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Record W4321650093 · doi:10.48550/arxiv.2302.11497

Influence of atomic relaxations on the moiré flat band wavefunctions in antiparallel twisted bilayer WS$_{\text{2}}$

2023· preprint· en· W4321650093 on OpenAlexafffund
Laurent Molino, Leena Aggarwal, Indrajit Maity, Ryan Plumadore, Johannes Lischner, Adina Luican‐Mayer

Bibliographic record

VenuearXiv (Cornell University) · 2023
Typepreprint
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsUniversity of Ottawa
FundersEngineering and Physical Sciences Research CouncilNatural Sciences and Engineering Research Council of CanadaEuropean Commission
KeywordsAntiparallel (mathematics)Wave functionBilayerCondensed matter physicsMoiré patternPhysicsMolecular physicsQuantum mechanicsChemistryOpticsMembrane

Abstract

fetched live from OpenAlex

Twisting bilayers of transition metal dichalcogenides (TMDs) gives rise to a periodic moiré potential resulting in flat electronic bands with localized wavefunctions and enhanced correlation effects. In this work, scanning tunneling microscopy is used to image a WS$_{2}$ bilayer twisted approximately $3^{\circ}$ off the antiparallel alignment. Scanning tunneling spectroscopy reveals the presence of localized electronic states in the vicinity of the valence band onset. In particular, the onset of the valence band is observed to occur first in regions with a Bernal stacking in which S atoms are located on top of each other. In contrast, density-functional theory calculations on twisted bilayers which have been relaxed in vacuum predict the highest lying flat valence band to be localized in regions of AA' stacking. However, agreement with the experiment is recovered when the calculations are carried out on bilayers in which the atomic displacements from the unrelaxed positions have been reduced reflecting the influence of the substrate and finite temperature. This demonstrates the delicate interplay of atomic relaxations and the electronic structure of twisted bilayer materials.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.634
Threshold uncertainty score0.981

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.092
GPT teacher head0.207
Teacher spread0.115 · 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 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

Citations0
Published2023
Admission routes2
Has abstractyes

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