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Record W1514340084 · doi:10.1063/1.3467788

A kinetics model for Tb3+ recombinations in low doped Tb:Lu1.8Y0.2SiO5 crystals

2010· article· en· W1514340084 on OpenAlexaff
Pier Carlo Ricci, M. Salis, Riccardo Corpino, Carlo Maria Carbonaro, E. Fortin, A. Anedda

Bibliographic record

VenueJournal of Applied Physics · 2010
Typearticle
Languageen
FieldPhysics and Astronomy
TopicRadiation Detection and Scintillator Technologies
Canadian institutionsUniversity of Ottawa
Fundersnot available
KeywordsTerbiumYttriumCeriumLutetiumPhosphorDopingImpurityLanthanideIonChemistryAnalytical Chemistry (journal)Materials scienceOptoelectronicsInorganic chemistryOxide

Abstract

fetched live from OpenAlex

The detailed characterization of the terbium related optical properties of low doped oxyorthosilicates of lutetium and yttrium is reported. The introduction of terbium ions generates an ultraviolet absorption band peaked at about 242 nm and line shaped emissions in the 350–600 nm range. The transitions are related to the D53 and D54 levels and the analysis of the decay time measurements allows to individuate a cross relaxation mechanism among Terbium ions. We propose a three level kinetic model which is able to reproduce the experimental data allowing to discriminate among the radiative and nonradiative contributions to the transitions in the case of low content of Tb ions (nominal content 10 ppm). The reported study addresses two important goals, providing, from one side, a detailed characterization of possible inorganic phosphors, and from the other side, since traces of unwanted elements were identified in numerous commercial samples of cerium doped oxyorthosilicates, it can contribute to increase the performance of scintillator devices by revealing the optical features of one of the more diffuse and critical impurities.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.008
Threshold uncertainty score0.017

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.000
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0020.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.002

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 head0.253
Teacher spread0.239 · 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 designSimulation or modeling
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

Citations34
Published2010
Admission routes1
Has abstractyes

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