A reference spike train-based neurocomputing method for enhanced tactile discrimination of surface roughness

2021 ◽  
Author(s):  
Longhui Qin ◽  
Yilei Zhang
Keyword(s):  
Surface Roughness ◽  
Spike Train ◽  
Tactile Discrimination

Tactile Surface Roughness Categorization With Multineuron Spike Train Distance

2020 ◽  
pp. 1-11
Author(s):  
Zhengkun Yi ◽  
Tiantian Xu ◽  
Shifeng Guo ◽  
Wanfeng Shang ◽  
Xinyu Wu
Keyword(s):  
Surface Roughness ◽  
Spike Train

Roughness measurements of nonlinear optical polymer films by scanning tunneling microscopy

1989 ◽  
Vol 47 ◽  
pp. 22-23
Author(s):  
I. H. Musselman ◽  
R.-T. Chen ◽  
P. E. Russell
Keyword(s):  
Surface Roughness ◽  
Scanning Tunneling Microscopy ◽  
Nonlinear Optical ◽  
Polymer Surface ◽  
Light Extinction ◽  
Scanning Tunneling ◽  
Silicon Substrates ◽  
Tunneling Microscopy ◽  
Optical Polymer ◽  
Total Light

Scanning tunneling microscopy (STM) has been used to characterize the surface roughness of nonlinear optical (NLO) polymers. A review of STM of polymer surfaces is included in this volume. The NLO polymers are instrumental in the development of electrooptical waveguide devices, the most fundamental of which is the modulator. The most common modulator design is the Mach Zehnder interferometer, in which the input light is split into two legs and then recombined into a common output within the two dimensional waveguide. A π phase retardation, resulting in total light extinction at the output of the interferometer, can be achieved by changing the refractive index of one leg with respect to the other using the electrooptic effect. For best device performance, it is essential that the NLO polymer exhibit minimal surface roughness in order to reduce light scattering. Scanning tunneling microscopy, with its high lateral and vertical resolution, is capable of quantifying the NLO polymer surface roughness induced by processing. Results are presented below in which STM was used to measure the surface roughness of films produced by spin-coating NLO-active polymers onto silicon substrates.

Surface roughness measurements of vanadium-contaminated fluidized cracking catalysts by atomic force microscopy

1996 ◽  
Vol 54 ◽  
pp. 866-867
Author(s):  
H. Kinney ◽  
M.L. Occelli ◽  
S.A.C. Gould
Keyword(s):  
Surface Roughness ◽  
Zeolite Y ◽  
Atomic Level ◽  
Microporous Structure ◽  
Contact Mode ◽  
Force Microscopy ◽  
Atomic Force ◽  
Before And After ◽  
Roughness Measurements ◽  
Cracking Catalysts

For this study we have used a contact mode atomic force microscope (AFM) to study to topography of fluidized cracking catalysts (FCC), before and after contamination with 5% vanadium. We selected the AFM because of its ability to well characterize the surface roughness of materials down to the atomic level. It is believed that the cracking in the FCCs occurs mainly on the catalysts top 10-15 μm suggesting that the surface corrugation could play a key role in the FCCs microactivity properties. To test this hypothesis, we chose vanadium as a contaminate because this metal is capable of irreversibly destroying the FCC crystallinity as well as it microporous structure. In addition, we wanted to examine the extent to which steaming affects the vanadium contaminated FCC. Using the AFM, we measured the surface roughness of FCCs, before and after contamination and after steaming.We obtained our FCC (GRZ-1) from Davison. The FCC is generated so that it contains and estimated 35% rare earth exchaged zeolite Y, 50% kaolin and 15% binder.

Effects of Process Parameters on Surface Roughness and MRR in the hard turning of EN 36 steel

2018 ◽  
pp. 102-110
Author(s):  
Amritpal Singh ◽  
Rakesh Kumar
Keyword(s):  
Surface Roughness ◽  
Material Removal Rate ◽  
Material Removal ◽  
Hard Turning ◽  
Control Parameter ◽  
Removal Rate ◽  
Cutting Speed ◽  
Depth Of Cut ◽  
Cutting Condition ◽  
Dry Cutting

In the present study, Experimental investigation of the effects of various cutting parameters on the response parameters in the hard turning of EN36 steel under the dry cutting condition is done. The input control parameters selected for the present work was the cutting speed, feed and depth of cut. The objective of the present work is to minimize the surface roughness to obtain better surface finish and maximization of material removal rate for better productivity. The design of experiments was done with the help of Taguchi L9 orthogonal array. Analysis of variance (ANOVA) was used to find out the significance of the input parameters on the response parameters. Percentage contribution for each control parameter was calculated using ANOVA with 95 % confidence value. From results, it was observed that feed is the most significant factor for surface roughness and the depth of cut is the most significant control parameter for Material removal rate.

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