Tailoring magnetic properties in well order magnetic nanotstructures prepared by ALD technique
Bibliographic record
Abstract
Super paramagnetism, as one of the most fascinating magnetic phenomena, has been widely used in electronics, magnetic imaging, cell separation, drug delivery and cancer therapy. Super paramagnetism typically appears in a sufficient small magnetic nanoparticle, where the magnetic moment flips randomly with the thermal fluctuations. Once the size of the particle increasing, resulting in the magnetic domain merging and domain wall motion, the magnetic property undergoes a transition from the super paramagnetism to the ferromagnetism. Therefore, preparation of super paramagnetic thin films and nanostructure, instead of particles, would be a challenge since the film structure favors the formation of the large ferromagnetic domains in high-energy growth modes[1-2]. This results in a large grain size and magnetic domain. Atomic layer deposition (ALD), featured with self-limiting surface reaction, is used to synthesize the thin films and nanostructures due to its precise control of the thickness at monolayer atomic level and conformal deposition with low energy. Most of ALD deposited oxide thin films are found to be polycrystalline or amorphous with very small grain size, which is ideal for the preparation of super paramagnetic thin films and nano-structure. One of the key challenges in realizing super paramagnetism is to find a low-energy growth way to create sufficient small grains and magnetic domains which allow the magnetization randomly and rapidly reverse. In this work, well-defined super paramagnetic and ferrimagnetic Fe3O4thin films and well-ordered Fe3O4nanootube arrays are successfully grown using atomic layer deposition (ALD) technique by finely optimizing the growth condition and post-annealing process. As-grown Fe3O4thin films and nanotube arrays exhibit a conformal surface and nanocrystalline nature with the average grain size just few nanometers, resulting in a super paramagnetic behavior with a blocking temperature of 210 K (figure 1b). The in-situ grown iron oxide thin films exhibit a well-controlled morphology with the grain size less than 5 nm. The well-defined super paramagnetic loops are observed showing a near zero coercive field for the Fe3O4thin films (figure 1a). Super paramagnetic Fe3O4nanotube arrays (figure 1d-e) are in situ obtained by finely tuning the growth condition and the level of oxidization. The evolution of super papramagnetism is related to the atom-by-atom growth at a low temperature results in a very small grain size. After post-annealing the thin films in H2/Ar mixture atmosphere at 400 °C, the magnetic ordering of the magnetite films and nanotube arrays undergoes a transition from superparamagnetism to ferrimagnetism, exhibiting a distinct magnetic anisotropy.(figure 1c) Atomic layer deposition of magnetite thin films and well-ordered nanotube arrays with well-controlled morphology and magnetic properties provides great opportunities for integrating with other order parameters to realize magnetic nano-devices with potential applications in spintronics, electronics, and bio-applications.[3-4]
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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) | 0.001 | 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".