Process optimization for shallow trench isolation etch using computational models

被引:5
|
作者
Huang, Shuo [1 ]
Panneerchelvam, Prem [2 ]
Huard, Chad M. [2 ]
Sridhar, Shyam [3 ]
Ventzek, Peter L. G. [3 ]
Smith, Mark D. [4 ]
机构
[1] KLA Corp, 1200 Woodridge Ave, Ann Arbor, MI 48105 USA
[2] KLA Corp, 8834 N Capital Texas HW,Suite 301, Austin, TX 78759 USA
[3] Tokyo Electron Amer Inc, 2400 Grove Blvd, Austin, TX 78741 USA
[4] KLA Corp, 1 Technol Dr, Milpitas, CA 95035 USA
来源
关键词
SILICON DIOXIDE; PLASMA; DEPOSITION; SIO2;
D O I
10.1116/6.0002838
中图分类号
TB3 [工程材料学];
学科分类号
0805 ; 080502 ;
摘要
The critical dimensions of advanced semiconductor manufacturing processes have decreased to a few tens of nanometers while the aspect ratios have increased beyond 100. The performance of plasma etch patterning processes as well as the cost and time of the development cycle are critical to the success of ramping a new technology node toward profitable high-volume manufacturing. In this paper, a computational patterning software, ProETCH (R), has been developed with rigorous physics and advanced algorithms for modeling the etch patterning process, with the featured capabilities in calibrating the reaction mechanisms and optimizing the etch process. A shallow trench isolation etch process using self-aligned double patterning was investigated. A reaction mechanism of silicon etch by Ar/Cl-2 plasma was developed to address the surface reactions, and a plasma hypermodel was introduced to correlate process operating conditions to plasma parameters at the wafer surface. The parameters of the reaction mechanism and the plasma hypermodel were calibrated with experimental data obtained from cross-sectional scanning electron microscope (XSEM) images. The calibrated model is used to identify the different fundamental pathways that contribute to the observed profile metrics in XSEMs. The model was then used for process development and optimization by solving the forward and inverse problems. In the forward problem, the model is used to predict the etching profile at different process conditions. Predictions for both interpolation conditions (process parameters within the range used for developing the model) and extrapolation conditions (process parameters outside of the range used for developing the model) agree well with the experimental data with the root mean square error less than 4 nm (1 nm resolution used for the mesh). In the inverse problem, the developed model is used to search for process conditions (e.g., values of bias power and pressure), which could result in desirable profiles. The solutions to the inverse problem demonstrate a degeneracy in process space of the etching process for a given target profile.
引用
收藏
页数:15
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