Customizable Porous Electrodes for Redox Flow Batteries via Additive Manufacturing
Bibliographic record
Abstract
Porous electrodes play a crucial role in the performance and cost-effectiveness of redox flow batteries (RFBs) by providing the necessary surface area for the electrochemical reactions, facilitating electrolyte transport, and contributing to mass, charge, and heat transfer. Enhancing the electrode performance can increase the power density and reduce the battery costs. However, traditional carbon-fiber porous electrodes, adapted from fuel cell gas diffusion layers, are not optimized for liquid-phase electrochemistry. Therefore, new manufacturing techniques that allow for precise control of the electrode microstructure and properties are required. Additive manufacturing is particularly interesting for obtaining controlled architectures, which enables the study of geometry-performance relationships and the production of high-performance electrodes with improved electrochemical performance and lower hydraulic resistance. In my presentation, I will discuss our recent advancements in the additive manufacturing of porous electrodes for RFBs, where we demonstrate the flexibility of this approach for the fabrication of electrode microstructures for electrochemical applications. I will specifically focus on our work on triply periodic minimal surface (TPMS) structures as RFB electrodes. TPMS structures, naturally occurring in butterfly wings, leaves, and sea urchin skeletons, feature periodic surfaces with large surface areas that are advantageous for RFB electrodes. In our previous research, we demonstrated that the electrode pillar shape influences mass transfer rates, leading us to explore various TPMS designs, including gyroid, diamond, and IWP. We fabricated TPMS electrodes using a commercial desktop digital light processing printer followed by carbonization. In organic redox flow cells, TPMS electrodes demonstrated higher internal surface area and improved mass transport compared to cubic periodic structures, improving the reactor performance. The diamond TPMS, in particular, outperformed regular cubic structures, showing the lowest overpotential and highest current density and mass transfer coefficient. Our research emphasizes the potential of additive manufacturing to develop customized porous electrodes with multiscale structures that offer superior electrochemical performance and low hydraulic resistance. Acknowledgments The authors gratefully acknowledge funding by the European Union (ERC, FAIR-RFB, ERC-2021-STG 101042844). Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Council. Neither the European Union nor the granting authority can be held responsible for them.
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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 | 0.000 |
| 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".