Degradation of Carbon Electrodes in the Vanadium Redox Flow Battery
Bibliographic record
Abstract
The Vanadium Redox Flow Battery (VRFB) is a promising candidate for large scale energy storage. These systems are expected to operate for long cycle life ~ 10 years of lifetime (~ 500 - 2000 charge – discharge cycles). 1 The VRFB’s system includes an posolyte (VO 2 + /VO 2+ ) and negolyte (V 2+ /V 3+ ) compartments with carbon electrodes, and uses acidic electrolytes (usually 3M H 2 SO 4 ). The carbon electrodes in VRFB need to perform in a harsh and corrosive environment associated with the charge/discharge cycling. In this study, we used polyacrylonitrile (PAN) based carbon papers as model carbon electrodes to study changes in the electrodes during cycling operation. The carbon papers were pre-treated according to the conventional approach by heating them in air at 500 ⁰C to incorporate oxygen functional groups on their surfaces. 2,3 These pre-treated electrodes were then used in flow battery for 100-cycles at a current density of 80 mA/cm 2 . At the single cell level, the performance of these electrodes following the operation indicated a slight decrease in voltage efficiency (from 60 % to 52 %). This decrease in performance may be attributed to the electrode degradation during operation. Characterization of the electrode prior and following 100-cycles was performed using Raman spectroscopy, XPS analysis as well as electrochemical studies. Raman analysis showed differences between the fresh and the degraded carbon electrodes, including increasing defect and electronic density distribution. XPS analysis of the degraded electrodes suggest an alteration in the amount of oxygen functional groups. Electrochemical studies showed an decrease in the electron transfer kinetics after degradation, coupled with noticeable difference between the electrodes exposed to the posolyte (VO 2 + /VO 2+ ) and negolyte (V 2+ /V 3+ ). The results provide insight into the stability of the oxygen functional groups during cycling operation which could assist in developing pre-treatment methods to functionalize the VRFB’s electrodes and for other similar electrochemical systems. References: (1) Soloveichik, G. L. Flow Batteries: Current Status and Trends. Chem. Rev. 2015 , 115 , 11533–11558. (2) Singh, A.; Yasri, N.; Karan, K.; Roberts, E. P. L. Electrocatalytic Activity of Functionalized Carbon Paper Electrodes and Their Correlation to the Fermi Level Derived from Raman Spectra. ACS Appl. Energy Mater. 2019 , acsaem.9b00180. (3) Singh, A. K.; Yasri, N.; Karan, K.; Roberts, E. P. L. Effect of Pretreatment on Carbon Materials. Meeting. Abstract. 2018 , MA2018 - 01 , 2391.
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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".