Tracking the Three-Dimensional Distribution of Growth Impurities in $\text{Cd}_{0.9} \text{Zn}_{0.1} \text{Te}$ Single Crystal
Bibliographic record
Abstract
CdZnTe (CZT) crystals have been the subject of extensive studies toward high-performance room temperature X-ray detectors. Despite decades of research, the atomic-level understanding of growth impurities in these materials remains conspicuously missing in literature despite its importance to elucidate the growth imperfections and their role in shaping the material behavior. Herein, this works combines Transmission Electron Microscopy (TEM) and Atom Probe Tomography (APT) to achieve the full atomic-scale analysis of the inclusions typically found in CZT crystals. The inclusions consist of Te single crystals containing CZT nanoscale crystalline precipitates. These precipitates reach tens of nanometers in diameter and contain$\text{Cu}, \text{In}$, and Na impurities. Cu and In are found to decorate the surface of the precipitates. This atomic scale analysis gives unique insights into the three-dimensional distribution of growth impurities, which is highly valuable to understand the mechanisms underlying the crystallization process. These insights are also critical to model the basic properties of CZT semiconductors.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Open science | 0.000 | 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 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".