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Su, Mu-Chun; Chang, Hsiao-Te

doi:10.1023/a:1009681803460

Cited by 4 publications

(2 citation statements)

References 10 publications

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“…where E is the Young modulus of SU-8 (E = 2.0 GPa [14]), L is the micropillar length, S is the space between the neighboring micropillars and γ SU-8 is the surface tension of SU-8. From equation ( 1), H max of the SU-8 pattern with 20 μm length and 40 μm space in figure 1 is about 740 μm (AR = 37).…”

Section: Fabrication Of Har Su-8 Microstructuresmentioning

confidence: 99%

“…Among wet cleaning techniques, the piranha solution is the most widely used because it will eliminate the adsorbed organics effectively; however, it grows a thin chemical SiO 2 layer (Si-OH). This is a recommended pretreatment method from Microchem R SU-8 processing guidelines [14], and also applied in our experiments (figure 1). In addition to the exposure of the substrate to the piranha solution, we further performed HF treatment, which etches the generated SiO 2 layer, and therefore makes the Si surface hydrophobic terminated with Si-H.…”

Section: Fabrication Of Har Su-8 Microstructuresmentioning

confidence: 99%

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The effects of adhesion energy on the fabrication of high-aspect-ratio SU-8 microstructures

Hwang

Park

Kim

et al. 2010

J. Micromech. Microeng.

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The effects of a Si wafer cleaning method on the adhesion behavior of SU-8 microstructures were investigated. In particular, the role of adhesion energy was clearly demonstrated for fabricating high-aspect-ratio (HAR) SU-8 micropillar arrays with reduced contact area. The surface energy values of the Si wafers prepared through different cleaning techniques were calculated using contact angle measurements, revealing that the difference of adhesion energy was mainly determined by the presence of a SiO 2 layer. It was found that the adhesion energy of the SU-8 microstructure to the Si wafer was increased by approximately 72% through HF treatment that is required to remove the oxide layer. Furthermore, the dispersion component of the surface energy played a major role in the adhesion of SU-8 to various solid substrates. These results consistently indicate that thermodynamic adhesion energy needs to be high for the strong macroscopic adhesion strength of the SU-8 photoresist. Also, the calculated adhesion energy values were in good agreement with the physical measurements of macroscopic shear stress, suggesting that a simple thermodynamic approach used here can be used to examine the adhesion characteristics of the SU-8 photoresist. Using the optimized cleaning method, HAR SU micropillar arrays of 20 μm width and 300 μm height (AR = 15) were fabricated.

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Section: Fabrication Of Har Su-8 Microstructuresmentioning

confidence: 99%

Section: Fabrication Of Har Su-8 Microstructuresmentioning

confidence: 99%

The effects of adhesion energy on the fabrication of high-aspect-ratio SU-8 microstructures

Hwang

Park

Kim

et al. 2010

J. Micromech. Microeng.

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Modeling Connectionist Neuro-Fuzzy network and Applications

Shalinie¹

2005

Neural Comput & Applic

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The main objective of this paper is to propose a Neuro-Fuzzy network, which can model a system from input-output data by automatically dividing the inputoutput space and extracting fuzzy if-then rules from numerical data. The structure of the network is simple with input, rule and output layers only. The connections between input and rule layer is used to derive the membership functions of the fuzzified part. Kohonen's self-organizing learning algorithm is applied to partition the pattern space. Using this algorithm, similar rules are mapped close by and extraction of if-then rules is made easy. It can also adapt to a number of rules automatically. The proposed network is verified for three benchmark applications. Experimental results show that the adaptive method discussed in this paper not only trains in a few hundred iterations but also provides better performance measures when compared to conventional methods.

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