Preconditioning Operation of Membraneless Vanadium Micro Redox Flow Batteries
Bibliographic record
Abstract
Abstract Development of a Membraneless Vanadium Micro Redox Flow Battery (MVMRFB) with an automated closed‐loop control, using micro actuators and micro sensors, is presented for the first‐time during electrolyte preconditioning operation in recirculation mode. The progress of preconditioning is tracked with UV‐vis spectroscopy by 3D printed micro flow cuvettes. Influence of flow rate, reactor internal resistance, and presence of side reactions in the preconditioning process are studied. Optimal flow rate ratio between negative and positive electrolytes is determined and significant performance improvements achieved by operating at lower flow rates are obtained. Influence of reactor internal resistance, which is directly related with the maximum power density, is evaluated demonstrating that operating at a high‐power density can be a source of inefficiency due to the presence of side reactions. Finally, presence of side reactions is evaluated through a dual measurement of electrolytes concentrations in both negative and positive side, and it is demonstrated to be a cause for charge imbalance between the two half‐cells. This work lays a solid foundation for the successful implementation of a charge‐discharge cycle in MVMRFBs operating in recirculation mode.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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 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".