Application of resist-profile-aware source optimization in 28 nm full chip optical proximity correction

Jun Zhu; Wei Zhang; Chinte Kuo; Qing Wang; Fang Wei; Chenming Zhang; Han Chen; Daquan He; D. Hsu Stephen

doi:10.1088/1674-4926/38/7/074007

J. Semicond. > 2017, Volume 38 > Issue 7 > 074007

SEMICONDUCTOR DEVICES

Application of resist-profile-aware source optimization in 28 nm full chip optical proximity correction

Jun Zhu¹, Wei Zhang¹, Chinte Kuo¹, Qing Wang^2,, Fang Wei², Chenming Zhang², Han Chen², Daquan He² and D. Hsu Stephen³

+ Author Affiliations

Corresponding author: Qing Wang, Email: qangever@126.com

DOI: 10.1088/1674-4926/38/7/074007

Abstract: As technology node shrinks, aggressive design rules for contact and other back end of line (BEOL) layers continue to drive the need for more effective full chip patterning optimization. Resist top loss is one of the major challenges for 28 nm and below technology nodes, which can lead to post-etch hotspots that are difficult to predict and eventually degrade the process window significantly. To tackle this problem, we used an advanced programmable illuminator (FlexRay) and Tachyon SMO (Source Mask Optimization) platform to make resist-aware source optimization possible, and it is proved to greatly improve the imaging contrast, enhance focus and exposure latitude, and minimize resist top loss thus improving the yield.

Key words: integrated circuits, OPC, source optimization, lithography, resist top loss

References

[1]	Hsu S, Chen L, Liu H Y, et al. An innovative source-mask co-optimization (SMO) method for extending low k1 imaging. Proc SPIE, 2008, 7140(12): 714010 https://www.researchgate.net/publication/229001493_An_Innovative_Source-Mask_co-Optimization_SMO_Method_for_Extending_Low_k1_Imaging
[2]	Hsu S, Chen L, Liu H, et al. Source-mask cooptimization: optimize design for imaging and impact of source complexity on lithography performance. Proc SPIE, 2009, 7520(7): 712008 https://www.researchgate.net/publication/252623150_Source-mask_co-optimization_Optimize_design_for_imaging_and_impact_of_source_complexity_on_lithography_performance?ev=auth_pub
[3]	Zhang D Q, Chua G S, Foong Y M, et al. Source mask optimization methodology (SMO) & application to real full chip optical proximity correction. Proc SPIE, 2012, 8326: 83261V-11 doi: 10.1117/12.916614
[4]	Chen A, Foong Y M, Khoh A, et al. Resist profile aware source mask optimization. Proc SPIE, 2014, 9053(1): 43
[5]	Wang Z H, Liu W, Wang L, et al. Key process study in nanoimprint lithography. J Semicond, 2012, 33(10): 106002 doi: 10.1088/1674-4926/33/10/106002
[6]	Setten E V, Oorschot D, Manet C W, et al. EUV mask stack optimization for enhanced imaging performance. Proc SPIE, 2010, 7823(10): 782312
[7]	Zhou K J, Wang P J, Wen L. Design of power balance SRAM for DPA-resistance. J Semicond, 2016, 37(4): 045002 doi: 10.1088/1674-4926/37/4/045002
[8]	Yu J C, Yu P, Chao H Y. Fast source optimization involving quadratic line-contour objectives for the resist image. Opt Express, 2012, 20(7): 8161 doi: 10.1364/OE.20.008161
[9]	Xie C L, Chen Y, Shi Z. A novel OPC method to reduce mask volume with yield-aware dissection. J Semicond, 2013, 34(10): 106002 doi: 10.1088/1674-4926/34/10/106002
[10]	Yu M Y, Li T, Yang J Q, et al. A 1 V 186-μW 50-MS/s 10-bit subrange SAR ADC in 130-nm CMOS process. J Semicond, 2016, 37(7): 075005 doi: 10.1088/1674-4926/37/7/075005
[11]	Song Z, Ma X, Gao J, et al. Inverse lithography source optimization via compressive sensing. Opt Express, 2014, 22(12): 14180 doi: 10.1364/OE.22.014180
[12]	Zhong S, Zhu Z M. A 0.1-1.5 GHz, low jitter, area efficient PLL in 55-nm CMOS process. J Semicond, 2016, 37(5): 055004 doi: 10.1088/1674-4926/37/5/055004
[13]	Pang L, Xiao G, Tolani V, et al. Inverse lithography technology (ILT) enabled source mask optimization (SMO). ECS Trans, 2009, 18(1): 299 http://d.wanfangdata.com.cn/Conference/WFHYXW355775
[14]	Koops H W P, Kretz J, Weber M. Combined lithographies for the reduction of stitching errors in lithography. J Vac Sci Technol B, 1994, 12(6): 3265 doi: 10.1116/1.587609
[15]	Li J, Shen Y, Lam E Y. Hotspot-aware fast source and mask optimization. Opt Express, 2012, 20(19): 21792 doi: 10.1364/OE.20.021792
[16]	Granik Y. Source optimization for image fidelity and throughput. J Microlithography Microfabric Microsyst, 2007, 3(4): 509
[17]	Clerc F, Farrusseng D, Mirodatos C. A versatile open-source optimization platform for experimental design. Chemometrics & Intelligent Laboratory Systems, 2008, 93(2): 167 https://www.researchgate.net/publication/223350594_OptiCat_A_versatile_open-source_optimization_platform_for_experimental_design
[18]	Erdmann A, Farkas R, Fuehner T, et al. Mask and source optimization for lithographic imaging systems. Proc SPIE, 2003: 5182

Fig. 1. At 2x node, resist top loss and sidewall angle variation.

DownLoad: Full-Size Img PowerPoint

Fig. 2. (Color online) Full chip SMO source optimization flow.

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Fig. 3. (Color online) Using R3D model (optimizing the top and bottom contours) in SMO enables a source that improves CD profile across process window.

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Fig. 4. (Color online) FMO flow.

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Fig. 5. (Color online) Resist 3D (R3D) model.

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Fig. 6. (Color online) Post-etch CD variation.

DownLoad: Full-Size Img PowerPoint

Fig. 7. (Color online) PW comparison between 13 clips and 98 clips.

DownLoad: Full-Size Img PowerPoint

Fig. 8. (Color online) PW comparison of POR and FFS.

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Fig. 9. (Color online) BFS comparison.

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Fig. 10. (Color online) Simulation contours match SEM image.

DownLoad: Full-Size Img PowerPoint

Fig. 11. (Color online) Top and bottom contour comparison for both POR and FFS.

DownLoad: Full-Size Img PowerPoint

Fig. 13. AEI SEM image comparison on hotspot 2 for (a) POR and (b) FFS source.

DownLoad: Full-Size Img PowerPoint

Fig. 12. AEI SEM image comparison on hotspot 1 for (a) POR and (b) FFS source.

DownLoad: Full-Size Img PowerPoint

Table 1. Key litho-spec comparison on POR and FFS.

DownLoad: CSV

[1]	Hsu S, Chen L, Liu H Y, et al. An innovative source-mask co-optimization (SMO) method for extending low k1 imaging. Proc SPIE, 2008, 7140(12): 714010 https://www.researchgate.net/publication/229001493_An_Innovative_Source-Mask_co-Optimization_SMO_Method_for_Extending_Low_k1_Imaging
[2]	Hsu S, Chen L, Liu H, et al. Source-mask cooptimization: optimize design for imaging and impact of source complexity on lithography performance. Proc SPIE, 2009, 7520(7): 712008 https://www.researchgate.net/publication/252623150_Source-mask_co-optimization_Optimize_design_for_imaging_and_impact_of_source_complexity_on_lithography_performance?ev=auth_pub
[3]	Zhang D Q, Chua G S, Foong Y M, et al. Source mask optimization methodology (SMO) & application to real full chip optical proximity correction. Proc SPIE, 2012, 8326: 83261V-11 doi: 10.1117/12.916614
[4]	Chen A, Foong Y M, Khoh A, et al. Resist profile aware source mask optimization. Proc SPIE, 2014, 9053(1): 43
[5]	Wang Z H, Liu W, Wang L, et al. Key process study in nanoimprint lithography. J Semicond, 2012, 33(10): 106002 doi: 10.1088/1674-4926/33/10/106002
[6]	Setten E V, Oorschot D, Manet C W, et al. EUV mask stack optimization for enhanced imaging performance. Proc SPIE, 2010, 7823(10): 782312
[7]	Zhou K J, Wang P J, Wen L. Design of power balance SRAM for DPA-resistance. J Semicond, 2016, 37(4): 045002 doi: 10.1088/1674-4926/37/4/045002
[8]	Yu J C, Yu P, Chao H Y. Fast source optimization involving quadratic line-contour objectives for the resist image. Opt Express, 2012, 20(7): 8161 doi: 10.1364/OE.20.008161
[9]	Xie C L, Chen Y, Shi Z. A novel OPC method to reduce mask volume with yield-aware dissection. J Semicond, 2013, 34(10): 106002 doi: 10.1088/1674-4926/34/10/106002
[10]	Yu M Y, Li T, Yang J Q, et al. A 1 V 186-μW 50-MS/s 10-bit subrange SAR ADC in 130-nm CMOS process. J Semicond, 2016, 37(7): 075005 doi: 10.1088/1674-4926/37/7/075005
[11]	Song Z, Ma X, Gao J, et al. Inverse lithography source optimization via compressive sensing. Opt Express, 2014, 22(12): 14180 doi: 10.1364/OE.22.014180
[12]	Zhong S, Zhu Z M. A 0.1-1.5 GHz, low jitter, area efficient PLL in 55-nm CMOS process. J Semicond, 2016, 37(5): 055004 doi: 10.1088/1674-4926/37/5/055004
[13]	Pang L, Xiao G, Tolani V, et al. Inverse lithography technology (ILT) enabled source mask optimization (SMO). ECS Trans, 2009, 18(1): 299 http://d.wanfangdata.com.cn/Conference/WFHYXW355775
[14]	Koops H W P, Kretz J, Weber M. Combined lithographies for the reduction of stitching errors in lithography. J Vac Sci Technol B, 1994, 12(6): 3265 doi: 10.1116/1.587609
[15]	Li J, Shen Y, Lam E Y. Hotspot-aware fast source and mask optimization. Opt Express, 2012, 20(19): 21792 doi: 10.1364/OE.20.021792
[16]	Granik Y. Source optimization for image fidelity and throughput. J Microlithography Microfabric Microsyst, 2007, 3(4): 509
[17]	Clerc F, Farrusseng D, Mirodatos C. A versatile open-source optimization platform for experimental design. Chemometrics & Intelligent Laboratory Systems, 2008, 93(2): 167 https://www.researchgate.net/publication/223350594_OptiCat_A_versatile_open-source_optimization_platform_for_experimental_design
[18]	Erdmann A, Farkas R, Fuehner T, et al. Mask and source optimization for lithographic imaging systems. Proc SPIE, 2003: 5182

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Received: 18 December 2016 Revised: 10 January 2017 Online: Published: 01 July 2017

Article Navigation > Journal of Semiconductors > 2017 > 38(7): 074007

Jun Zhu, Wei Zhang, Chinte Kuo, Qing Wang, Fang Wei, Chenming Zhang, Han Chen, Daquan He, D. Hsu Stephen. Application of resist-profile-aware source optimization in 28 nm full chip optical proximity correction[J]. Journal of Semiconductors, 2017, 38(7): 074007. doi: 10.1088/1674-4926/38/7/074007 ****J Zhu, W Zhang, C N T Kuo, Q Wang, F Wei, C M Zhang, H Chen, D Q He, D H Stephen. Application of resist-profile-aware source optimization in 28 nm full chip optical proximity correction[J]. J. Semicond., 2017, 38(7): 074007. doi: 10.1088/1674-4926/38/7/074007.

Citation:

J Zhu, W Zhang, C N T Kuo, Q Wang, F Wei, C M Zhang, H Chen, D Q He, D H Stephen. Application of resist-profile-aware source optimization in 28 nm full chip optical proximity correction[J]. J. Semicond., 2017, 38(7): 074007. doi: 10.1088/1674-4926/38/7/074007.

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Application of resist-profile-aware source optimization in 28 nm full chip optical proximity correction

DOI: 10.1088/1674-4926/38/7/074007

1.
State Key Laboratory of ASIC and System, School of Microelectronics, Fudan University, Shanghai 200433, China
2.
Shanghai Huali Microelectronics Corp., Shanghai 200433, China
3.
ASML Brion, USA

More Information

Corresponding author: Qing Wang, Email: qangever@126.com
Received Date: 2016-12-18
Revised Date: 2017-01-10
Published Date: 2017-07-01

Abstract

Abstract

As technology node shrinks, aggressive design rules for contact and other back end of line (BEOL) layers continue to drive the need for more effective full chip patterning optimization. Resist top loss is one of the major challenges for 28 nm and below technology nodes, which can lead to post-etch hotspots that are difficult to predict and eventually degrade the process window significantly. To tackle this problem, we used an advanced programmable illuminator (FlexRay) and Tachyon SMO (Source Mask Optimization) platform to make resist-aware source optimization possible, and it is proved to greatly improve the imaging contrast, enhance focus and exposure latitude, and minimize resist top loss thus improving the yield.
- integrated circuits,
- OPC,
- source optimization,
- lithography,
- resist top loss

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References(18)

References

[1]	Hsu S, Chen L, Liu H Y, et al. An innovative source-mask co-optimization (SMO) method for extending low k1 imaging. Proc SPIE, 2008, 7140(12): 714010 https://www.researchgate.net/publication/229001493_An_Innovative_Source-Mask_co-Optimization_SMO_Method_for_Extending_Low_k1_Imaging
[2]	Hsu S, Chen L, Liu H, et al. Source-mask cooptimization: optimize design for imaging and impact of source complexity on lithography performance. Proc SPIE, 2009, 7520(7): 712008 https://www.researchgate.net/publication/252623150_Source-mask_co-optimization_Optimize_design_for_imaging_and_impact_of_source_complexity_on_lithography_performance?ev=auth_pub
[3]	Zhang D Q, Chua G S, Foong Y M, et al. Source mask optimization methodology (SMO) & application to real full chip optical proximity correction. Proc SPIE, 2012, 8326: 83261V-11 doi: 10.1117/12.916614
[4]	Chen A, Foong Y M, Khoh A, et al. Resist profile aware source mask optimization. Proc SPIE, 2014, 9053(1): 43
[5]	Wang Z H, Liu W, Wang L, et al. Key process study in nanoimprint lithography. J Semicond, 2012, 33(10): 106002 doi: 10.1088/1674-4926/33/10/106002
[6]	Setten E V, Oorschot D, Manet C W, et al. EUV mask stack optimization for enhanced imaging performance. Proc SPIE, 2010, 7823(10): 782312
[7]	Zhou K J, Wang P J, Wen L. Design of power balance SRAM for DPA-resistance. J Semicond, 2016, 37(4): 045002 doi: 10.1088/1674-4926/37/4/045002
[8]	Yu J C, Yu P, Chao H Y. Fast source optimization involving quadratic line-contour objectives for the resist image. Opt Express, 2012, 20(7): 8161 doi: 10.1364/OE.20.008161
[9]	Xie C L, Chen Y, Shi Z. A novel OPC method to reduce mask volume with yield-aware dissection. J Semicond, 2013, 34(10): 106002 doi: 10.1088/1674-4926/34/10/106002
[10]	Yu M Y, Li T, Yang J Q, et al. A 1 V 186-μW 50-MS/s 10-bit subrange SAR ADC in 130-nm CMOS process. J Semicond, 2016, 37(7): 075005 doi: 10.1088/1674-4926/37/7/075005
[11]	Song Z, Ma X, Gao J, et al. Inverse lithography source optimization via compressive sensing. Opt Express, 2014, 22(12): 14180 doi: 10.1364/OE.22.014180
[12]	Zhong S, Zhu Z M. A 0.1-1.5 GHz, low jitter, area efficient PLL in 55-nm CMOS process. J Semicond, 2016, 37(5): 055004 doi: 10.1088/1674-4926/37/5/055004
[13]	Pang L, Xiao G, Tolani V, et al. Inverse lithography technology (ILT) enabled source mask optimization (SMO). ECS Trans, 2009, 18(1): 299 http://d.wanfangdata.com.cn/Conference/WFHYXW355775
[14]	Koops H W P, Kretz J, Weber M. Combined lithographies for the reduction of stitching errors in lithography. J Vac Sci Technol B, 1994, 12(6): 3265 doi: 10.1116/1.587609
[15]	Li J, Shen Y, Lam E Y. Hotspot-aware fast source and mask optimization. Opt Express, 2012, 20(19): 21792 doi: 10.1364/OE.20.021792
[16]	Granik Y. Source optimization for image fidelity and throughput. J Microlithography Microfabric Microsyst, 2007, 3(4): 509
[17]	Clerc F, Farrusseng D, Mirodatos C. A versatile open-source optimization platform for experimental design. Chemometrics & Intelligent Laboratory Systems, 2008, 93(2): 167 https://www.researchgate.net/publication/223350594_OptiCat_A_versatile_open-source_optimization_platform_for_experimental_design
[18]	Erdmann A, Farkas R, Fuehner T, et al. Mask and source optimization for lithographic imaging systems. Proc SPIE, 2003: 5182

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