Crystalline structure, electronic and lattice-dynamics properties of NbTe2
Bibliographic record
Abstract
Abstract Layered-structure materials are currently relevant given their quasi-2D nature. Knowledge of their physical properties is currently of major interest. Niobium ditelluride possesses a monoclinic layered-structure with a distortion in the tellurium planes. This structural complexity has hindered the determination of its fundamental physical properties. In this work, NbTe 2 crystals were used to elucidate its structural, compositional, electronic and vibrational properties. These findings have been compared with calculations based on density functional theory. The chemical composition and elemental distribution at the nanoscale were obtained through atom probe tomography. Ultraviolet photoelectron spectroscopy allowed the first determination of the work function of NbTe 2 . Its high value, 5.32 eV, and chemical stability allow foreseeing applications such as contact in optoelectronics. Raman spectra were obtained using different excitation laser lines: 488, 633, and 785 nm. The vibrational frequencies were in agreement with those determined through density functional theory. It was possible to detect a theoretically-predicted, low-frequency, low-intensity Raman active mode not previously observed. The dispersion curves and electronic band structure were calculated, along with their corresponding density of states. The electrical properties, as well as a pseudo-gap in the density of states around the Fermi energy are characteristics proper of a semi metal.
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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 | 0.000 | 0.000 |
| Open science | 0.000 | 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".