Bibliographic record
Abstract
The primary objective of the work described in this thesis was to study the influence of undoped LEC GaAs substrate material from various suppliers on the performance of ion implanted and annealed active layers. Optical transient current spectroscopy (OTCS) was investigated as a qualification test for GaAs substrates. Deep level spectra of the substrates before ion implantation were obtained. It was found that while the OTCS spectra of high pressure grown GaAs from two suppliers were similar, that of the low pressure material showed different relative concentration of traps. The use of OTCS was further extended to study trap concentration as a function of surface treatment. It was found that the use of chemical etchants reduces the concentration of some levels, possibly those located on the surface as opposed to bulk traps. Surface damage was found to enhance the negative peak in the OTCS spectrum. The deep levels spectra were found to be affected by the geometry of the device and the type of electrode material. Channel current deep level transient spectroscopy (DLTS) was used to study both process- and substrate-induced deep levels in ion implanted MESFET channels. The spectra of process-induced traps were found to be different according to the encapsulant used. Silicon dioxide (both RF sputtered and plasma enhanced chemically vapor deposited (PECVD)) was found to induce a variety of process related defects. This is believed to be because silicon dioxide is permeable to gallium and hence does not preserve the stoichiometry of ion implanted GaAs during high temperature anneals. Deep level spectra of MESFETs annealed using silicon nitride, on the other hand, were found to contain single traps related to the defects in the starting material. For implants through silicon nitride, a high concentration of the main electron trap EL2 was found, whereas implants directly into the surface resulted in the level EL12. Comparison of the characteristics of the variety of LEC undoped GaAs material show that they differed widely and had inhomogeneous properties. For example, compared to the high pressure grown GaAs, the Litton’s low pressure substrate had lower activation, mobility, drain current and threshold voltage, good confinement of the scatter in the same characteristics, low concentration of deep levels, and the least backgating effect which makes it promising for IC fabrication. Comparison of the high pressure grown material from two suppliers showed that Cominco's recent material had good mobility, activation, relatively high scatter of threshold voltage, high concentration of deep levels, and was affected by backgating. In comparison, Sumitomo's material showed thermal instability, less scatter of threshold voltage, less mobility and deep level concentrations, and similar backgating characteristics. Substrate grown three years earlier showed higher diffusion of dopant, different deep levels, and better backgating characteristics. Finally, a substrate which had failed the qualification test by a device manufacturer showed minimal diffusion tails and threshold voltage scatter, the highest concentration of deep levels, and substantial backgating.
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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".