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Record W2338015967 · doi:10.1021/acs.nanolett.6b01152

Patterning Superatom Dopants on Transition Metal Dichalcogenides

2016· article· en· W2338015967 on OpenAlexfundno aff
Jaeeun Yu, Chul‐Ho Lee, Delphine Bouilly, Ming‐Yong Han, Philip Kim, Michael L. Steigerwald, Xavier Roy, Colin Nuckolls

Bibliographic record

VenueNano Letters · 2016
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsnot available
FundersAir Force Office of Scientific ResearchFonds de recherche du Québec – Nature et technologiesNatural Sciences and Engineering Research Council of CanadaKwanjeong Educational FoundationDivision of Materials ResearchNational Research Foundation of Korea
KeywordsSuperatomDopantDopingMaterials scienceTransition metalNanotechnologyFabricationMetalOptoelectronicsChemical physicsChemistryElectronic structureComputational chemistryMetallurgyOrganic chemistry

Abstract

fetched live from OpenAlex

This study describes a new and simple approach to dope two-dimensional transition metal dichalcogenides (TMDCs) using the superatom Co6Se8(PEt3)6 as the electron dopant. Semiconducting TMDCs are wired into field-effect transistor devices and then immersed into a solution of these superatoms. The degree of doping is determined by the concentration of the superatoms in solution and by the length of time the films are immersed in the dopant solution. Using this chemical approach, we are able to turn mono- and few-layer MoS2 samples from moderately to heavily electron-doped states. The same approach applied on WSe2 films changes their characteristics from hole transporting to electron transporting. Moreover, we show that the superatom doping can be patterned on specific areas of TMDC films. To illustrate the power of this technique, we demonstrate the fabrication of a lateral p-n junction by selectively doping only a portion of the channel in a WSe2 device. Finally, encapsulation of the doped films with crystalline hydrocarbon layers stabilizes their properties in an ambient environment.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient 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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score1.000

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)0.0010.001

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 head0.014
GPT teacher head0.227
Teacher spread0.213 · 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

Citations52
Published2016
Admission routes1
Has abstractyes

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