Electrode Materials for Enhancing the Performance and Cycling Stability of Zinc Iodide Flow Batteries at High Current Densities
Bibliographic record
Abstract
Aqueous redox flow battery systems that use a zinc negative electrode have a relatively high energy density. However, high current densities can lead to zinc dendrite growth and electrode polarization, which limit the battery’s high power density and cyclability. In this study, a perforated copper foil with a high electrical conductivity was used on the negative side, combined with an electrocatalyst on the positive electrode in a zinc iodide flow battery. A significant improvement in the energy efficiency (ca. 10% vs using graphite felt on both sides) and cycling stability at a high current density of 40 mA cm –2 was observed. A long cycling stability with a high areal capacity of 222 mA h cm –2 is obtained in this study, which is the highest reported areal capacity for zinc–iodide aqueous flow batteries operating at high current density, in comparison to previous studies. Additionally, the use of a perforated copper foil anode in combination with a novel flow mode was discovered to achieve consistent cycling at exceedingly high current densities of >100 mA cm –2 . In situ and ex situ characterization techniques, including in situ atomic force microscopy coupled with in situ optical microscopy and X-ray diffraction, are applied to clarify the relationship between zinc deposition morphology on the perforated copper foil and battery performance in two different flow field conditions. With a portion of the flow going through the perforations, a significantly more uniform and compact zinc deposition was observed compared to the case where all of the flow passed over the surface of the electrode. Results from modeling and simulation support the conclusion that the flow of a fraction of electrolyte through the electrode enhances mass transport, enabling a more compact deposit.
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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 | 0.001 | 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) | 0.001 | 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".