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Record W2284089878 · doi:10.1021/acsnano.5b07219

Cu<sub>2</sub>Se and Cu Nanocrystals as Local Sources of Copper in Thermally Activated <i>In Situ</i> Cation Exchange

2016· article· en· W2284089878 on OpenAlexaff
Alberto Casu, Alessandro Genovese, Liberato Manna, Paolo Longo, Joka Buha, Gianluigi A. Botton, Sorin Lazar, Mousumi Upadhyay Kahaly, Udo Schwingenschlöegl, Mirko Prato, Hongbo Li, Sandeep Ghosh, Francisco Palazón, Francesco De Donato, Sergio Lentijo Mozo, Efisio Zuddas, Andrea Falqui

Bibliographic record

VenueACS Nano · 2016
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsMcMaster University
FundersEuropean Research CouncilEuropean Commission
KeywordsCopperNanocrystalIn situMaterials scienceInorganic chemistryChemical engineeringNanotechnologyMetallurgyChemistryOrganic chemistry

Abstract

fetched live from OpenAlex

Among the different synthesis approaches to colloidal nanocrystals, a recently developed toolkit is represented by cation exchange reactions, where the use of template nanocrystals gives access to materials that would be hardly attainable via direct synthesis. Besides, postsynthetic treatments, such as thermally activated solid-state reactions, represent a further flourishing route to promote finely controlled cation exchange. Here, we report that, upon in situ heating in a transmission electron microscope, Cu2Se or Cu nanocrystals deposited on an amorphous solid substrate undergo partial loss of Cu atoms, which are then engaged in local cation exchange reactions with Cu "acceptor" phases represented by rod- and wire-shaped CdSe nanocrystals. This thermal treatment slowly transforms the initial CdSe nanocrystals into Cu(2-x)Se nanocrystals, through the complete sublimation of Cd and the partial sublimation of Se atoms. Both Cu "donor" and "acceptor" particles were not always in direct contact with each other; hence, the gradual transfer of Cu species from Cu2Se or metallic Cu to CdSe nanocrystals was mediated by the substrate and depended on the distance between the donor and acceptor nanostructures. Differently from what happens in the comparably faster cation exchange reactions performed in liquid solution, this study shows that slow cation exchange reactions can be performed at the solid state and helps to shed light on the intermediate steps involved in such reactions.

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)0.001
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 score0.012
Threshold uncertainty score0.350

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 head0.017
GPT teacher head0.226
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.

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

Citations28
Published2016
Admission routes1
Has abstractyes

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