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Record W2466875599 · doi:10.1063/1.4955188

Bandgap modulation in photoexcited topological insulator Bi2Te3 via atomic displacements

2016· article· en· W2466875599 on OpenAlexaff
Masaki Hada, Katsura Norimatsu, Seiichi Tanaka, Sercan Keskin, Tetsuya Tsuruta, Kyushiro Igarashi, T. Ishikawa, Yōsuke Kayanuma, R. J. Dwayne Miller, Ken Onda, T. Sasagawa, Shin‐ya Koshihara, Kazutaka G. Nakamura

Bibliographic record

VenueThe Journal of Chemical Physics · 2016
Typearticle
Languageen
FieldPhysics and Astronomy
TopicTopological Materials and Phenomena
Canadian institutionsUniversity of Toronto
FundersCore Research for Evolutional Science and TechnologyJapan Science and Technology AgencyJapan Society for the Promotion of Science
KeywordsPhotoexcitationTopological insulatorBand gapBismuthElectronic structureMaterials scienceInfraredSpectroscopyOptoelectronicsChemistryMolecular physicsAtomic physicsCondensed matter physicsPhysicsOpticsExcited state

Abstract

fetched live from OpenAlex

The atomic and electronic dynamics in the topological insulator (TI) Bi2Te3 under strong photoexcitation were characterized with time-resolved electron diffraction and time-resolved mid-infrared spectroscopy. Three-dimensional TIs characterized as bulk insulators with an electronic conduction surface band have shown a variety of exotic responses in terms of electronic transport when observed under conditions of applied pressure, magnetic field, or circularly polarized light. However, the atomic motions and their correlation between electronic systems in TIs under strong photoexcitation have not been explored. The artificial and transient modification of the electronic structures in TIs via photoinduced atomic motions represents a novel mechanism for providing a comparable level of bandgap control. The results of time-domain crystallography indicate that photoexcitation induces two-step atomic motions: first bismuth and then tellurium center-symmetric displacements. These atomic motions in Bi2Te3 trigger 10% bulk bandgap narrowing, which is consistent with the time-resolved mid-infrared spectroscopy results.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.716
Threshold uncertainty score0.472

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 head0.241
Teacher spread0.229 · 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

Citations32
Published2016
Admission routes1
Has abstractyes

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