Sustainable Redox Mediation for Lithium-Oxygen Battery By Using Protected Lithium Anode
Bibliographic record
Abstract
Because of the growing needs for secondary batteries with greater energy density in various applications including electric vehicle, rechargeable non-aqueous lithium–oxygen (Li-O2) battery is receiving a great attention owing to its high theoretical energy density of 3505 Wh kg-1 which far exceeds that of conventional lithium ion battery (LIB) [1, 2]. However, due to the insulating nature of main discharge product, lithium peroxide (Li2O2) the oxygen-evolving reaction (OER) during charge requires a much higher overpotential, which is the one of the main challenges to practical applications [2, 3]. Incomplete decomposition of Li2O2 at the cathode causes excessive accumulation of solid discharge products on cathode surface during cycling, resulting in cell failure by pore clogging. As a consequence, Li-O2batteries usually present poor round-trip efficiencies and severe capacity decays. To alleviate this problem, redox mediators (RMs) as soluble and mobile catalyst in aprotic media, have been intensively studied to address the overvoltage problem [3, 4]. In spite of such a smart strategy, self-discharge of redox mediator is inevitable in current battery configurations due to its chemical reduction at Li metal anode, as shown in Figure 1. In this presentation, we suggest a synergic combination of soluble redox mediator and protected Li metal electrode for preventing the self-discharge of redox mediator and realize the concept by exploiting a redox mediator of 2,2,6,6,-tegramethylpiperidinyl-1-oxyl (TEMPO) and a composite protective layer (CPL) of Al2O3/PVdF-HFP composite. First, from the electrochemical characterization in conjunction with SEM and XPS analyses, the effectiveness of the highly reversible TEMPO/TEMPO+ redox couple as a RM was verified. More importantly, this presentation provides a detrimental effect of TEMPO on the interfacial stability of Li metal electrode by monitoring the battery cycling under Ar atmosphere, and thus, the necessity of Li metal anode protection was suggested in terms of the reversibility of RMs in the non-aqueous media. The CPL coated on Li metal electrode could suppress the reaction of TEMPO at Li metal electrode and maintain the redox mediated Li2O2 oxidation over repeated cycles, opening a new possibility for a robust use of RM for Li-O2batteries. Figure 1. Schematic illustration of (a) the self-discharge of redox mediator in Li-O2 battery and (b) the CPL-coated Li electrode which prevent the reaction between redox mediator and Li metal electrode. References [1] P. G. Bruce, S. A. Freunberger, L. J. Hardwick, J.-M. Tarascon Nat. Mater. 2012, 11, 19-29. [2] G. Girishkumar, B. McCloskey, A. C. Luntz, S. Swanson, W. Wilcke J. Phys. Chem. Lett. 2010, 1, 2193-2203. [3] Y. Chen, S. A. Freunberger, Z. Peng, O. Fontaine, P. G. Bruce Nature Chem. 2013, 5, 489-494. [4] B. J. Bergner, A. Schürmann, K. Peppler, A. Garsuch, J. Janek J. Am. Chem. Soc. 2014, 136, 15054-15064. Figure 1
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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) | 0.001 | 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 | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".