A Simple Method for Production of High Aspect Ratio ZnO Nanowires with Uniform Structure for NO2 Gas Sensors

2014 ◽  
Vol 6 (8) ◽  
pp. 1659-1667 ◽  
Author(s):  
Hoang Van Han ◽  
Nguyen Van Hieu ◽  
Tran Trung
Keyword(s):  
Aspect Ratio ◽  
Gas Sensors ◽  
High Aspect Ratio ◽  
Zno Nanowires ◽  
Uniform Structure ◽  
Simple Method ◽  
No2 Gas Sensors

pH-Dependent Toxicity of High Aspect Ratio ZnO Nanowires in Macrophages Due to Intracellular Dissolution

ACS Nano ◽  
2010 ◽  
Vol 4 (11) ◽  
pp. 6767-6779 ◽  
Author(s):  
Karin H. Müller ◽  
Jaideep Kulkarni ◽  
Michael Motskin ◽  
Angela Goode ◽  
Peter Winship ◽  
...  
Keyword(s):  
Aspect Ratio ◽  
High Aspect Ratio ◽  
Zno Nanowires ◽  
Ph Dependent

Morphology and electrical properties of high aspect ratio ZnO nanowires grown by hydrothermal method without repeated batch process

2012 ◽  
Vol 101 (8) ◽  
pp. 083905 ◽  
Author(s):  
Jin Woo Cho ◽  
Churl Seung Lee ◽  
Kyoung Il Lee ◽  
Seon Min Kim ◽  
Sung Hyun Kim ◽  
...  
Keyword(s):  
Electrical Properties ◽  
Aspect Ratio ◽  
Hydrothermal Method ◽  
High Aspect Ratio ◽  
Batch Process ◽  
Zno Nanowires ◽  
Repeated Batch ◽  
Repeated Batch Process

A simple method for fabrication of high-aspect-ratio all-silicon grooves

2013 ◽  
Vol 284 ◽  
pp. 372-378 ◽  
Author(s):  
Yuncan Ma ◽  
An Pan ◽  
Jinhai Si ◽  
Tao Chen ◽  
Feng Chen ◽  
...  
Keyword(s):  
Aspect Ratio ◽  
High Aspect Ratio ◽  
Simple Method

FABRICATION OF PERIODIC STANDING ROD ARRAYS BY THE SHADOW CONE METHOD

2006 ◽  
Vol 05 (06) ◽  
pp. 815-819 ◽  
Author(s):  
HIROFUMI TANAKA ◽  
PAUL S. WEISS ◽  
MARK W. HORN
Keyword(s):  
Aspect Ratio ◽  
High Aspect Ratio ◽  
Low Cost ◽  
Industrial Applications ◽  
Silicon Substrates ◽  
Simple Method ◽  
Periodic Arrays

A simple method for fabricating periodic arrays of high aspect ratio (1:20) standing nanorods on silicon substrates is described. It is based on shadow deposition onto periodically arranged arrays of mini-rods on a rotating sample stage. Consequently, such nanostructures can be prepared on relatively large areas and at low cost, making the method suitable for industrial applications.

Ultra-sensitive hydrazine chemical sensor based on high-aspect-ratio ZnO nanowires

Talanta ◽  
2009 ◽  
Vol 77 (4) ◽  
pp. 1376-1380 ◽  
Author(s):  
A UMAR ◽  
M RAHMAN ◽  
Y HAHN
Keyword(s):  
Aspect Ratio ◽  
High Aspect Ratio ◽  
Chemical Sensor ◽  
Zno Nanowires

Synthesis of high aspect ratio ZnO nanowires with an inexpensive handcrafted electrochemical setup

2016 ◽  
Vol 61 (7) ◽  
pp. 1105-1109
Author(s):  
Ali Taheri ◽  
Shahyar Saramad ◽  
Saeed Setayeshi
Keyword(s):  
Aspect Ratio ◽  
High Aspect Ratio ◽  
Zno Nanowires

scholarly journals A Numerical Model to Predict the Anisotropy of Polymer Composites Reinforced with High-Aspect-Ratio Short Aramid Fibers

2019 ◽  
Vol 2019 ◽  
pp. 1-12
Author(s):  
Jianhong Gao ◽  
Xiaoxiang Yang ◽  
Lihong Huang
Keyword(s):  
Aspect Ratio ◽  
High Aspect Ratio ◽  
Orientation Distribution ◽  
Composite Fiber ◽  
Fe Model ◽  
Fiber Types ◽  
Aramid Fibers ◽  
Simple Method ◽  
Fiber Orientation Distribution ◽  
Nonlinear Matrix

Some fiber types have a high aspect ratio and it is very difficult to predict their composites using traditional finite element (FE) modeling. In this study, an FE model was developed to predict the anisotropy of composites reinforced by short aramid fibers. Three fiber distribution types were studied as follows: perfectly aligned, normally distributed, and randomly distributed fibers. The elastic constants were obtained, and, for different alignment angles and parameters in the fiber orientation distribution function, their numerical results were compared to those of the Mori–Tanaka model. Good agreement was obtained; thus, the employed FE model is an excellent and simple method to predict the isotropy and anisotropy of a composite with high-aspect-ratio fibers. Therefore, the FE model was employed to predict the orientation distribution of a composite fiber with a nonlinear matrix. The predicted and experimental results agree well.

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