MétaCan
Menu
Back to cohort
Record W3126770688 · doi:10.1088/1361-6528/abe2cb

A reversible and stable doping technique to invert the carrier polarity of MoTe <sub>2</sub>

2021· article· en· W3126770688 on OpenAlexaff
Ms Samiya, Ali Raza, Muhammad Waqas Iqbal, Hafiz Mansoor ul Haque, Karna Ramachandraiah, Saqlain Yousuf, Seong Chan Jun, Atteq ur Rehman, Muhammad Zahir Iqbal

Bibliographic record

VenueNanotechnology · 2021
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsSimon Fraser University
FundersHigher Education Commission, Pakistan
KeywordsMaterials scienceDopingDiodeHeterojunctionOptoelectronicsSemiconductorMiniaturizationKelvin probe force microscopeStackingp–n junctionWork functionNanotechnologyAtomic force microscopyChemistry

Abstract

fetched live from OpenAlex

Abstract Two-dimensional (2D) materials can be implemented in several functional devices for future optoelectronics and electronics applications. Remarkably, recent research on p–n diodes by stacking 2D materials in heterostructures or homostructures (out of plane) has been carried out extensively with novel designs that are impossible with conventional bulk semiconductor materials. However, the insight of a lateral p–n diode through a single nanoflake based on 2D material needs attention to facilitate the miniaturization of device architectures with efficient performance. Here, we have established a physical carrier-type inversion technique to invert the polarity of MoTe 2 -based field-effect transistors (FETs) with deep ultraviolet (DUV) doping in (oxygen) O 2 and (nitrogen) N 2 gas environments. A p-type MoTe 2 nanoflake transformed its polarity to n-type when irradiated under DUV illumination in an N 2 gaseous atmosphere, and it returned to its original state once irradiated in an O 2 gaseous environment. Further, Kelvin probe force microscopy (KPFM) measurements were employed to support our findings, where the value of the work function changed from ∼4.8 and ∼4.5 eV when p-type MoTe 2 inverted to the n-type, respectively. Also, using this approach, an in-plane homogeneous p–n junction was formed and achieved a diode rectifying ratio (I f /I r ) up to ∼3.8 × 10 4 . This effective approach for carrier-type inversion may play an important role in the advancement of functional 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.

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 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 score0.007
Threshold uncertainty score0.291

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 head0.011
GPT teacher head0.234
Teacher spread0.223 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations23
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueNanotechnologySame topic2D Materials and ApplicationsFrench-language works237,207