Optimization of a parallel‐plate <scp>RF</scp> probe for high resolution thin film imaging
Why this work is in the frame
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Bibliographic record
Abstract
Abstract Choosing an MR probe with the correct dimensions and high sensitivity is critical for magnetic resonance imaging, especially high resolution thin film imaging. In this work, a parallel‐plate resonator has been optimized for strength and uniformity of the B 1 magnetic field. The parallel‐plate resonator is designed for high resolution imaging in the direction perpendicular to the plates. The optimization process was undertaken through simulation with CST Micro Wave Studio, followed by experiment. A 400 μm capillary tube, filled with doped water, was used for testing the optimized probe in a 2.4 T magnet. It is shown that increasing the width of the copper leads connected to the plates increases the homogeneity of the B 1 magnetic field by almost 90%. The best approach to increase the sensitivity and the homogeneity of the probe was to maintain the dimensions of the plates and copper leads but to add additional capacitors at the corners to distribute the current. This approach produces a 40% stronger B 1 magnetic field and increases the homogeneity by almost 85%. The experimental B 1 magnetic field of the parallel‐plate prototype agrees within 20% of the value found through simulation, for specified power. The experimental MRI results show that it is possible to achieve a nominal resolution of 10 μm between the plates for suitable samples using the optimized probe. The optimized parallel‐plate resonator, combined with a phase encode SE SPI method, may be used for high resolution studies of lithium‐ion transport in the electrolyte solution of lithium‐ion batteries.
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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 it