Electron spin resonance spectroscopy using a Nb superconducting resonator
Bibliographic record
Abstract
Recently, micro-resonator structures have demonstrated considerable enhancement of ESR spectroscopy. The high-quality factor and confined mode of these resonators (cavities) lead to an enhanced spin-cavity interaction that both increase sensitivity for conventional measurements and allow access to experiments that can investigate and utilize effects associated with strongly interacting spin ensembles and cavities. Superconducting micro-resonators are particularly interesting due to their natural compatibility with low temperatures, where the reduction of thermal noise permits coherent effects of the spin-cavity interaction to be resolved. In this work, we present X-band CW-ESR measurements of a microcrystalline BDPA sample performed using a niobium (Nb) superconducting micro-resonator. The achieved ultimate sensitivity and power conversion factor for this particular device, interfaced with an X-band Bruker EMX Micro ESR spectrometer, were found to be 5.4 × 108 Spins/G and 155 G/W, respectively, at a temperature of 3.8 K. The enhanced spin-cavity interaction in our setup had a profound influence on the measured BDPA spectral line shape, leading to a line-narrowing process not present in measurements performed using a conventional 3D resonator.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".