20 December 2018 Optimized parameters selected on the basis of the development defect model
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Abstract
With the continuous shrinking of critical dimension, it may require more time and effort to reduce or remove the lithography defects in the development process. Therefore, defect reduction has become one of the most important technical challenges in device mass production. With the purpose of finding an optimizing recipe, we can simulate group parameters, including nitrogen gas dispensation and wafer-rotation speed. From previous studies, we have established a model based on viscous fluid dynamics and have calculated the removing force distribution across the 300-mm-diameter wafer for the defect residual. In this model, we assumed that the defects mostly are polymer residual; once the removing force reached a certain threshold level (1  ×  10  −  14  N), the defect with a “centered-ring-like” signature could be removed. For illustration, several groups of optimal parameter under postdeveloping rinse process conditions are given. The numerical simulations represent several recipes in the development process. We find that we can reproduce a group of the total force curves. From the simulation, we could find that we can get the minimally required strength from the three parameters for defect removal. We have done some experiments to validate the simulation results. The experimental data are almost in agreement with the simulation data. Therefore, the above simulation results have verified the effectiveness and validity of the proposed optimization methodology, and it also has shown that the trend of parameters provided by the optimized method has the potential to be an efficient candidate for reducing or removing lithography defects in the development process.
© 2018 Society of Photo-Optical Instrumentation Engineers (SPIE) 1932-5150/2018/$25.00 © 2018 SPIE
Ling Ma, Buqing Xu, Qiang Wu, Lisong Dong, Taian Fan, Yuntao Jiang, and Yayi Wei "Optimized parameters selected on the basis of the development defect model," Journal of Micro/Nanolithography, MEMS, and MOEMS 17(4), 043508 (20 December 2018). https://doi.org/10.1117/1.JMM.17.4.043508
Received: 29 September 2018; Accepted: 30 November 2018; Published: 20 December 2018
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KEYWORDS
Semiconducting wafers

Lithography

Nitrogen

Photoresist materials

Particles

Computer simulations

Microelectronics

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