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Record W4318928374 · doi:10.1039/d2nr07141j

Trends in energy and charge transfer in 2D and integrated perovskite heterostructures

2023· review· en· W4318928374 on OpenAlexaff
Sikandar Aftab, Muhammad Zahir Iqbal, H.H. Hegazy, Sikander Azam, Fahmid Kabir

Bibliographic record

VenueNanoscale · 2023
Typereview
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsSimon Fraser University
FundersKing Khalid UniversityNational Research Foundation of Korea
KeywordsHeterojunctionPerovskite (structure)van der Waals forceCharge (physics)Materials scienceRange (aeronautics)NanotechnologyTransition metalChemical physicsEnergy transferEngineering physicsOptoelectronicsCondensed matter physicsChemistryPhysicsCatalysisCrystallographyMoleculeQuantum mechanics

Abstract

fetched live from OpenAlex

stacking, separation, and dielectric angles. This focused review article summarizes the most recent and promising strategies for interlayer exciton emission in 2D or integrated perovskites and TMD heterostructures. These types of devices require a thorough comprehension and effective control of interlayer couplings in order to realize their functionalities and improve performance, which is demonstrated in this article with the energy or charge transfer mechanisms in the individual devices. An ideal platform for examining the interlayer coupling and the related physical processes is provided by a summary of the recent research findings in 2D perovskites and TMDs. Furthermore, it would encourage more investigation into the comprehension and regulation of excitonic effects and the related optoelectronic applications in vdW heterostructures over a broad spectral response range. Finally, the current challenges and prospects are summarized in this paper.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.996
Threshold uncertainty score0.973

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.023
GPT teacher head0.267
Teacher spread0.244 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations18
Published2023
Admission routes1
Has abstractyes

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