Ni@Pt core-shell nanoparticles as an improved electrocatalyst for ethanol electrooxidation in alkaline media
Publish place: Third Hydrogen and Fuel Cell Conference
Publish Year: 1394
نوع سند: مقاله کنفرانسی
زبان: English
View: 424
This Paper With 8 Page And PDF Format Ready To Download
- Certificate
- من نویسنده این مقاله هستم
استخراج به نرم افزارهای پژوهشی:
شناسه ملی سند علمی:
H2FC03_006
تاریخ نمایه سازی: 19 خرداد 1396
Abstract:
Core-shell nanostructures are emerging as more important materials than alloy nanostructures, and have much more interesting potential applications in various fields, including catalysis and electronics. In this work, we demonstrate the facile synthesis of core-shell nanoparticles consisting of Pt thin layer as the shell and Ninanoparticles as the cores. X-ray diffraction, scanning electron microscopy, transmission electron microscopy and energy dispersive X-ray spectroscopy are used to investigate the surface morphology and chemical structural. The general electrochemical behavior towards ethanol oxidation on core-shell nanoparticles has been investigated by cyclic voltammetry in 0.5 M NaOH solution. The Ni@Pt core-shell nanoparticles showmarkedly enhanced electrocatalytic activity and stability for ethanol oxidation compared with the Pt-alonenanoparticles catalyst. The attractive performances exhibited by these prepared Ni@Pt core-shell nanoparticles make them promising candidates as future high-performance catalysts for ethanol electrooxidation. The facile method described herein is suitable for large-scale, low-cost production, and significantly lowers the Pt loading,and thus, the cost of the catalysts
Keywords:
Authors
Serveh Ghaderi
Electroanalytical Chemistry Laboratory, Department of Chemistry, Faculty of Sciences,Azarbaijan Shahid Madani University, Tabriz
Biuck Habibi
Electroanalytical Chemistry Laboratory, Department of Chemistry, Faculty of Sciences,Azarbaijan Shahid Madani University, Tabriz
مراجع و منابع این Paper:
لیست زیر مراجع و منابع استفاده شده در این Paper را نمایش می دهد. این مراجع به صورت کاملا ماشینی و بر اساس هوش مصنوعی استخراج شده اند و لذا ممکن است دارای اشکالاتی باشند که به مرور زمان دقت استخراج این محتوا افزایش می یابد. مراجعی که مقالات مربوط به آنها در سیویلیکا نمایه شده و پیدا شده اند، به خود Paper لینک شده اند :