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Direct formation of gold nanoparticles on substrates using a novel ZnO sacrificial templated-growth hydrothermal approach and their properties in organic memory device

Lean Poh Goh1, Khairunisak Abdul Razak12*, Nur Syafinaz Ridhuan12, Kuan Yew Cheong1, Poh Choon Ooi3 and Kean Chin Aw3

Author Affiliations

1 School of Materials and Mineral Resources Engineering, Universiti Sains Malaysia, Nibong Tebal, Penang 14300, Malaysia

2 NanoBiotechnology Research and Innovation, INFORMM, Universiti Sains Malaysia, USM, Penang, 11800, Malaysia

3 Mechanical Engineering, The University of Auckland, Auckland, 1142, New Zealand

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Nanoscale Research Letters 2012, 7:563  doi:10.1186/1556-276X-7-563

Published: 10 October 2012


This study describes a novel fabrication technique to grow gold nanoparticles (AuNPs) directly on seeded ZnO sacrificial template/polymethylsilsesquioxanes (PMSSQ)/Si using low-temperature hydrothermal reaction at 80°C for 4 h. The effect of non-annealing and various annealing temperatures, 200°C, 300°C, and 400°C, of the ZnO-seeded template on AuNP size and distribution was systematically studied. Another PMMSQ layer was spin-coated on AuNPs to study the memory properties of organic insulator-embedded AuNPs. Well-distributed and controllable AuNP sizes were successfully grown directly on the substrate, as observed using a field emission scanning electron microscope followed by an elemental analysis study. A phase analysis study confirmed that the ZnO sacrificial template was eliminated during the hydrothermal reaction. The AuNP formation mechanism using this hydrothermal reaction approach was proposed. In this study, the AuNPs were charge-trapped sites and showed excellent memory effects when embedded in PMSSQ. Optimum memory properties of PMMSQ-embedded AuNPs were obtained for AuNPs synthesized on a seeded ZnO template annealed at 300°C, with 54 electrons trapped per AuNP and excellent current–voltage response between an erased and programmed device.

Gold nanoparticles; Seeded growth; Hydrothermal; Organic memory