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Record W3134374865 · doi:10.1021/acsnano.1c00580

Room-Temperature Upconversion in a Nanosized {Ln<sub>15</sub>} Molecular Cluster-Aggregate

2021· article· en· W3134374865 on OpenAlexafffund
Diogo A. Gálico, Jeffrey S. Ovens, Fernando A. Sigoli, Muralee Murugesu

Bibliographic record

VenueACS Nano · 2021
Typearticle
Languageen
FieldMaterials Science
TopicLuminescence Properties of Advanced Materials
Canadian institutionsUniversity of Ottawa
FundersNatural Sciences and Engineering Research Council of CanadaCanada Foundation for InnovationUniversity of Ottawa
KeywordsPhoton upconversionLanthanideMaterials scienceExcited stateCluster (spacecraft)YtterbiumIonQuantum yieldAbsorption (acoustics)NanoparticleNanotechnologyChemical physicsDopingOptoelectronicsAtomic physicsFluorescenceChemistryOpticsPhysicsOrganic chemistry

Abstract

fetched live from OpenAlex

The successive absorption of low-energy photons to the accumulation of the intermediate excited states leading to higher energy emission is still a challenge in molecular architectures. Contrary to low-phonon solids and nanoparticles, the rational construction of molecular systems containing an excess of donor atoms in relation to acceptor ones is far from trivial. Moreover, the vibrations caused by high-energy oscillators commonly present on coordination compounds result in serious drawbacks on molecular upconversion. To overcome these limitations, we demonstrate that upconversion can be achieved even at room temperatures through the use of molecular cluster-aggregates (MCAs). To achieve the upconverted emission, we synthesized a MCA containing 15 lanthanide ions, {Er2Yb13}, ensuring an excess of donor atoms. With the excitation on the ytterbium ion, the characteristic green and red emissions from erbium were obtained at room temperature. To prove the mechanism behind the upconversion process, four other compositions were synthesized and studied, namely, {Y13Er2}, {Y10Er5}, {Er10Yb5}, and {Y10Er1Yb4}. Upconversion quantum yield values on the order of 10–3% were obtained, values 100000 times higher than for previously reported lanthanide-based molecular upconverting systems. The presented methodology is an interesting approach to address a fine composition control and harness the upconversion properties of nanoscale molecular materials.

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 categoriesMeta-epidemiology (narrow)
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 score0.002
Threshold uncertainty score1.000

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 communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.006
GPT teacher head0.216
Teacher spread0.210 · 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.

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

Citations50
Published2021
Admission routes2
Has abstractyes

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