li-ion cathodes, nonlithithated metal oxides and fluorides, sulfur and air cathodes, as well as other advanced concepts. Several types of electrolytes including liquid, polymer and ceramic will be evaluated based on ability to limit dendrites and manufacturability. Other methods to limit dendrite propagation such as surface pretreatments and pulse plating will also be covered. Finally, the performance of prototype cells developed at EaglePicher using lithium metal anode will be highlighted. Figure 1 shows a 2 Ah prototype pouch cell using a lithium anode, high nickel cathode and nonaqueous electrolyte. The cell demonstrates an extremely high specific energy of >375 Wh kg −1 but a poor cycle life of ~25 cycles to 80% retention. This presentation will focus on design considerations for cells with lithium anodes, as well as improving the cycle life and safety characteristics of these cells. Several methods for improving both of these areas will discussed. Incorporation of these methods and the performance improvement of 2 and 10 Ah pouch cells using the lithium anode will presented. Figure 1
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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) | 0.000 | 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) | 0.000 | 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".