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Record W2807653522 · doi:10.1038/s41598-018-24736-x

Magnetic Field Enhanced Superconductivity in Epitaxial Thin Film WTe2

2018· article· en· W2807653522 on OpenAlexafffund
Tomoya Asaba, Yongjie Wang, Gang Li, Ziji Xiang, Colin Tinsman, Lu Chen, Zhou Shangnan, Songrui Zhao, David Laleyan, Yi Li, Zetian Mi, Lü Li

Bibliographic record

VenueScientific Reports · 2018
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsMcGill University
FundersArmy Research OfficeDivision of Electrical, Communications and Cyber SystemsDivision of Materials ResearchHigh Magnetic Field Laboratory, Chinese Academy of SciencesOffice of Naval ResearchJohns Hopkins UniversityNatural Sciences and Engineering Research Council of CanadaNational High Magnetic Field LaboratoryU.S. Department of EnergyNational Science Foundation
KeywordsCondensed matter physicsSuperconductivityCritical fieldMagnetic fieldThin filmMolecular beam epitaxyMaterials scienceElectrical resistivity and conductivityEpitaxyPhysicsNanotechnologyLayer (electronics)Quantum mechanics

Abstract

fetched live from OpenAlex

Abstract In conventional superconductors an external magnetic field generally suppresses superconductivity. This results from a simple thermodynamic competition of the superconducting and magnetic free energies. In this study, we report the unconventional features in the superconducting epitaxial thin film tungsten telluride (WTe 2 ). Measuring the electrical transport properties of Molecular Beam Epitaxy (MBE) grown WTe 2 thin films with a high precision rotation stage, we map the upper critical field H c 2 at different temperatures T . We observe the superconducting transition temperature T c is enhanced by in-plane magnetic fields. The upper critical field H c 2 is observed to establish an unconventional non-monotonic dependence on temperature. We suggest that this unconventional feature is due to the lifting of inversion symmetry, which leads to the enhancement of H c 2 in Ising superconductors.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.023
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0060.001

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 head0.015
GPT teacher head0.263
Teacher spread0.248 · 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.

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

Citations39
Published2018
Admission routes2
Has abstractyes

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