Hot Embossing of Microoptical Components Prototyped by Deep Proton Writing

被引:30
|
作者
Van Erps, Juergen [1 ]
Wissmann, Markus [2 ]
Guttmann, Markus [2 ]
Hartmann, Michael [2 ]
Mohr, Juergen [2 ]
Debaes, Christof [1 ]
Thienpont, Hugo [1 ]
机构
[1] Vrije Univ Brussel, Dept Appl Phys & Photon, B-1050 Brussels, Belgium
[2] IMT, D-76344 Eggenstein Leopoldshafen, Germany
关键词
Coupling components; deep proton writing (DPW); hot embossing; mass fabrication; plastics; replication;
D O I
10.1109/LPT.2008.928836
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In this letter, we present the replication of out-of-plane coupling microcomponents using hot embossing, through the fabrication of a metal mould by electroforming a polymer template patterned by means of deep proton writing (DPW). We compare the surface roughness and the optical performance of the hot embossed replicas with the DPW prototypes and can conclude that the replicated components exhibit only a small increase in surface roughness and a very small decrease in coupling performance. This paves the way towards low-cost mass replication of DPW-fabricated prototypes in a variety of high-tech plastics.
引用
收藏
页码:1539 / 1541
页数:3
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  • [21] Microfabrication of a nickel mold insert by a modified deep X-ray lithography process and its application to hot embossing
    Lee, Bong-Kee
    Kim, Jong Hyun
    Kim, Dong Sung
    Chang, Suk Sang
    Kwon, Tai Hun
    [J]. MICROELECTRONIC ENGINEERING, 2010, 87 (12) : 2449 - 2455
  • [22] Characterization of refractive index distribution in spherical microlenses fabricated by deep proton writing
    Kniazewski, P.
    Gomez, V.
    Pakula, A.
    Ottevaere, H.
    Kujawinska, M.
    Thienpont, H.
    [J]. IEEE PHOTONICS TECHNOLOGY LETTERS, 2008, 20 (1-4) : 208 - 210
  • [23] Deep proton writing with 12 MeV protons for rapid prototyping of microstructures in polymethylmethacrylate
    Ebraert, Evert
    Gokce, Berkcan
    Van Vlierberghe, Sandra
    Vervaeke, Michael
    Meyer, Pascal
    Guttmann, Markus
    Dubruel, Peter
    Thienpont, Hugo
    Van Erps, Juergen
    [J]. JOURNAL OF MICRO-NANOLITHOGRAPHY MEMS AND MOEMS, 2016, 15 (04):
  • [24] Optimization of Hot Embossing Condition Using Taguchi Method and Evaluation of Microchannels for Flexible On-Chip Proton-Exchange Membrane Fuel Cell
    Huang, Yubo
    Gao, Han
    Wu, Zhiheng
    Xiao, Hongyang
    Xia, Cao
    Xia, Yuanlin
    Wang, Zhuqing
    [J]. MICROMACHINES, 2024, 15 (08)
  • [25] Deep Proton Writing: A tool for rapid prototyping of polymer micro-opto-mechanical modules
    Debaes, C.
    Van Erps, J.
    Vervaeke, A.
    Desmet, L.
    Ottevaere, H.
    Gomez, V.
    Van Overmeire, S.
    Vynck, P.
    Hermanne, A.
    Thienpont, H.
    [J]. VIRTUAL AND RAPID MANUFACTURING: ADVANCED RESEARCH IN VIRTUAL AND RAPID PROTOTYPING, 2008, : 515 - 520
  • [26] Rapid feasibility assessment of components to be formed through hot stamping: A deep learning approach
    Attar, Hamid Reza
    Zhou, Haosu
    Foster, Alistair
    Li, Nan
    [J]. JOURNAL OF MANUFACTURING PROCESSES, 2021, 68 : 1650 - 1671
  • [27] Deep proton writing of high aspect ratio SU-8 micro-pillars on glass
    Ebraert, Evert
    Rwamucyo, Ben
    Thienpont, Hugo
    Van Erps, Jurgen
    [J]. NUCLEAR INSTRUMENTS & METHODS IN PHYSICS RESEARCH SECTION B-BEAM INTERACTIONS WITH MATERIALS AND ATOMS, 2016, 389 : 5 - 12
  • [28] High-precision 2-d SM fiber connectors fabricated through deep proton writing
    Van Erps, J. rgen
    Volckaerts, Bart
    van Amerongen, Harry
    Vynck, Pedro
    Krajewski, Rafal
    Debaes, Christof
    Watté, Jan
    Hermanne, Alex
    Thienpont, Hugo
    [J]. IEEE PHOTONICS TECHNOLOGY LETTERS, 2006, 18 (9-12) : 1164 - 1166
  • [29] Deep proton writing: a rapid prototyping polymer micro-fabrication tool for micro-optical modules
    Debaes, C.
    Van Erps, J.
    Vervaeke, M.
    Volckaerts, B.
    Ottevaere, H.
    Gomez, V.
    Vynck, P.
    Desmet, L.
    Krajewski, R.
    Ishii, Y.
    Hermanne, A.
    Thienpont, H.
    [J]. NEW JOURNAL OF PHYSICS, 2006, 8
  • [30] A Physics-Informed Deep Learning Model and Its Application in Heat Dissipation for Hot Section Components
    Zhou, Wei-Wei
    Wang, Qi
    Yang, Li
    Huang, Kang
    [J]. Tuijin Jishu/Journal of Propulsion Technology, 2022, 43 (10):