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Record W4214730567 · doi:10.1021/acs.nanolett.1c01590

Electrically Switchable Intervalley Excitons with Strong Two-Phonon Scattering in Bilayer WSe<sub>2</sub>

2022· article· en· W4214730567 on OpenAlexaff
Mashael M. Altaiary, Erfu Liu, Ching-Tarng Liang, Fu-Chen Hsiao, Jeremiah van Baren, Takashi Taniguchi, Kenji Watanabe, Nathaniel M. Gabor, Yia‐Chung Chang, Chun Hung Lui

Bibliographic record

VenueNano Letters · 2022
Typearticle
Languageen
FieldMaterials Science
Topic2D Materials and Applications
Canadian institutionsCanadian Institute for Advanced Research
FundersDivision of Materials ResearchCore Research for Evolutional Science and TechnologyU.S. NavyMinistry of Science and Technology, TaiwanMinistry of Education, Culture, Sports, Science and Technology
KeywordsExcitonCondensed matter physicsPhononScatteringBilayerElectric fieldBiexcitonDipoleSemiconductorPhysicsMaterials scienceChemistryOptoelectronicsOpticsQuantum mechanics

Abstract

fetched live from OpenAlex

We report the observation of QΓ intervalley exciton in bilayer WSe2 devices encapsulated by boron nitride. The QΓ exciton resides at ∼18 meV below the QK exciton. The QΓ and QK excitons exhibit different Stark shifts under an out-of-plane electric field due to their different interlayer dipole moments. By controlling the electric field, we can switch their energy ordering and control which exciton dominates the luminescence of bilayer WSe2. Remarkably, both QΓ and QK excitons exhibit unusually strong two-phonon replicas, which are comparable to or even stronger than the one-phonon replicas. By detailed theoretical simulation, we reveal the existence of numerous (≥14) two-phonon scattering paths involving (nearly) resonant exciton–phonon scattering in bilayer WSe2. To our knowledge, such electric-field-switchable intervalley excitons with strong two-phonon replicas have not been found in any other two-dimensional semiconductors. These make bilayer WSe2 a distinctive valleytronic material with potential novel applications.

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 score0.003
Threshold uncertainty score0.796

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 head0.009
GPT teacher head0.218
Teacher spread0.209 · 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

Citations27
Published2022
Admission routes1
Has abstractyes

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