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Record W4283823414 · doi:10.1063/5.0095819

Anomalous Hall effect in nanoscale structures of the antiferromagnetic Weyl semimetal Mn3Sn at room temperature

2022· article· en· W4283823414 on OpenAlexfundno aff
Takumi Matsuo, Tomoya Higo, Daisuke Nishio‐Hamane, Satoru Nakatsuji

Bibliographic record

VenueApplied Physics Letters · 2022
Typearticle
Languageen
FieldPhysics and Astronomy
TopicMagnetic properties of thin films
Canadian institutionsnot available
FundersJST-Mirai ProgramCore Research for Evolutional Science and TechnologyDivision of Materials ResearchJapan Society for the Promotion of ScienceOffice of ScienceMinistry of Education, Culture, Sports, Science and TechnologyUniversity of TokyoCanadian Institute for Advanced ResearchBasic Energy SciencesHattori Hokokai FoundationU.S. Department of Energy
KeywordsWeyl semimetalCondensed matter physicsAntiferromagnetismFerromagnetismHall effectMaterials scienceNanoscopic scaleSemimetalCrystalliteMagnetizationNanotechnologyMagnetic fieldPhysics

Abstract

fetched live from OpenAlex

The magnetic Weyl semimetallic state in the chiral antiferromagnet Mn3Sn has attracted interest for its potential in memory technology. Despite vanishingly small magnetization, the material exhibits large transverse responses that can be electrically manipulated, similar to ferromagnets. Through deposition on heated Si/SiO2 substrates, we have fabricated polycrystalline Mn3Sn films that have coarse surfaces, the thinner of which have a discontinuous structure comprised of grains with diameters of the order of 100 nm. We confirm that these grains retain the anomalous Hall effect arising in the time reversal symmetry broken chiral antiferromagnetic phase of Mn3Sn at room temperature by serially connecting the grains with an additional conducting layer. These results pave the path for the potential applications of nanoscale Mn3Sn systems, which could be useful in the development of energy efficient memory devices.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.028
Threshold uncertainty score0.916

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.003
GPT teacher head0.177
Teacher spread0.173 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations6
Published2022
Admission routes1
Has abstractyes

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