Control of the antiferromagnetic domain configuration and Néel axis orientation with epitaxial strain
Bibliographic record
Abstract
In the growing field of spintronic devices incorporating antiferromagnetic materials, control of the domain configuration and Néel axis orientation is critical for technological implementations. Here we show by X-ray magnetic linear dichroism in photoelectron emission microscopy how antiferromagnetic properties of LaFeO3 (LFO) thin films can be tailored through epitaxial strain. LFO films were grown via molecular beam epitaxy with precise stoichiometric control, using substrates that span a range of strain states—from compressive to tensile—and crystal symmetries, including different crystallographic orientations. First, we show that epitaxial strain dictates the Néel axis orientation, shifting it from completely in-plane under compressive strain to completely out-of-plane under tensile strain, regardless of the substrate crystal symmetry. Second, we find that LFO films grown on cubic substrates exhibit a fourfold distribution of antiferromagnetic domains, but can be controlled by varying the substrate miscut, while those on orthorhombic substrates, regardless of strain state, form large-scale monodomains, a highly desirable feature for spintronic applications. Precise control over antiferromagnetic domain configurations and Néel axis orientation is essential for technological advancement of spintronic devices. Here, the authors use epitaxial strain to tailor the magnetic properties of LaFeO3 thin films, demonstrating a crystal engineering approach which may have much wider applicability.
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 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".