Impact of carbon concentration on 1∕f noise and random telegraph signal noise in SiGe:C heterojunction bipolar transistors
Bibliographic record
Abstract
The influence of carbon concentration on the low-frequency noise (LF noise) of Si∕SiGe:C∕Si heterojunction bipolar transistors (HBTs) is investigated. When carbon is incorporated into these HBTs, representative noise spectra of the input current spectral density SIB show significant generation-recombination (GR) components. On the other hand, for transistors without carbon incorporation, no GR components were observed. When only 1∕f noise component is observed, the 1∕f noise level is found to be independent of the carbon concentration and the associated figure of merit of the normalized noise magnitude KB has a very good value of ∼4×10−10μm2. In order to relate the 1∕f noise and the high-frequency performance of the transistor, we studied and modeled the figure of merit defined as the ratio fc∕fT (fc is the low-frequency corner frequency and fT the unity current-gain frequency). Then we performed a detailed analysis of the GR components associated with the presence of the carbon. We found that the observed Lorentzian spectra are associated with random telegraph signal (RTS) noise. However, no RTS noise was measured in carbon-free devices. It is believed that the RTS noise is due to electrically active defects formed by the addition of carbon, typically observed for concentrations above the bulk solid solubility limit in silicon. The RTS amplitude (ΔIB) is found to scale with the base current, to decrease exponentially with temperature, and to be independent of the carbon concentration. The mean pulse widths (tH,tL) of the RTS are found to decrease rapidly with bias voltage, as 1∕exp(qVBE∕kT) or stronger. Our results confirm that electrically active C-related defects are located in the base-emitter junction, and the RTS amplitude is explained by a model based on voltage barrier height fluctuations across the base-emitter junction induced by trapped carriers in the space charge region. The observed bias dependence of mean pulse widths seems to indicate that two capture processes are involved, electron and hole capture. These C-related defects behave like recombination centers with deep energy levels rather than electron or hole traps involving trapping-detrapping processes.
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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 | 0.000 | 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) | 0.000 | 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".