Bulk transport paths through defects in floating zone and Al flux grown <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mrow><mml:mi>SmB</mml:mi></mml:mrow><mml:mn>6</mml:mn></mml:msub></mml:math>
Bibliographic record
Abstract
We investigate the roles of disorder on low-temperature transport in $\mathrm{Sm}{\mathrm{B}}_{6}$ crystals grown by both the Al flux and floating zone methods. We used the inverted resistance method with Corbino geometry to investigate whether low-temperature variations in the standard resistance plateau arise from a surface or a bulk channel in floating zone samples. The results show significant sample-dependent residual bulk conduction, in contrast to smaller amounts of residual bulk conduction previously observed in Al flux grown samples with Sm vacancies. We consider hopping in an activated impurity band as a possible source for the observed bulk conduction, but it is unlikely that the large residual bulk conduction seen in floating zone samples is solely due to Sm vacancies. We therefore propose that one-dimensional defects, or dislocations, contribute as well. Using chemical etching, we find evidence for dislocations in both flux and floating zone samples, with higher dislocation density in floating zone samples than in Al flux grown samples. In addition to the possibility of transport through one-dimensional dislocations, we also discuss our results in the context of recent theoretical models of $\mathrm{Sm}{\mathrm{B}}_{6}$.
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 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 | 0.001 | 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".