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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/45503完整後設資料紀錄
| DC 欄位 | 值 | 語言 |
|---|---|---|
| dc.contributor.advisor | 蔡坤諭 | |
| dc.contributor.author | Hoi-Tou Ng | en |
| dc.contributor.author | 伍海濤 | zh_TW |
| dc.date.accessioned | 2021-06-15T04:23:51Z | - |
| dc.date.available | 2015-08-20 | |
| dc.date.copyright | 2010-08-20 | |
| dc.date.issued | 2009 | |
| dc.date.submitted | 2009-08-18 | |
| dc.identifier.citation | [1] I. Adesida et al, “High resolution electron-beam lithography on thin films,” JVST 16 1743-1748, 1979
[2] L. D. Jackel, et al, Appl. Phys. Lett. 45, 698 (1984) [3] S. Valkealahti and R. M. Nieminen, “Monte Carlo calculations of keV electron and positron slowing down in solids. II,” Appl. Phys. A 35, 51-59 (1984) [4] Z. Czyzewski, D. O. MacCalium, A. Romig, and D. C. Joy, “Calculation of Mott scattering cross section, ” J. Appl. Phys. 68(7), 3066-3072 (1990) [5] Wolfgang S. M. Werner, “Slowing down of medium-energy electrons in solids,” Physical Review B, 55 14 925-14 934 (1996) [6] M. Gentili, L. Grella, A. Lucchesini, L. Luciani, L. Mastro, “Energy density function determination in very-high-resolution electron-beam lithography,” J. Vac. Sci. Technol. B 8, 1867-1871 (1990) [7] Mark A. Hartney, “Modeling of Resist Performance”, Advanced Materials for Optics and Electronics vol. 4, 165-175 (1994) [8] J.Baro, j.Sempau, J.M. Fernandez-Varea, F.Salvat, “PENELOPE: An algorithm for Monte Carlo simulation of the penetration and energy loss of electrons and positrons in matter,” Nuclear Instruments and Methods in Physics Research B 100 31-46 (1995) [9] P. K. MacKeown, Stochastic Simulation in Physics, Springer-Verlag (1997). [10] M. A. McCord and M. J. Rooks, “Electron beam lithography,' Chap. 2 in Handbook of Microlithography, Micromachining, and Microfabrication. Volume 1: Microlithography, P. Rai-Choudhury Ed., pp 139-250, SPIE Press Monograph Vol. PM39 (1997) [11] S.Y. Lee, B. D. Cook, “PYRAMID—A Hierarchical, Rule-Based Approach Toward Proximity Effect Correction-Part I: Exposure Estimation,” IEEE Tran. Semi. Manuf., 11(1), 108-116 (1998) [12] G.p.Patsis et al, “Surface and line-edge roughness in solution and plasma developed negative tone resists: Experiment and simulation” , JVST B vol. 18 3292-3296,2000 [13] Nakasugi, A. Ando, R. Inanami, N. Sasaki, K.Sugihara, M. Miyoshi and H. Fujiok, “Edge Roughness Study of Chemically Amplified Resist in Low-Energy Electron-Beam Lithography Using Computer Simulation,” Jpn. J. Appl. Phys. Vol. 41 p. 4157–4162, (2002). [14] Shiying Xiong, Jeffrey Bokor, “Study of Gate Line Edge Roughness Effect in 50 nm Bulk MOSFET Devices,” Proceedings of SPIE, 2002 [15] P. Kruit, S. Steenbrink, R. Jager, M. Wieland, “Optimum dose for shot noise limited CD uniformity in electron-beam lithography,” JVST B. 22(6).p. 2948–2955, (2004). [16] M. Yoshizawa, et al 'Impact of Latent Image Quality on Line Edge Roughness in Electron Beam Lithography', J. J. Appl. Phys. 43, 3739 (2004) [17] H.Y. Song, Y.L. Zhang, Q.Wei and X.D. Kong, “Optimization of electron scattering model in electron beam lithography,” Microfabrication Technology 3 14-19 (2005) [18] Jacques Beauvais et al, “Resist Sensitivity and Thickness-Based Beam Count Optimization for Parallel Low Energy E-Beam Exposure Systems,” Proceedings of SPIE Vol. 5751, 2005 [19] P. Kruit et al, “Shot Noise in Electron-Beam Lithography and Line-Width Measurements” , Scanning vol. 28 20-26,2006 [20] Y. Ma, Y.C. Cheng, F. Cerrina, T.Barwicz, H.I. Smith, “Local line edge roughness in micro-photonic devices: An electron beam lithography study,” JVST B 26(1) p 235-241 2007 [21] D. Drouin, A. R. Couture, D. Joly, X. Tastet, V. Aimez, and R. Gauvin, “CASINO V2.42—A fast and easy-to-use modeling tool for scanning electron microscopy and microanalysis users,” Scanning 29, 92-101 (2007). Software available at http://www.gel.usherbrooke.ca/casino. [22] International Technology Roadmap of Semiconductors, Lithography. Available online at http://www.itrs.net/ (2007) [23] SEMI, ‘Test method for evaluation of line-edge roughness and line width roughness”, SEMI P47-0307,2007 [24] Burn Lin, ”Mirco-lithography”, lecture chapter 2,2008 [25] C.H. Liu, H.T. Ng, P. Ng, K.Y. Tsai, S.J. Lin, and a J.H. Chen, 'A novel curve-fitting procedure for determining proximity effect parameters in electron beam lithography', to appear in SPIE Litho. Asia (2008) [26] S.M. Chang et al, “Patterning fidelity on low-energy multiple-electron-beam direct write lithography,” Proc. SPIE 6921, 69211R-69211R-9 (2008). [27] Chi-Hsiung Fan, “Monte Carlo simulation of electron trajectory and design of an electron beam position monitor system for multiple electron beam direct-write lithography”, Master Thesis, National Taiwan University (2008) [28] Hsing-Hong Chen, “Analysis and optimization design of MEMS-based electron optical systems for electron beam direct-write lithography”, Master Thesis, National Taiwan University (2009) [29] The Mathworks, Inc., MATLAB program version R2008a. Information available at http://www.mathworks.com. | |
| dc.identifier.uri | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/45503 | - |
| dc.description.abstract | 低能電子微影術擁有高解析度，低基底損害，增加光阻敏感度的優勢，被認為實踐22奈米製程的技術之一。為了在高斯電子束柵狀掃描系統下增加製程的產量，電子的曝光量，曝光之距離和曝光點大小等參數必須謹慎選取，以達到產量的最佳化。為此我們以一個蒙地卡羅的模擬方法去模擬出光阻的曝光形狀，根據邊緣粗糙度對ITRS上的標準值的比較而把以上所述的參數的邊界找出。同時把曝光形狀作為電子光學系統的判定條件，對電子光學系統的參數作出進一步的最佳化。 | zh_TW |
| dc.description.abstract | Low-energy electron beam lithography (LEEBL) is a promising patterning solution for the 22-nm half-pitch node and beyond due to its high resolution, low substrate damage, and increased resist sensitivities. In order to achieve throughout required for high-volume manufacturing, writing parameters such as probe size, pixel size, electron dosage, proximity correction scheme, and number of beams need to be carefully selected in a Gaussian-beam–raster-scan system. In high-throughput LEEBL, line edge roughness (LER) caused by shot noise becomes a critical issue for both device patterning and device performance variability. To characterize these effects, stochastic MOSFET gate patterning with LEEBL is constructed by overlapping energy distributions from an in-house electron scattering Monte Carlo simulation program with various writing parameters. Parameter optimization can help provide initial guidelines and specifications for design and operation of multiple electron beam direct-write systems. | en |
| dc.description.provenance | Made available in DSpace on 2021-06-15T04:23:51Z (GMT). No. of bitstreams: 1 ntu-98-R96921013-1.pdf: 1687044 bytes, checksum: 6d7ff17b65e52a21e8788f8f369e3a1b (MD5) Previous issue date: 2009 | en |
| dc.description.tableofcontents | Table of Contents
Abstract I 摘要 II Statement of Contributions III 誌謝 IV Table of Contents V List of Figures VII List of Tables IX Chapter 1 Introduction 1 1.1 Microlithography 1 1.2 Electron Beam Lithography 2 1.3 Multiple Electron Beam Lithography 4 Chapter 2 Monte Carlo simulation 6 2.1 Monte Carlo method 6 2.2 Scattering phenomena in solid 6 2.2.1 Polar angle 7 2.2.2 Azimuth angle 7 2.2.3 Distance between two collisions 8 2.2.4 Energy loss 8 2.2.5 Collision determination 10 2.3 Point spread function comparison with CASINO 11 2.4 The simulation time analysis of the original simulation structure and Parallel simulation structure 13 2.4.1 Algorism improve 13 2.4.2 Parallel Algorism 17 2.4.3 Acceleration Results 18 Chapter 3 Exposure and latent image Electron beam exposure process 20 3.1 Simulation model 20 3.1.1 Electron beam spot distribution 22 3.1.2 Point spread distribution 22 3.1.3 Threshold level and latent image 23 3.1.4 Diffusion model 24 3.2 Patterns parameters definition 26 3.2.1 Parameters definition 27 3.2.1.1 Spot size 27 3.2.1.2 Grid size 27 3.2.1.3 Dosage 28 3.2.2 Patterns’ latent image simulation results 28 3.3 Direct Monte Carlo method 29 3.3.1 Different of DMC and pervious method in pattern simulation 30 Chapter 4 Parameter selection methodology 33 4.1 Parameters boundary finding methodology 33 4.2 Process of the methodology 33 4.3 Simulation with DMC and hybrid method including PAG diffusion 35 Chapter 5 Lens parameters optimization including the whole e-beam system 38 5.1 Preliminary EOS for MPML2 38 5.2 Whole system simulation flow 40 5.2.1 New random variable generator 41 5.2.2 Source + Enizel lens as an operator 45 5.3 Parameters definition 47 5.4 Optimization 49 Chapter 6 Future Work 53 Reference 54 BIOGRAPHIES 58 | |
| dc.language.iso | en | |
| dc.subject | 邊緣粗糙度 | zh_TW |
| dc.subject | 低能電子微影術 | zh_TW |
| dc.subject | 蒙地卡羅方法 | zh_TW |
| dc.subject | 最佳化 | zh_TW |
| dc.subject | Line Edge Roughness | en |
| dc.subject | low energy electron beam lithography | en |
| dc.subject | optimization | en |
| dc.subject | Monte Carlo method | en |
| dc.title | 基於直接蒙地卡羅方法之電子束微影圖像模擬及其於電子光學系統優化設計之應用 | zh_TW |
| dc.title | PATTERNING SIMULATION BASED ON DIRECT MONTE CARLO METHOD AND ITS APPLICATION TO ELECTRON OPTICAL SYSTEM OPTIMIZATION FOR ELECTRON BEAM LITHOGRAPHY | en |
| dc.type | Thesis | |
| dc.date.schoolyear | 98-2 | |
| dc.description.degree | 碩士 | |
| dc.contributor.oralexamcommittee | 顏家鈺,管傑雄,李佳翰,郭宇軒,陳政宏 | |
| dc.subject.keyword | 低能電子微影術,邊緣粗糙度,蒙地卡羅方法,最佳化, | zh_TW |
| dc.subject.keyword | low energy electron beam lithography,Line Edge Roughness,Monte Carlo method,optimization, | en |
| dc.relation.page | 58 | |
| dc.rights.note | 有償授權 | |
| dc.date.accepted | 2009-08-18 | |
| dc.contributor.author-college | 電機資訊學院 | zh_TW |
| dc.contributor.author-dept | 電機工程學研究所 | zh_TW |
| 顯示於系所單位： | 電機工程學系 | |
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