Simultaneous diamagnetic and magnetic particle trapping in ferrofluid microflows via a single permanent magnet
Bibliographic record
Abstract
Trapping and preconcentrating particles and cells for enhanced detection and analysis are often essential in many chemical and biological applications. Existing methods for diamagnetic particle trapping require the placement of one or multiple pairs of magnets nearby the particle flowing channel. The strong attractive or repulsive force between the magnets makes it difficult to align and place them close enough to the channel, which not only complicates the device fabrication but also restricts the particle trapping performance. This work demonstrates for the first time the use of a single permanent magnet to simultaneously trap diamagnetic and magnetic particles in ferrofluid flows through a T-shaped microchannel. The two types of particles are preconcentrated to distinct locations of the T-junction due to the induced negative and positive magnetophoretic motions, respectively. Moreover, they can be sequentially released from their respective trapping spots by simply increasing the ferrofluid flow rate. In addition, a three-dimensional numerical model is developed, which predicts with a reasonable agreement the trajectories of diamagnetic and magnetic particles as well as the buildup of ferrofluid nanoparticles.
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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 | 0.000 |
| 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 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".