Investigation of switching characteristics of nanomagnets via magnetic force microscopy
Bibliographic record
Abstract
Magnetic quantum cellular automata (MQCA) have been proposed as an alternate computing architecture. Single domain magnetic particles represent "1" or "0"; their stray field interaction controls the propagation and manipulation of information. An inherent requirement for an MQCA system is to know the conditions under which nanomagnets switch between the purely "up" (1) and the purely "down" (0) state, and to control this reproducibly. As a first step to study this, arrays of two types of permalloy particles were designed, simulated, fabricated and imaged, and their switching distributions ascertained. Individual particles were "peanut"-shaped, to investigate the effect of a shape anisotropy for an elliptical particle. Particles had long axes of 750 nm and 250 nm, but had identical aspect ratios. Particles were simulated with a public domain software package, Object Oriented Micromagnetic Framework (OOMMF), fabricated by electron beam lithography with standard lift-off techniques in the fabrication facility in Sherbrooke, Canada, and imaged in vacuum using a custom built magnetic force microscope in constant height mode with an in plane, in-situ magnetic field. Ensemble hysteresis loops were obtained as was the average switching fields for both arrays. The 750 nm particles were found experimentally to have a two-step switching process. The first switch occurred at 60 +/- 16 Oe and the second at 130 +/- 56 Oe. These results were nominally better than those obtained in a previous study on similarly sized ellipses. Simulations on the 250 nm particles predicted that particles of that size would have the single domain configuration as their virgin state, and would have a one-step switching process. The switching field of a typical particle was calculated to be 550 +/- 30 Oe. This was confirmed experimentally, where the switching field distribution had its peak at 490 +/- 40 Oe. Thus, theory and experiment are in agreement, within error.
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 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".