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Cited by 245

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

A general synthesis approach for supported bimetallic nanoparticles via surface inorganometallic chemistry

Open access
Ding, Kunlun, Cullen, David A., Zhang, Laibao, Cao, Zhi, Roy, Amitava D., Ivanov, Ilia N., Cao, Dongmei·2018·Science

Abstract

More alloying on silica: Controlling the stoichiometry and achieving a high degree of alloying of metals at ultrasmall scales for catalysis can be difficult. Double complex salts, formed by a cation like Pd(NH 3 ) 4 2+ and an anion like IrCl 6 2− , should be excellent precursors but are poorly soluble and difficult to adsorb directly on metal oxide surfaces. Ding et al. show that sequentially adsorbing the cations and anions from organic solvents onto a silica surface, followed by heating in hydrogen, creates well-mixed nanoparticles, most less than 3 nanometers in diameter, for a variety of alloys. These materials were then tested as catalysts for acetylene hydrogenation to ethylene. Science , this issue p. 560

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Metadata

Authors
Ding, K., Cullen, D. A., Zhang, L., Cao, Z., Roy, A. D., Ivanov, I. N., & Cao, D.
Venue
Science
Published
2018-11-02
Volume
362
Issue
6414
Pages
560-564
ISSN
  • 0036-8075 (ISSN-L)
  • 1095-9203
OpenAlex
W2899050862
Cited by
245
References
4
FWCI
9.58
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: A general synthesis approach for supported bimetallic nanoparticles via surface inorganometallic chemistry. https://app.cochat.ai/papers/10.1126/science.aau4414
The paper
Ding, K., Cullen, D. A., Zhang, L., Cao, Z., Roy, A. D., Ivanov, I. N., & Cao, D. (2018). A general synthesis approach for supported bimetallic nanoparticles via surface inorganometallic chemistry. Science. https://doi.org/10.1126/science.aau4414

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.