Improving the Cycling Stability of Sodium Metal Electrode By Making an Sodium-Carbon Composite Electrode
Bibliographic record
Abstract
The use of metallic anodes such as lithium and sodium has attracted large attention in the battery field because of their extremely high specific capacity and low operation potential. Indeed, the formation of metal dendrite upon repeated electrochemical plating/stripping cycling was early identified as obstacle of the development of safe metal anode secondary batteries. Also, due to dendrite formation, the low cycle efficiency and unstable cycle life happen, which hinder their practical application as anode materials. Therefore, to suppress the growth of metal dendrite is one of the most critical issues from a practical view point. Recently, lithium metal has been extensively researched as anode candidate for secondary batteries due to its lowest redox potential and highest specific capacity among metallic anodes. Despite these promising properties, lithium sources are relatively limited and unevenly distributed across the globe, which lead to high costs of lithium metal batteries. Therefore, inevitably, lithium-based batteries will become unaffordable and large-scale production will falter. Therefore, sodium (Na) is one of the promising alternatives to lithium for energy storage technologies because of its relatively high theoretical specific capacity of 1166 mAh g-1 and natural abundance. Also, it has comparable redox potential, that is -2.70 V vs. SHE. However, like lithium metal anode, inhomogeneous electrochemical deposition of Na is a crucial problem that have to be solved for the usage of sodium metal as anode safely. Furthermore, Na metal has extremely high reactivity with liquid organic electrolyte, so high interfacial resistance could be induced due to continuous electrolyte decomposition during battery cycling, which also leads to earlier cell failure. In this research, we present a stabilized sodium electrode by introducing electrically connected carbon network (ECN) to a bulk Na electrode with a simple folding & rolling method. As a results of introducing ECN, we observed that a cell overpotential was decreased as the amount of ECN inside bulk Na metal was increased. Also, we found that the cycling stability of Na/Na symmetric cell with ECN was almost 4.5 times increased compared to bare Na/Na cell, which is consistent with the results of EIS during cycling. By using SEM and CA analysis, we confirmed that an introduced ECN could act as not only an electrical network but also artificial uniform seed for Na nucleation.
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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 | 0.001 | 0.001 |
| 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) | 0.001 | 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".