• Journal of the Optical Society of Korea
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• v.16 no.3
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• pp.221-227
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• 2012

We propose optical proximity corrections (OPCs) for digital micromirror device (DMD)-based maskless lithography. A pattern writing scheme is analyzed and a theoretical model for obtaining the dose distribution profile and resulting structure is derived. By using simulation based on this model we were able to reduce the edge placement error (EPE) between the design width and the critical dimension (CD) of a fabricated photoresist, which enables improvement of the CD. Moreover, by experiments carried out with the parameter derived from the writing scheme, we minimized the corner-rounding effect by controlling light transmission to the corners of a feature by modulating a DMD.

• Journal of the Korean institute of surface engineering
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• v.55 no.6
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• pp.328-341
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• 2022

Area selective atomic layer deposition (AS-ALD) is a bottom-up nanopattern fabrication method that can grow the ALD films only on the desired substrate areas without using photolithography and etching processes. Particularly, AS-ALD has attracted great attention in the semiconductor manufacturing process due to its advantage in reducing edge placement error by fabricating self-aligned patterns. In this paper, the basic principles and characteristics of AS-ALD are described. In addition, various approaches for achieving AS-ALD with excellent selectivity were comprehensively reviewed. Finally, the technology development to overcome the selectivity limit of AS-ALD was introduced along with future prospects.

• Proceedings of the Korean Institute of Electrical and Electronic Material Engineers Conference
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• 2003.05b
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• pp.62-65
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• 2003

When a mobile robot moves around autonomously without man-made corrupted bye landmarks, it is essential to recognize the placement of surrounding objects especially for self localization, obstacle avoidance, and target classification and localization. To recognize the environment we use many Kinds of sensors, such as ultrasonic sensors, laser range finder, CCD camera, and so on. Among the sensors, ultra sonic sensors(sonar)are unexpensive and easy to use. In this paper, we analyze the sonar data and propose a method to recognize features of indoor environment. It is supposed that the environments are consisted of features of planes, edges, and corners, For the analysis, sonar data of plane, edge, and corner are accumulated for several given ranges. The data are filtered to eliminate some noise using the Kalman filter algorithm. Then, the data for each feature are compared each other to extract the character is ties of each feature. We demonstrate the applicability of the proposed method using the sonar data obtained form a sonar transducer rotating and scanning the range information around a indoor environment.