Measurement of a dielectric film thickness in the course of spraying

1966 ◽  
Vol 9 (5) ◽  
pp. 655-657
Author(s):  
Yu. G. Yagola ◽  
V. E. Minaichev
Keyword(s):  
Film Thickness ◽  
Dielectric Film

Accurate monitoring of dielectric film thickness

Vacuum ◽  
1995 ◽  
Vol 46 (2) ◽  
pp. 199-201 ◽  
Author(s):  
OS Heavens ◽  
GJ Kopek ◽  
Yuan Yi-Fang
Keyword(s):  
Film Thickness ◽  
Dielectric Film

A Computational Model to Study Film Formation and Debris Flushing Phenomena in Spray-Electric Discharge Machining

2016 ◽  
Vol 4 (3) ◽  
Author(s):  
Arvind Pattabhiraman ◽  
Deepak Marla ◽  
Shiv G. Kapoor
Keyword(s):  
Film Thickness ◽  
Computational Model ◽  
Electric Discharge ◽  
Dielectric Film ◽  
Film Formation ◽  
Electric Discharge Machining ◽  
Spray Formation ◽  
Spray System ◽  
Debris Particles ◽  
Interelectrode Gap

A computational model to investigate the flushing of electric discharge machining (EDM) debris from the interelectrode gap during the spray-EDM process is developed. Spray-EDM differs from conventional EDM in that an atomized dielectric spray is used to generate a thin film that penetrates the interelectrode gap. The debris flushing in spray-EDM is investigated by developing models for three processes, viz., dielectric spray formation, film formation, and debris flushing. The range of spray system parameters including gas pressure and impingement angle that ensure formation of dielectric film on the surface is identified followed by the determination of dielectric film thickness and velocity. The debris flushing in conventional EDM with stationary dielectric and spray-EDM processes is then compared. It is observed that the dielectric film thickness and velocity play a significant role in removing the debris particles from the machining region. The model is used to determine the spray conditions that result in enhanced debris flushing with spray-EDM.

scholarly journals Influence of Carbon Quantum Dots on the Electrical Performance of Triboelectric Generators

Proceedings ◽  
2018 ◽  
Vol 2 (13) ◽  
pp. 1025 ◽  
Author(s):  
Vasiliki Prifti ◽  
Antigoni Siaraka ◽  
Aikaterini Giannouli ◽  
Apostolos Segkos ◽  
Achilleas Bardakas ◽  
...  
Keyword(s):  
Surface Roughness ◽  
Quantum Dots ◽  
Film Thickness ◽  
Potential Application ◽  
Dielectric Film ◽  
Sliding Mode ◽  
Flexible Substrate ◽  
Carbon Quantum Dots ◽  
Electrical Performance ◽  
Device Performance

In this work we investigate the triboelectric properties of Carbon Quantum Dots (CQDs) films for potential application in triboelectric generators. CQDs were deposited on silicon wafers, using spin on techniques. Device performance was estimated in sliding mode experiments, where the CQDs-surface was sliding on top of a flexible substrate. The triboelectric signal as well as the charging of capacitors, after signal rectification, was monitored as a function of time. Our results indicate that surface roughness plays a very important role in the triboelectric signal and could compensate opposite trends due to other parameters, such as the dielectric film thickness.

Novel microspot dielectric film thickness measurement system

1992 ◽  
Author(s):  
David Willenborg ◽  
Susan M. Kelso ◽  
Jon L. Opsal ◽  
Jeffrey T. Fanton ◽  
Allan Rosencwaig
Keyword(s):  
Film Thickness ◽  
Measurement System ◽  
Dielectric Film ◽  
Thickness Measurement ◽  
Film Thickness Measurement ◽  
Thickness Measurement System

scholarly journals Dielectric Film Thickness Measurement Via a Convolutional Neural Network for Integrated Circuit Delayering End Point Detection

2021 ◽  
Author(s):  
Jonathan Scholl ◽  
Nick Darby ◽  
Josh Baur ◽  
Yash Patel ◽  
Isabel Boona ◽  
...  
Keyword(s):  
Computer Vision ◽  
Film Thickness ◽  
Integrated Circuit ◽  
Dielectric Film ◽  
Ideal Point ◽  
Thickness Measurement ◽  
Dielectric Thickness ◽  
End Point ◽  
End Point Detection ◽  
Point Detection

Abstract The integrated circuit (IC) delayering workflow is heavily reliant on operator experience to determine the processing end point, which is the ideal point on an IC where processing should be terminated, to optimize region of interest imaging. The current method of end point detection during IC delayering utilizes qualitative correlation between dielectric film color and dielectric thickness observed via optical microscopy to guide decision making. The goal of this work is to quantify this relationship using computer vision. In the field of computer vision, convolutional neural networks (CNNs) have been successfully applied to capture spatial relationships within images. Given this success, a CNN was trained for thickness estimates of dielectric films using optical images captured during processing for eventual automated end point detection. The trained model explained 39% of the variance in dielectric film thickness with a mean absolute error of approximately 47 nm.

Influence of Dielectric Film Thickness on the Magnetic Properties of the Magneto-Optical Multilayer Films

1997 ◽  
Vol 475 ◽  
Author(s):  
X.S. Miao ◽  
Y.C. Chan ◽  
Y.M. Huang ◽  
W.Z. Liu ◽  
Z.Y. Lee
Keyword(s):  
Magnetic Properties ◽  
Film Thickness ◽  
Magnetic Anisotropy ◽  
Dielectric Film ◽  
Magnetic Interaction ◽  
Multilayer Films

ABSTRACTThe magnetic interaction of magneto-optical multilayer films have been analyzed using the stress mechanism of coercivity and the single ion model of magnetic anisotropy. The relation between the magnetic properties of the multilayer films and the dielectric film thickness has been explained.

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