Thermally-driven large current-perpendicular-to-plane magnetoresistance in ultrathin flakes of vanadium diselenide
Bibliographic record
Abstract
Abstract Current-perpendicular-to-plane magnetoresistance (CPP MR) in layered heterojunctions is at the heart of modern magnetic field sensing and data storage technologies. van der waals heterostructures and two-dimensional (2D) magnets opened a new playground for exploring this effect, although most 2D magnets exhibit large CPP MR only at very low temperatures due to their very low Curie temperatures. vanadium diselenide (VSe2) is a promising material since its monolayers can potentially act as room temperature ferromagnets. VSe2 multilayers have been predicted to exhibit CPP MR effects, although experimental work in this area remains scarce. In this work we investigate CPP MR in 1T-VSe2 ultrathin flakes, revealing a large (∼60%–70%), positive, linear, and non saturating CPP MR, which persists close to room temperature (∼250 K), in a relatively small magnetic field range of ±12 kG. The CPP MR has been found to increase with decreasing flake thickness. The CPP MR originates due to the intrinsic inhomogeneity in the CPP transport path, and exhibits unprecedented immunity against thermal fluctuations, leading to increasingly enhanced MR as temperature is increased, even significantly beyond the charge density wave transition temperature. The observed ‘thermally-driven’ MR features are remarkably robust and reproducible, and can offer a viable route for developing practical room temperature 2D based magnetic sensor technologies. Our results also suggest that harnessing similar effects in other 2D systems could result in large MR as well, thereby motivating further research on CPP transport in these systems, which has been relatively unexplored so far.
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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".