Graphene: a self-reducing template for synthesis of graphene–nanoparticles hybrids-Reference-Cited by-同舟云学术

Graphene: a self-reducing template for synthesis of graphene–nanoparticles hybrids

Published:2015 Issue:76 Volume:5 Page:62284-62289
ISSN:2046-2069
Container-title:RSC Advances
language:en
Short-container-title:RSC Adv.

Author:

Devi M. Manolata¹²³⁴,Sahu Sumit Ranjan¹²³⁴,Mukherjee Puspal⁵²³⁴,Sen Pratik⁵²³⁴,Biswas Krishanu¹²³⁴

Affiliation:

1. Department of Materials Science and Engineering

2. Indian Institute of Technology Kanpur

3. Kanpur-208016

4. India

5. Department of Chemistry

Abstract

The integration of graphene with certain metallic nanoparticles, such as Au, Ag, Pt, Pd, Cu, etc., to produce a new generation of hybrid materials is a field of intense research nowadays.

Publisher

Royal Society of Chemistry (RSC)

Subject

General Chemical Engineering,General Chemistry

Link

http://pubs.rsc.org/en/content/articlepdf/2015/RA/C5RA10593E

Reference39 articles.

1. The rise of graphene

2. Graphene-Based Materials: Synthesis, Characterization, Properties, and Applications

3. Measurement of the Elastic Properties and Intrinsic Strength of Monolayer Graphene

4. Superior Thermal Conductivity of Single-Layer Graphene

5. Ultrahigh electron mobility in suspended graphene

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