Modeling, Dynamic Simulation and Design of Magnetic Sensors Based on Magnetic Tunnel Junction Technology
Bibliographic record
Abstract
Spintronic devices, with the integration of magnetic materials and microstructures, have been enabling people to make use of the electron spin and charge properties in many applications.Few works, however, have been carried out thus far in modeling and simulation of these devices based on magnetic tunnel junction (MTJ) technology.Accordingly, this thesis proposes a novel modeling approach as well as an iterative simulation methodology for MTJs.A more comprehensive electrical tunneling model is established for better interpreting the conductance and current generated by the electron tunneling, and this model can also facilitate the iterative simulation of the micromagnetic dynamics.Given the improved tunneling model as well as the iterative dynamic simulation, the electric characteristics of an MTJ with an external magnetic field can be conveniently computed.Finally, the magnetic sensor design based on the MTJ technology and the fabrication methods are presented.These works would lay a useful foundation for the future development of new spintronic devices.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".