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Record W1997159551 · doi:10.1103/physrevb.90.125441

Electrical contacts to monolayer black phosphorus: A first-principles investigation

2014· article· en· W1997159551 on OpenAlexafffund
Kui Gong, Lei Zhang, Wei Ji, Hong Guo

Bibliographic record

VenuePhysical Review B · 2014
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of ChinaCompute Canada
KeywordsBlack phosphorusMonolayerPhosphorusMaterials scienceEngineering physicsEnvironmental scienceNanotechnologyPhysicsOptoelectronicsMetallurgy

Abstract

fetched live from OpenAlex

We report first-principles theoretical investigations of possible metal contacts to monolayer black phosphorus (BP). By analyzing lattice geometry, five metal surfaces are found to have minimal lattice mismatch with BP: Cu(111), Zn(0001), In(110), Ta(110), and Nb(110). Further studies indicate Ta and Nb bond strongly with monolayer BP causing substantial bond distortions, but the combined Ta-BP and Nb-BP form good metal surfaces to contact a second layer BP. By analyzing the geometry, bonding, electronic structure, charge transfer, potential, and band bending, it is concluded that Cu(111) is the best candidate to form excellent Ohmic contact to monolayer BP. The other four metal surfaces or combined surfaces also provide viable structures to form metal/BP contacts, but they have Schottky character. Finally, the band bending property in the current-in-plane (CIP) structure where metal/BP is connected to a freestanding monolayer BP, is investigated. By both work function estimates and direct calculations of the two-probe CIP structure, we find that the freestanding BP channel is $n$ type.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.004
Threshold uncertainty score0.012

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.030
GPT teacher head0.293
Teacher spread0.263 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations132
Published2014
Admission routes2
Has abstractyes

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