State of Charge in a Vanadium Redox Flow Battery Measured via <sup>1</sup>H MR Relaxation with Low Field Portable Magnets
Bibliographic record
Abstract
Vanadium redox flow batteries offer a promising solution for medium- to large-scale energy storage applications. Accurately monitoring the state of charge (SOC) of these batteries is crucial for optimizing long-term performance and ensuring effective battery control. Electrolyte crossover and side reactions can degrade battery performance, but traditional electrochemical techniques are often inadequate for diagnosing these issues. This study introduces a novel 1 H magnetic resonance approach to estimate the SOC by analyzing the bulk relaxation times, T 1 and T 2, in the electrolyte. The basis of the measurement is the paramagnetic relaxation enhancement effect of vanadium ions on the bulk solution. The four different vanadium oxidation states in the redox flow battery have very different effects on the bulk relaxation times. The different relaxivities of these four species permit the determination of concentration. The measurement employs two MR devices, one measuring the cathode electrolyte and one measuring the anode electrolyte. The magnets are small inexpensive, permanent magnets, Proteus magnets, with a 1 H resonance frequency of 20 MHz. To the best of our knowledge, this is the first analytical MR measurement employing two discrete MR magnets in close proximity. The prospect exists for simultaneous measurement with the two MR devices, although measurements are sequential in this study. We demonstrate how 2D maps correlating T 1 with T 1, T 2 with T 2, and T 1 with T 2, measured from both sides of the battery, can effectively “map” the SOC during operation.
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 | 0.000 |
| 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".