Ultrafast dynamics of ferromagnetic/paramagnetic nanowires in MnAs thin films
Bibliographic record
Abstract
Thin films of MnAs on GaAs(001) possess a coexisting phase of ferromagnetic and paramagnetic periodic nanostripes between approximately 10 and 40 °C. The periodic stripes reflect an interplay between misfit and elastic strain. The films offer the possibility of using ultrafast laser heating to switch the magnetic properties for possible applications in information technology. Employing 1 kHz, 775 nm, 150 fs pump pulses and time-resolved optical diffraction and second harmonic generation we have time-resolved the dynamics of the magnetic nanowires in 150 and 190 nm thickness films to observe their destruction and regrowth. We find that the strong periodic elastic strain responsible for the periodic magnetic/structural stripes strongly influences the erasure dynamics while heat diffusion in the substrate governs stripe regrowth. From the time resolved diffraction of a 400 nm probe pulse we observe that erasure of the stripes occurs on a 5 ns time scale with the evolving periodic strain field leading to oscillation of the domains at shorter times. Regrowth of the periodic domains can take up to microseconds, depending on the initial temperature of the film. Hence we observe the dynamics over 7 orders of magnitude in time [1]. Specular second harmonic generation provides complementary information by monitoring the spatially averaged value of the surface strain field. In the periodic phase the strain field collapses in about 100 ps following the pump pulse, too long a time to explain using equilibrium thermodynamics concepts, and likely related to non-equilibrium latent heat dynamics. The surface strain recovers on a 1 ns time scale [2]. Our work reveals that strain-induced magnetic domains in thin films cannot be erased in less than 100's of ps and that the recovery of the domains, determined by heat diffusion, takes several microseconds. This imposes limitations on the applications of optical switching of magnetic domains for information technology applications.
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".