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Record W2947351351 · doi:10.1021/acscentsci.9b00288

A Luminescent Thermometer Exhibiting Slow Relaxation of the Magnetization: Toward Self-Monitored Building Blocks for Next-Generation Optomagnetic Devices

2019· article· en· W2947351351 on OpenAlexafffund
Dylan Errulat, Riccardo Marin, Diogo A. Gálico, Katie L. M. Harriman, Amélie Pialat, Bulat Gabidullin, F. Iikawa, O. D. D. Couto, Jani O. Moilanen, Eva Hemmer, Fernando A. Sigoli, Muralee Murugesu

Bibliographic record

VenueACS Central Science · 2019
Typearticle
Languageen
FieldMaterials Science
TopicMagnetism in coordination complexes
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCoordenação de Aperfeiçoamento de Pessoal de Nível SuperiorFundação de Amparo à Pesquisa do Estado de São PauloConselho Nacional de Desenvolvimento Científico e TecnológicoUniversity of Ottawa
KeywordsThermometerZeeman effectLuminescenceMaterials scienceMagnetizationRelaxation (psychology)NanotechnologyOptoelectronicsAtmospheric temperature rangePhotoluminescenceFabricationMagnetChemical physicsMagnetic fieldChemistryElectrical engineeringThermodynamicsPhysics

Abstract

fetched live from OpenAlex

], which exhibits slow relaxation of the magnetization along with remarkable photoluminescent properties. This combination allows the gaining of fundamental insight in the electronic properties of the compound and investigation of optomagnetic cross-effects (Zeeman effect). Importantly, spectral variations stemming from two distinct thermal-dependent mechanisms taking place at the molecular level are used to perform luminescence thermometry over the 5-398 K temperature range. Overall, these properties make the proposed system a unique molecular luminescent thermometer bearing SMM properties, which preserves its temperature self-monitoring capability even under applied magnetic fields.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.028
GPT teacher head0.260
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), 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

Citations163
Published2019
Admission routes2
Has abstractyes

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