Modular thermal Hall effect measurement setup for fast-turnaround screening of materials over wide temperature range using capacitive thermometry
Bibliographic record
Abstract
We demonstrate a simple and easy-to-build probe designed to be loaded into a widely available Quantum Design Physical Properties Measurement System (PPMS) cryostat, with a detachable shielded sample puck section and robust heat sinking of three pairs of coaxial cables. It can be in principle used with any low-temperature cryostat. Our modular puck design has a radiation shield for thermal isolation and protection of the delicate sample space while handling and allows any variety of experimental setup benefiting from shielded coaxial wiring to be constructed on a selection of sample pucks. Pucks can be quickly and easily switched, and the system makes use of the simple yet extremely stable temperature and magnetic field control of the easy-to-use PPMS system. We focus on a setup designed for measurements of the thermal Hall effect and show that this system can yield unprecedented resolution over a wide temperature range and with rapid sample mounting or changing—allowing a large collection of potential samples to be screened for this novel physics. Our design aims to make these sensitive but challenging measurements quick, reliable, cheap, and accessible, through the use of a standard, widespread base cryostat and a system of modular removable sample stage pucks to allow quick turnaround and screening of a large number of candidate samples for potential new thermal Hall physics.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".