Size effect studies in catalysis: a simple surfactant-free synthesis of sub 3 nm Pd nanocatalysts supported on carbon

Quinson, Jonathan; Simonsen, Søren Bredmose; Kuhn, Luise Theil; Kunz, Sebastian; Arenz, Matthias

doi:10.1039/c8ra06912c

Cited by 19 publications

(23 citation statements)

References 30 publications

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“…A surfactant-free synthesis method to produce Pt, Ir, Ru, or bimetallic NPs has recently been reported [ 22 ]. It only requires a monoalcohol as solvent and reducing agent [ 25 ], a base, and a metal precursor to obtain size-controlled NPs [ 26 – 27 ]. This approach leads to catalysts that are more active than those prepared, for example, in polyols [ 28 – 29 ].…”

Section: Resultsmentioning

confidence: 99%

Surfactant-free syntheses and pair distribution function analysis of osmium nanoparticles

Juelsholt¹,

Quinson²,

Kjær³

et al. 2022

Beilstein J. Nanotechnol.

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A surfactant-free synthesis of precious metal nanoparticles (NPs) performed in alkaline low-boiling-point solvents has been recently reported. Monoalcohols are here investigated as solvents and reducing agents to obtain colloidal Os nanoparticles by using low-temperature (<100 °C) surfactant-free syntheses. The effect of the precursor (OsCl3 or H2OsCl6), precursor concentration (up to 100 mM), solvent (methanol or ethanol), presence or absence of a base (NaOH), and addition of water (0 to 100 vol %) on the resulting nanomaterials is discussed. It is found that no base is required to obtain Os nanoparticles as opposed to the case of Pt or Ir NPs. The robustness of the synthesis for a precursor concentration up to 100 mM allows for the performance of X-ray total scattering with pair distribution function (PDF) analysis, which shows that 1–2 nm hexagonal close packed (hcp) NPs are formed from chain-like [OsOxCly] complexes.

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Section: Resultsmentioning

confidence: 99%

Surfactant-free syntheses and pair distribution function analysis of osmium nanoparticles

Juelsholt¹,

Quinson²,

Kjær³

et al. 2022

Beilstein J. Nanotechnol.

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“…A surfactant-free synthesis method to produce Pt, Ir, Ru or bimetallic NPs has been reported [22]. It only requires a mono-alcohol as solvent and reducing agent [25] a base and a metal precursor to obtain size controlled NPs [26,27]. This approach leads to catalysts that are more active than those prepared for example in polyols [28,29].…”

Section: Resultsmentioning

confidence: 99%

Surfactant-free syntheses and pair distribution function analysis of osmium nanoparticles

Juelsholt

Quinson

Kjær

et al. 2021

Preprint

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A surfactant-free synthesis of precious metal nanoparticles performed in low boiling point solvents and in alkaline conditions has been reported recently. This strategy presents several advantages over alternative colloidal syntheses. The resulting nanoparticles are readily relevant for applications like catalysis and the synthetic process is compatible with large scale production. Alkaline mono-alcohols are here investigated as solvent and reducing agents to obtain colloidal Os nanoparticles by this low temperature (< 100 °C) surfactant-free synthesis. The effect of precursor (OsCl3 or H2OsCl6), precursor concentration (up to 100 mM), solvent (methanol or ethanol), presence or absence of base (NaOH) and addition of water (0 to 100 v.%) on the resulting nanomaterials is discussed. It is fond that no base is required to obtain Os nanoparticles as opposed to the case of Pt NPs for instance. The robustness of the synthesis for concentration of precursor up to 100 mM allows to perform X-ray total scattering with pair distribution function (PDF) analysis that shows that the 1-2 nm hcp NPs forms from chain-like [OsOxCly]-complexes.

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“…This is only slightly larger than Pt, Ir or Pd nanoparticles obtained in alkaline methanol which is an encouraging sign towards the formation of multi-metallic nanomaterials. 37,41 This surfactant-free synthesis at room temperature was used here as a fast and simple production method of carbon supported mutlimettalic nanomaterials. The chloride based precursors of the used metals were mixed together with carbon flakes in alkaline methanol and left steering for 10 minutes.…”

Section: Synthesismentioning

confidence: 99%

Exploring the Relationship between the CO Oxidation Reaction and the Elemental Composition in Electrocatalysts with Machine Learning - a Case Study of PtRuPdRhAu High Entropy Alloys

Mints

Pedersen

Bagger

et al. 2021

Preprint

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In recent years, the development of complex multi-metallic nanomaterials like high entropy alloy (HEA) catalysts has gained popularity. Composed of 5 or more metals, the compositions of HEAs exhibit extreme diversity. This is both a promising avenue to identify new catalysts and a severe constraint on their preparation and study. To address the challenges related to the preparation, study and optimization of HEAs, machine learning solutions are attractive. In this paper, the composition of PtRuPdRhAu hydrogen oxidation catalysts is optimized for the CO oxidation reaction. This is achieved by constructing a dataset using Bayesian optimization as guidance. For this quinary nanomaterial, the best performing composition was found within the first 35 experiments. However, the dataset was expanded until a total of 68 samples were investigated. This final dataset was used to construct a random forest regression model and a linear model. These machine learned models were used to assess the relationships between the concentrations of the consituent elements and the CO oxidation reaction onset potential. The onset potentials were found to correlate with the composition dependent adsorption energy of *OH obtained from density functional theory. This study demonstrates, how machine learning can be employed in an experimental setting to investigate the vast compositional space of HEAs.

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Size effect studies in catalysis: a simple surfactant-free synthesis of sub 3 nm Pd nanocatalysts supported on carbon

Abstract: A simple surfactant-free synthesis of sub 3 nm carbon-supported Pd nanocatalysts is introduced to study size effects in catalysis.

Cited by 19 publications

References 30 publications

Surfactant-free syntheses and pair distribution function analysis of osmium nanoparticles

Surfactant-free syntheses and pair distribution function analysis of osmium nanoparticles

Surfactant-free syntheses and pair distribution function analysis of osmium nanoparticles

Exploring the Relationship between the CO Oxidation Reaction and the Elemental Composition in Electrocatalysts with Machine Learning - a Case Study of PtRuPdRhAu High Entropy Alloys

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