ANALYSIS AND MONITORING OF MOLD CAVITY FILLING IN NANOIMPRINTING PROCESS

• Main Authors: Ching-Chung Nien, 粘金重
• Other Authors: Hong Hocheng
• Format: Others
• Language: en_US
• Published: 2007
• Online Access: http://ndltd.ncl.edu.tw/handle/48850836720793252163

博士 === 國立清華大學 === 動力機械工程學系 === 95 === Nanoimprint lithography (NIL) has been recognized as one of the very promising nonphotolithographic methods for nanoscale device manufacturing. While NIL has been studied and investigated to some detail, and significant achievements of the application have been demonstrated in recent years, NIL has been capable of patterning only fairly small samples, which severely limits the industrial applications of the technique. As a consequence, how to improve throughput to meet the requirements for large-scale industrial use is the most challenging issue for the research community of NIL at the present time. In addition, the mold cavity filling process is vital in pattern transfer and governs the pattern transfer quality as well as the throughput of the NIL process. Hence, the mold cavity filling control and in-situ process monitoring in a timely fashion to determine the status of patterning are needed. To understand pattern formation and exploring the quantitative information on mold cavity filling variations during the nanoimprinting process, the imprinting numerical analysis for PMMA polymer and mr-I 7030 polymer has been successfully performed using Mooney-Rivlin model and viscous flow model respectively. For the case of numerical analysis of nanoimprinting on PMMA with Mooney-Rivlin model, a finite element model for the single mold cavity has been constructed to simulate the nanoimprint process. The material behavior of the imprint mold is assumed to be linear elastic, and the polymer preheated above its glass transition temperature is considered to behave as a nonlinear elastic body described by the Mooney-Rivlin model. Using the developed numerical model, the mold cavity filling variations can be determined at any nanoimprint stage and for a mold cavity with a variety of aspect ratios. Moreover, to investigate the effects of pattern density and contact friction existing between the imprint mold and polymer on mold cavity filling of the nanoimprinting process, the model for an imprint mold with mixed patterns in an active area has been constructed to explore mold cavity filling in the nanoimprinting process, and a sensitivity analysis of the contact friction coefficient for the mold cavity filling is performed. Both the cavity feature and pattern density have significant effects on mold cavity filling of the nanoimprinting process, while the contact friction coefficient has a mild effect. In the numerical investigation of nanoimprinting on mr-I 7030 polymer with viscous flow model, the software package ANSYS/FLOTRAN is adopted to simulate the mold cavity filling process and the significant influence of pattern density on mold cavity filling has also been observed. The results arising from the model indicate that the imprint mold with varied pattern density has nonuniform displacement during the imprinting process and further strengthen the rationale of implementing an in-situ mold cavity filling monitoring system for nanoimprinting. The proposed mold cavity filling monitoring method for nanoimprinting operations in this study is based on capacitance measurement. In carrying out the proposed monitoring method, a broad range of aspects including numerical analysis of capacitive detection in nanoimprinting process, tuning the imprint process, designing a reliable capacitive sensor, determining the right materials and micromachining process for sensing electrodes, and data analysis have been covered. A finite element model valid for the numerical description of a parallel-plate capacitor has been developed, and simulations were carried out to predict the influence of mold cavity filling on capacitance values. In addition, to measure the continuous variations in capacitance, a series of imprinting experiments have been performed isothermally, and the capacitance values have also been measured at various imprinting stages. The major final stage of mold cavity filling near the end can be monitored and the experimental results have demonstrated that the capacitance measurements indeed provide information in-situ that can feasibly tell the cavity filling status during nanoimprinting. Throughout the study, the proposed capacitance measurement is found a promising approach to monitor mold cavity filling in nanoimprinting process, and the practical application of the conducted research is expected with certain improvement of the robustness of the monitoring technique in harsh environment at high imprinting temperature and applied pressure. The use of neural network to model the functional relationship between the capacitance value and the rise of mold cavity filling is recommended as another potential future research to achieve the ultimate goal of real-time mold cavity filling control for imprinting process.