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Record W4283377632 · doi:10.1103/physrevb.105.214518

Modulation doping of the FeSe monolayer on <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML"><mml:msub><mml:mrow><mml:mi>SrTiO</mml:mi></mml:mrow><mml:mn>3</mml:mn></mml:msub></mml:math>

2022· article· lv· W4283377632 on OpenAlexafffund
Fengmiao Li, Ilya Elfimov, G. A. Sawatzky

Bibliographic record

VenuePhysical review. B./Physical review. B · 2022
Typearticle
Languagelv
FieldMaterials Science
TopicIron-based superconductors research
Canadian institutionsUniversity of British Columbia
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence FundCanada Foundation for Innovation
KeywordsDopingCondensed matter physicsSuperconductivityMonolayerMaterials scienceHeterojunctionPhysicsNanotechnology

Abstract

fetched live from OpenAlex

The discovery of higher-temperature superconductivity in FeSe monolayers on ${\mathrm{SrTiO}}_{3}$ substrates has sparked a surge of interest in the interface superconductivity. One point of agreement reached to date is that modulation doping by impurities in the substrate is critical for the enhanced superconductivity. Remarkably, the universal doping about 0.1 electrons per Fe, i.e., so-called ``magic'' doping, has been observed on a range of Ti oxide substrates, which concludes that there likely is some important interaction limiting the FeSe doping. Our study discovers that the polarization change at the interface Se because of the close proximity to the substrate from that in the free-standing FeSe film significantly amplifies the total potential difference at the interface above and beyond the work function difference for charge transfer. Additionally, the titanate substrate with a large number of free electrons basically serves as an ``infinite'' charge reservoir, which leads to the saturated FeSe doping with the complete removal of the interface potential gradient. Our work has developed the theory for modulation doping in the van der Waals materials/oxides heterostructure, providing a solution to the puzzle of magic doping in FeSe monolayers on titanates. The information also presents experimental pathways to accommodate a variable carrier density of FeSe monolayers via modulation doping.

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)0.003
metaresearch head score (Gemma)0.004
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.833
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.004
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0000.002
Science and technology studies0.0010.001
Scholarly communication0.0000.001
Open science0.0030.003
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0750.004

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 head0.032
GPT teacher head0.310
Teacher spread0.278 · 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; both teacher heads agree on what is shown here.

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

Citations5
Published2022
Admission routes2
Has abstractyes

Explore more

Same venuePhysical review. B./Physical review. BSame topicIron-based superconductors researchFrench-language works237,207