scholarly journals Analysis of Acoustic Emission Signal Sensitivity to Variations in Thin-film Material Properties During CMP Process

2014 ◽  
Vol 38 (8) ◽  
pp. 863-867
Author(s):  
Sun Joon Park ◽  
Hyun Seop Lee ◽  
Hae Do Jeong
2004 ◽  
Vol 20 (2) ◽  
pp. 107-112
Author(s):  
Max Ti-Kuang Hou ◽  
Rongshun Chen

AbstractNarrow micromachined bilayer cantilevers, which are broadly used to determine different thin film material properties, have rarely been used to characterize the Poisson's ratio. It is difficult to be determined from the tip deflection, and thus the Poisson's ratio, of the narrow bilayer cantilever. In this paper, the tip deflections of ultra-wide micromachined bilayer cantilevers carry the needed information for finding the Poisson's ratio of thin-film materials. The measurement process and its corresponding model, based on the plate theory, is introduced and tested. The Poisson's ratio of the thin film is determined by comparing the tip deflections of the bilayer cantilever before and after the deposition of the upper layer. Because the fabrication processes are widely used in surface micromachining, the method can be easily implemented.


Author(s):  
Mohammad Nur E Alam ◽  
Mikhail Vasiliev

We report on the development of several different thin-film material systems prepared by RF magnetron sputtering at Edith Cowan University nanofabrication labs. While focusing on the RF sputtering process optimizations for new or the previously underexplored material compositions and multilayer structures, we disclose several unforeseen material properties and behaviours. We communicate research results related to the design, prototyping, and practical fabrication of high-performance magneto-optic (MO) materials, oxide based sensor components, and transparent heat regulation coatings for advanced construction and solar windows.


2022 ◽  
Vol 165 ◽  
pp. 108301
Author(s):  
Chen Liu ◽  
Oliver Nagler ◽  
Florian Tremmel ◽  
Marianne Unterreitmeier ◽  
Jessica J. Frick ◽  
...  

2020 ◽  
pp. 61-64
Author(s):  
Yu.G. Kabaldin ◽  
A.A. Khlybov ◽  
M.S. Anosov ◽  
D.A. Shatagin

The study of metals in impact bending and indentation is considered. A bench is developed for assessing the character of failure on the example of 45 steel at low temperatures using the classification of acoustic emission signal pulses and a trained artificial neural network. The results of fractographic studies of samples on impact bending correlate well with the results of pulse recognition in the acoustic emission signal. Keywords acoustic emission, classification, artificial neural network, low temperature, character of failure, hardness. [email protected]


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