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Record W4401628624 · doi:10.1021/acs.nanolett.4c02640

Origin of Dopant-Carrier Exchange Coupling and Excitonic Zeeman Splitting in Mn<sup>2+</sup>-Doped Lead Halide Perovskite Nanocrystals

2024· article· en· W4401628624 on OpenAlexafffund
I-Hsuan Yeh, Mahdieh Ghobadifard, Feng Lin, Victor A. Galievsky, Pavle V. Radovanovic

Bibliographic record

VenueNano Letters · 2024
Typearticle
Languageen
FieldEngineering
TopicPerovskite Materials and Applications
Canadian institutionsUniversity of Waterloo
FundersNatural Sciences and Engineering Research Council of CanadaCanada First Research Excellence FundCanada Foundation for Innovation
KeywordsSpintronicsZeeman effectMagnetic circular dichroismMagnetic semiconductorDopantPerovskite (structure)Condensed matter physicsMaterials scienceExchange interactionDopingCharge carrierExcitonChemistryPhysicsFerromagnetismCrystallographyMagnetic field

Abstract

fetched live from OpenAlex

Low-dimensional metal halide perovskites have unique optical and electrical properties that render them attractive for the design of diluted magnetic semiconductors. However, the nature of dopant-exciton exchange interactions that result in spin-polarization of host-lattice charge carriers as a basis for spintronics remains unexplored. Here, we investigate Mn 2+ -doped CsPbCl 3 nanocrystals using magnetic circular dichroism spectroscopy and show that Mn 2+ dopants induce excitonic Zeeman splitting which is strongly dependent on the nature of the band-edge structure. We demonstrate that the largest splitting corresponds to exchange interactions involving the excited state at the M-point along the spin–orbit split-off conduction band edge. This splitting gives rise to an absorption-like C -term excitonic MCD signal, with the estimated effective g -factor ( g eff ) of ca. 70. The results of this work help resolve the assignment of absorption transitions observed for metal halide perovskite nanocrystals and allow for a design of new diluted magnetic semiconductor materials for spintronics 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 score0.357
Threshold uncertainty score0.994

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 head0.014
GPT teacher head0.236
Teacher spread0.222 · 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

Citations19
Published2024
Admission routes2
Has abstractyes

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