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Record W3195977683 · doi:10.3390/molecules26164926

Solution/Ammonolysis Syntheses of Unsupported and Silica-Supported Copper(I) Nitride Nanostructures from Oxidic Precursors

2021· article· en· W3195977683 on OpenAlexaff
Robert Szczęsny, Tuan K.A. Hoang, Liliana Dobrzańska, Duncan H. Gregory

Bibliographic record

VenueMolecules · 2021
Typearticle
Languageen
FieldChemistry
TopicNanomaterials for catalytic reactions
Canadian institutionsHydro-Québec
FundersEngineering and Physical Sciences Research CouncilUniversity of Glasgow
KeywordsHydroxideChemistryNanoparticleCopperNanorodNitrideChemical engineeringInorganic chemistryPhase (matter)OxideMaterials scienceNanotechnologyOrganic chemistry

Abstract

fetched live from OpenAlex

Herein we describe an alternative strategy to achieve the preparation of nanoscale Cu3N. Copper(II) oxide/hydroxide nanopowder precursors were successfully fabricated by solution methods. Ammonolysis of the oxidic precursors can be achieved essentially pseudomorphically to produce either unsupported or supported nanoparticles of the nitride. Hence, Cu3N particles with diverse morphologies were synthesized from oxygen-containing precursors in two-step processes combining solvothermal and solid−gas ammonolysis stages. The single-phase hydroxochloride precursor, Cu2(OH)3Cl was prepared by solution-state synthesis from CuCl2·2H2O and urea, crystallising with the atacamite structure. Alternative precursors, CuO and Cu(OH)2, were obtained after subsequent treatment of Cu2(OH)3Cl with NaOH solution. Cu3N, in the form of micro- and nanorods, was the sole product formed from ammonolysis using either CuO or Cu(OH)2. Conversely, the ammonolysis of dicopper trihydroxide chloride resulted in two-phase mixtures of Cu3N and the monoamine, Cu(NH3)Cl under similar experimental conditions. Importantly, this pathway is applicable to afford composite materials by incorporating substrates or matrices that are resistant to ammoniation at relatively low temperatures (ca. 300 °C). We present preliminary evidence that Cu3N/SiO2 nanocomposites (up to ca. 5 wt.% Cu3N supported on SiO2) could be prepared from CuCl2·2H2O and urea starting materials following similar reaction steps. Evidence suggests that in this case Cu3N nanoparticles are confined within the porous SiO2 matrix.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.003
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
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)0.0010.000

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 head0.011
GPT teacher head0.223
Teacher spread0.211 · 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

Citations4
Published2021
Admission routes1
Has abstractyes

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