In-Depth Study of Zn Electrode Passivation in Alkaline Solutions for Zn Batteries
Bibliographic record
Abstract
Recently, increasing demand for energy storage options has rekindled work on Zn based alkaline batteries, particularly Zn-Air battery systems. Secondary alkaline Zinc-Air batteries hold several distinct advantages over other large-scale systems for energy storage. Such batteries use materials that are low cost, Zn is abundant in the earth’s crust and aqueous alkaline electrolytes are cheap and easy to work with, have a low toxicity and high chemical stability associated with them. To make Zn-air batteries viable for large scale use, issues associated with Zn electrode passivation need to be addressed that lead to a loss of performance during cycling. During the oxidation of Zn to discharge the battery, a passive layer of ZnO is formed on the electrode. This reduces the discharge current possible. Additionally, passivation is linked to electrode morphology changes between cycles, producing inconsistent performance and a reduction in capacity of the battery. Here we describe the current knowledge about Zn passivation and recent work done to better understand Zn passivation in alkaline solutions. Zn passivation is not well understood. There are multiple mechanism of passivation proposed and studies often have presented different results and conclusions despite using the same experimental conditions. Recently there have been calls in the literature for new in-depth studies that clear up the confusion present in the understanding of Zn passivation and dissolution processes in general[1, 2]. The Electrochemical Quartz Crystal Microbalance (EQCM) is a technique which can observe mass changes on an electrode at the order of 15 nanograms. The change in mass observed can be correlated to the charge passed at a given point during an experiment to give a value of mass change per mole of electron passed. This can then be used to determine the equivalent mass of the species being added to or removed to or from the electrode during an electrochemical reaction. EQCM experiments in KOH solutions of various concentrations and saturated to different levels with Zn have been conducted to observe the process by which the passivation layer forms on the surface and the process by which it is removed. Cyclic voltammogram (CV) experiments show that peaks associated with passivation removal give values of 8 to 16 grams per mole electron which corresponds well with the transition of ZnO or Zn(OH) 2 to Zn metal on the surface. The transition of the passive layer to active Zn metal on the surface may contribute to electrode shape change. During the anodic dissolution part of the CV sweep, initially values near 32 grams per mole of electron are observed in the EQCM plots, corresponding to direct removal of Zn in a 2-electron reaction. The mass to charge ratios subsequently transition to values near 49 grams per mole electron which would indicate that ZnO or Zn(OH) 2 is being formed and removed from the surface. This suggests that the formation of the passivating Zn species is potential dependent and is not solely precipitation of a film on the electrode surface. Linear sweep voltammetry and chronoamperometry experiments will be discussed as well as the impacts of additives to the solution on the electrochemistry of the electrode. Additionally, rotating disc electrode experiments were conducted using a Zn electrode in KOH solutions of various molarities saturated with Zn to understand the mass transport dependence of the passivation behavior. Changes in the location and height of peaks associated with passivation with rotation speed and sweep rate show a mass transport dependence on when passivation occurs but not on the removal of the passivation layer. Dissolution steps were conducted using Zn plate electrodes with different electrolyte concentrations and saturations of Zn at various potentials to observe major influencing factors in the passivation layer formation. These showed that passivation is heavily dependent on the amount of Zn in the solution as well as the potential applied. We conclude that the formation of the passive layer may depend on the ‘escape’ of the ZnO and Zn(OH) 2 species formed during dissolution from the electrode surface. This will be discussed in the context of the various proposed passivation mechanisms and will lead to some thoughts about improved electrode design. Acknowledgement We gratefully acknowledge the support of this work by the U.S. Department of Energy, Office of Electricity Delivery and Energy Reliability (Dr. Imre Gyuk). Bockelmann, M., et al., Electrochemical characterization and mathematical modeling of zinc passivation in alkaline solutions: A review. Electrochimica Acta, 2017 Mainar, A., et al., Alkaline aqueous electrolytes for secondary zinc-air batteries: an overview. International Journal of Energy Research, 2016 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 | 0.001 |
| 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".