Intrinsic defect intolerance in the ultra-pure metal PtSn4
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Bibliographic record
Abstract
Ultra-pure materials are highly valued as model systems for the study of intrinsic physics. Frequently, however, the crystal growth of such pristine samples requires significant optimization. PtSn4 is a rare example of a material that naturally forms with a very low concentration of crystalline defects. Here, we investigate the origin of its low defect levels using a combination of electrical resistivity measurements, computational modeling, and scanning tunneling microscopy imaging. While typical flux-grown crystals of PtSn4 can have residual resistivity ratios (RRRs) that exceed 1000, we show that even at the most extreme formation speeds, the RRR cannot be suppressed below 100. This aversion to defect formation extends to both the Pt and Sn sublattices, which contribute with equal weight to the conduction properties. Direct local imaging with scanning tunneling microscopy further substantiates the rarity of point defects, while the prohibitive energetic cost of forming a defect is demonstrated through density functional theory calculations. Taken together, our results establish PtSn4 as an intrinsically defect-intolerant material, making it an ideal platform to study other properties of interest, including extreme magnetoresistance and topology. Ultra-pure materials are essential for exploring intrinsic physics, yet achieving such purity often demands extensive crystal growth optimization. Here, the authors reveal that PtSn4 naturally exhibits extremely low defect levels, confirmed through resistivity measurements and microscopy, establishing it as an ideal platform for studying extreme magnetoresistance and topology.
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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 | 0.001 | 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