Bibliographic record
Abstract
The MOSFET was the subject of a patent in 1933, but did not reach commercial maturity until about thirty years later. The delay was principally due to a lack of understanding of the importance of the oxide/semiconductor interface, and to the time taken to develop suitable fabrication procedures, notably for the growth of the thin gate oxide. Now, in the early 21st century, the science of silicon, and the art and technology of its processing into electronic devices have reached such a state of maturity that billions of Si MOSFETs are made weekly. The claim that the Si MOSFET is the most abundant object made by mankind is difficult to refute. In this chapter the so-called ‘long-channel’ FET is considered. The basic electrostatics of the device is developed, and the DC current-voltage characteristics are derived using two models that are very widely used in the simulation of Si MOSFET integrated circuits: PSP and SPICE. PSP stands for ‘Penn-State Philips’, after the two organizations that have been largely instrumental in bringing this surface-potential model to a state of commercial viability. It is the Compact Model Council's new, industrialstandard, MOSFET model. SPICE stands for ‘Simulation Program with Integrated Circuit Emphasis’. It was originally developed by Lawrence Nagel at the University of California at Berkeley in the mid-1970s, and has evolved extensively since then. PSP is surface-potential based, whereas SPICE is threshold-voltage based.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.068 | 0.051 |
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".