Pole Piece Effect on Improvement of Magnetic Controllability for Noncontact Micromanipulation
Bibliographic record
Abstract
A single electromagnet can be used for one-dimensional (vertical) magnetic levitation, but cannot control the distribution of the magnetic field on a horizontal plane. For three-dimensional (3-D) levitated movement of objects, an arrangement of multiple electromagnets is required. A pole piece can connect the individual poles of the electromagnets in order to eliminate the appearance of multiple poles and produce a focal point of maximum magnetic field in the horizontal plane. This paper presents the results of an investigation of the effect on different pole pieces on the regulation and control of a large gap magnetic field for 3-D micromanipulation. In a large and wide magnetic gap, a levitated object tends to stay at the maximum point of magnetic field, Bmax, in order to minimize the system energy. By producing a unique Bmaxpoint and controlling its position, 3-D levitated movement of a small permanent magnet (single magnetic dipole moment) can be realized. If the Bmaxpoint is converted into an area with a uniform field that is stronger than any nearby point (Bmaxarea), complex objects, such as microrobots affixed with several permanent magnets, can be levitated and moved. By selecting a proper pole piece and tuning the electric currents in the electromagnets, the required field distribution will be obtained. The paper proposes a number of pole pieces and discusses their effect on magnetic field distribution. Through simulation results and experimental measurements, it shows that a number of proposed pole piece profiles can generate a magnetic field for 3-D levitated motion. Finally, it reports a demonstration of 3-D levitated motion of a single magnet (using the Bmaxpoint) and a microrobot (using the Bmaxarea) to show the feasibility of the proposed method for micromanipulation
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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) | 0.000 | 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) | 0.002 | 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".