Rectifying and Schottky characteristics of a-Si<sub><i>x</i></sub>Ge<sub>1−<i>x</i></sub>O<sub><i>y</i></sub> with metal contacts
Bibliographic record
Abstract
Metal–semiconductor contacts are a vital part of semiconductor devices as they can form a Schottky barrier or an Ohmic contact. The nature of the contact plays an important role in determining the electrical and physical characteristics of the device and hence is of paramount importance in the operation of the device. In the current work we report the design, fabrication, and current–voltage (I-V) characteristics of microbolometers, a type of infrared detector where the change in temperature changes the resistance of the sensing layer. Eight different types of microbolometers were fabricated using a-Si x Ge 1−x or a-Si x Ge 1−x O y sensing layers and Ti, Cr, Al, Au, Ni, or Ni 0.80 Cr 0.20 metals contacts. It has been observed that bolometers with an a-Si 0.15 Ge 0.85 (Si was lightly p-doped) sensing layer formed a Schottky contact with Ti, Au, Cr, and Al contact metals, while bolometers with a-Si 0.15 Ge 0.85 (Si was heavily n-doped) sensing layers formed an Ohmic contact with Au. For microbolometers with a Si 0.15 Ge 0.85 O 0.039 sensing layer, both Ni and Ni 0.80 Cr 0.20 contact metals formed the Ohmic contact. For a-Si x Ge 1−x and a-Si x Ge 1−x O y microbolometers, Au and Ni 0.80 Cr 0.20 were used as the absorber layers, respectively. The I–V characteristics of the microbolometers were analyzed with a thermionic emission model. A linear dependence on the Ge composition was approximated to find the effective Richardson constant. The theory predicts Richardson constants of 112 and 50 A/cm 2 K 2 for Si and Ge, respectively. Barrier heights of all devices are calculated and the reasons for the formation of the Ohmic and Schottky contacts are discussed.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 teacher head, 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".