Influence of Cu and Ge chemical doping on the metastability and charge density wave state of <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"> <mml:mrow> <mml:mi>β</mml:mi> <mml:mtext>−</mml:mtext> <mml:msub> <mml:mi>As</mml:mi> <mml:mn>2</mml:mn> </mml:msub> <mml:msub> <mml:mi>Te</mml:mi> <mml:mn>3</mml:mn> </mml:msub> </mml:mrow> </mml:math>
Bibliographic record
Abstract
${\mathrm{As}}_{2}{\mathrm{Te}}_{3}$ is a layered chalcogenide that has garnered increasing recent interest; in particular, its metastable $\ensuremath{\beta}\text{\ensuremath{-}}{\mathrm{As}}_{2}{\mathrm{Te}}_{3}$ allotropic phase due to its relationship to other tetradymite (space group $R\overline{3}m$) chalcogenides which act as good thermoelectrics. Upon cooling below room temperature, $\ensuremath{\beta}\text{\ensuremath{-}}{\mathrm{As}}_{2}{\mathrm{Te}}_{3}$ transitions to ${\ensuremath{\beta}}^{\ensuremath{'}}\text{\ensuremath{-}}{\mathrm{As}}_{2}{\mathrm{Te}}_{3}$ and exhibits a notable increase in the resistivity which has been attributed to a transition to a charge density wave state. In this work we explore how Cu and Ge doping influences the electronic properties of $\ensuremath{\beta}\text{\ensuremath{-}}{\mathrm{As}}_{2}{\mathrm{Te}}_{3}$ and ${\ensuremath{\beta}}^{\ensuremath{'}}\text{\ensuremath{-}}{\mathrm{As}}_{2}{\mathrm{Te}}_{3}$. Samples with doping values $\mathrm{x}\ensuremath{\lesssim}0.3$ for ${\mathrm{Ge}}_{x}{\mathrm{As}}_{2}{\mathrm{Te}}_{3}$ and $\mathrm{x}\ensuremath{\lesssim}0.2$ for ${\mathrm{Cu}}_{x}{\mathrm{As}}_{2}{\mathrm{Te}}_{3}$ were synthesized and investigated by microwave plasma atomic emission spectroscopy, powder x-ray diffraction, differential scanning calorimetry, heat capacity, resistivity, and room temperature optical reflectance measurements. We use our results to create a temperature-doping phase diagram and show that doping with Ge can stabilize the $\ensuremath{\beta}$ phase and eliminate the low temperature ${\ensuremath{\beta}}^{\ensuremath{'}}\text{\ensuremath{-}}{\mathrm{As}}_{2}{\mathrm{Te}}_{3}$ phase. The optical reflectance is analyzed to extract information on the effectiveness of introducing charge carriers from which we conclude that while Ge adds carriers monotonically with doping for $\mathrm{x}\ensuremath{\lesssim}0.2$, the effect of Cu doping is more complicated, exhibiting two regimes.
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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 | 0.006 | 0.006 |
| Meta-epidemiology (narrow) | 0.002 | 0.003 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.004 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.004 | 0.005 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.251 | 0.002 |
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; both teacher heads agree on what is shown here.
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".