Studies of the Ferromagnetic Superconductors URhGe and UCoGe
Bibliographic record
Abstract
This thesis comprises studies on two ferromagnetic superconductors, URhGe (Tcurie=9.SK and Tsc=2S0mK) and UCoGe (Tcurie=2.SK and Tsc=800mK). These properties are interesting because the current theory to explain superconductivity predicts that ferromagnetism should destroy superconductivity. Not only is that not true in these materials, but ferromagnetism and superconductivity are thought to arise from a common mechanism. The studies conducted on these materials arise from that possibility, in an attempt to understand the unconventional nature of these materials.<br />Original work is contained in chapters 4, Sand 6. All of this work is currently not published in sources other than this thesis. <br /> Chapter 1 will give an introduction to these materials, and the work that has been done on them by other groups, and work done on related materials. <br /> Chapter 2 will give details of the various experimental methods used in measuring the structure and properties of the materials studied. This work was conducted by the author at McMaster University, with the assistance of individuals from the Brockhouse Institute for Materials Research, and the Center for Electron Microscopy at McMaster University.<br /> Chapter 3 will provide an introduction to the technique of muon Spin Resonance/Relaxation (μSR). This work was done at the TRIUMF facility in Vancouver, British Columbia, with the assistance of several TRIUMF staff. The data was collected by the author, and other members of Dr. Luke's research group as well as collaborators from TRlUMF and from Columbia University. <br /> Chapter 4 will present the measurements made on UCoGe, while Chapter 5 presents the measurements of URhGe. Details of the crystal growth and structure characterization measurements are included in these chapters, along with resistivity, bulk magnetization and μSR measurements. <br /> Both zero- field (ZF) and transverse field (TF) μSR has been performed. This work focuses on studying the magnetic moment size, and the magnetic volume fraction around the ferromagnetic transition, and to temperatures as low as 20mK. Consideration is also given to the magnetic and superconducting properties in the low-temperature region. <br /> In the Introduction, URhGe is presented first, followed by UCoGe, since this was the order in which they were discovered. The results obtained from UCoGe are presented first, since work on that compound was started before the work on URhGe. <br /> Chapter 6 focuses on the conclusions drawn from this work, comparing the measurements of both materials.
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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) | 0.009 | 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".