MétaCan
Menu
Back to cohort
Record W2321489630 · doi:10.1021/acs.jpcc.5b12677

Bandgap Transition of 2H Transition Metal Dichalcogenides: Predictive Tuning via Inherent Interface Coupling and Strain

2016· article· en· W2321489630 on OpenAlexafffund
Bin Ouyang, Zetian Mi, Jun Song

Bibliographic record

VenueThe Journal of Physical Chemistry C · 2016
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsMcGill University
FundersNatural Sciences and Engineering Research Council of CanadaFaculty of Engineering, McGill University
KeywordsDensity functional theoryHeterojunctionMaterials scienceMonolayerStrain engineeringCoupling (piping)BilayerTransition metalBand gapCondensed matter physicsPhase transitionPhase (matter)Strain (injury)Electronic band structureDirect and indirect band gapsElectronic structureChemical physicsNanotechnologyOptoelectronicsChemistryComputational chemistryMembranePhysicsComposite material

Abstract

fetched live from OpenAlex

Phase transitions within two-dimensional transition metal dichalcogenides (TMD) promise new possibilities for engineering their properties. Using first-principles density functional theory (DFT) calculations, we systematically examined the interfacial electronic coupling between the 2H phase monolayer with its polymorphic phases in several group IV TMD, i.e., MoS 2 (MoSe 2 ) and WS 2 (WSe 2 ), inherent bilayer heterostructures. It is found that the interface coupling, augmented by in-plane strain, can greatly modify the band structure of the 2H phase to induce bandgap transition (either indirect-to-direct or direct-to-indirect). Moreover, the effects of strain on the band structure can be well understood and predicted within the framework of deformation potential theory. The present study provides important insights toward engineering optoelectronic properties of TMD-based 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 score0.050
Threshold uncertainty score0.203

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 head0.012
GPT teacher head0.251
Teacher spread0.239 · 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

Citations33
Published2016
Admission routes2
Has abstractyes

Explore more

Same venueThe Journal of Physical Chemistry CSame topic2D Materials and ApplicationsFrench-language works237,207