Microlithography Simulation and the Transmission and Analysis of Bio-signal

• Main Authors: Pei-Chun Lin, 林沛諄
• Other Authors: Chung-Ping Chen
• Format: Others
• Language: en_US
• Published: 2012
• Online Access: http://ndltd.ncl.edu.tw/handle/73803244303315202658

碩士 === 國立臺灣大學 === 電子工程學研究所 === 100 === This thesis is divided into two parts; the first part is microlithography simulation. This part is focused on the simulation of the optical system throughout the whole microlithography process, including the photochemical reaction, the establishment of photoresist and the effect of diffusion. As the VLSI manufacture technology improves, the feature size of micro-electronic devices become much smaller than the wavelength of the exposure light source, and the limits of micro-lithography image system is continuously challenged. The exposed image results clearly deviate from the original design pattern due to the optical diffraction effect. Furthermore, a deeper discussion about the modeling of photoresist is proposed. The Dill model, Kim model, original Mack model and enhanced kinetic model are introduced and compared. We discuss the effect that the standing wave of light brings on to the design pattern, and use numerical methods to simulate acid diffusion effect. The chemical amplification resist used in lithography process enhances the lithography reaction with the low-energy lights. Moreover, the reaction of the lights can be regarded as the acid diffusion phenomena. We can look thoroughly into the acid diffusion equation by using matrix algebra and specific algorithms. However the non-numerical solution can be obtained by fast Fourier transform method FFT. At last, we expect to develop a fast and reliable auxiliary system for lithography simulation. The other topic is about Physiological signals transmission and analysis. The importance of Telecare is emphasized as the technology improves and the amount of medical resources becomes abundant. Therefore, the establishment of a platform to store personal health records for wireless biological measurement instruments and smart phone applications is necessary. Patients can upload the measured results by the biological instruments at home via Bluetooth or wireless network to a personal health care platform. Personal health records are available to them and their doctor through an internet access with intelligent mobile phones without restrictions of time or location. Our system can upload the measurements of blood pressure, as well as the results of ECG analysis. We utilize Support Vector Machines and MIT-BIH Arrhythmia database to complete the network back-end analysis systems. Patients can receive real-time ECG on the phone; in addition, we implemented a real-time algorithm in the smart phone which can diagnose heart diseases according to their health care records. In this case, both transfer and monitoring can be simply done.