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Record W2177833829 · doi:10.1063/1.4935752

Device performance simulations of multilayer black phosphorus tunneling transistors

2015· article· en· W2177833829 on OpenAlex

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

VenueApplied Physics Letters · 2015
Typearticle
Languageen
FieldEngineering
TopicAdvancements in Semiconductor Devices and Circuit Design
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaNational Natural Science Foundation of China
KeywordsMonolayerMaterials scienceTransistorQuantum tunnellingOptoelectronicsZigzagBlack phosphorusDopingLeakage (economics)Subthreshold swingIonThreshold voltageNanotechnologyVoltageElectrical engineeringPhysics

Abstract

fetched live from OpenAlex

We report a theoretical investigation of ballistic transport in multilayer black phosphorus (BP) tunneling transistors (TFETs) with HfO2 as the gate oxide. First-principles calculations show that monolayer BP can be preserved well on HfO2 (111) surface. For a better device performance, the optimum layer and transport direction at different channel lengths are investigated. It is shown that BP TFETs have larger drain current in the armchair direction (AD) than in the zigzag direction, and the current difference can be several orders of magnitude. On-state current can be enhanced in the BP TFETs using thicker BP film, while the minimal leakage current is increased at the same time. To reduce the leakage current and subthreshold swing in the multilayer BP TFETs, lower source/drain doping concentration and smaller drain voltage should be applied. Compared to monolayer MoS2, MoSe2, and MoTe2 TFETs monolayer BP TFETs in AD can reach larger on-state current at the same Ion/Ioff ratio.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.362
Threshold uncertainty score0.746

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 science0.0000.000
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 head0.034
GPT teacher head0.232
Teacher spread0.198 · 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