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Record W2801480012 · doi:10.1109/tnano.2018.2877524

The Stability of Exfolicated FeSe Nanosheets During in-air Device Fabrication Processes

2018· article· en· W2801480012 on OpenAlex
Rui Yang, Weijun Luo, Shun Chi, D. A. Bonn, Guangrui Xia

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIEEE Transactions on Nanotechnology · 2018
Typearticle
Languageen
FieldMaterials Science
TopicIron-based superconductors research
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaUniversity of British ColumbiaCanada Foundation for Innovation
KeywordsFabricationMaterials scienceRaman spectroscopySuperconductivityEvaporationSpectroscopyWaferNanotechnologyExfoliation jointOptoelectronicsOpticsCondensed matter physics

Abstract

fetched live from OpenAlex

We studied the stability and superconductivity of FeSe nanosheets during an in-air device fabrication process. Methods were developed to improve the exfoliation yield and to maintain the superconductivity of FeSe. Raman spectroscopy, atomic force microscopy, optical microscopy, and time-of-flight-secondary-ion-mass-spectroscopy measurements show that FeSe nanosheets decayed in air. Precipitation of Se particles and the oxidation of iron likely occurred during the decay process. Transport measurements revealed that the superconductivity of FeSe disappeared during a conventional electron beam lithography process. Shadow mask evaporation and transfer onto pre-defined electrodes methods were shown to be effective in maintaining the superconductivity after the in-air device fabrication process. These methods developed provide a way of making high quality FeSe nano-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.

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 score0.008
Threshold uncertainty score0.468

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
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 head0.027
GPT teacher head0.286
Teacher spread0.259 · 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