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Record W4389815603 · doi:10.1063/1674-0068/cjcp2310107

Exciton and vibrational dynamics of MAu24(SR)18 (M=Pd, Pt) nanoclusters

2023· article· en· W4389815603 on OpenAlexaff
Yanzhen Wu, Xu Liu, Jie Kong, Wei Zhang, Yan Zhu, Meng Zhou

Bibliographic record

VenueChinese Journal of Chemical Physics · 2023
Typearticle
Languageen
FieldMaterials Science
TopicNanocluster Synthesis and Applications
Canadian institutionsMinistry of Education and Child Care
Fundersnot available
KeywordsNanoclustersExcitonPhysicsAtomic physicsMaterials scienceMolecular physicsChemistryChemical physicsPhysical chemistryNanotechnologyCondensed matter physics

Abstract

fetched live from OpenAlex

The optical properties of doped metal nanoclusters (NCs) have stimulated great research interests because of their applications in biosensing and photocatalysis. The photoluminescence and excited state dynamics of MAu24(SR)18 are complicated and the detailed mechanism has not been fully understood. Here, we investigate the exciton and vibrational dynamics of two doped NCs MAu24(SR)18 (M=Pd, Pt; SR stands for phenylethanethiolate) by ultrafast spectroscopy. In contrast to the parent Au25(SR)18 NCs, Pd and Pt doping significantly reduce the exciton lifetime by several orders of magnitude. We find that the ultrashort exciton lifetimes of PtAu24 (5 ps) and PdAu24 (30 ps) are ascribed to the ultrasmall energy gap (Eg=0.3 eV). In both two doped NCs, we observe significant coherent vibrations (2.4 THz) that arise from the metal core, which indicates these oscillations can survive regardless of the short exciton lifetime. Unravelling the effect of foreign atom doping on the exciton and vibrational dynamics of metal NCs will provide new insight into their optical properties and help designing these molecular-like nanostructures for specific 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 score0.047
Threshold uncertainty score0.368

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 head0.012
GPT teacher head0.260
Teacher spread0.247 · 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

Citations3
Published2023
Admission routes1
Has abstractyes

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