کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
9821518 | 1518986 | 2005 | 8 صفحه PDF | دانلود رایگان |
عنوان انگلیسی مقاله ISI
Prediction of plasma-induced DC bias using polynomial neural network
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کلمات کلیدی
موضوعات مرتبط
مهندسی و علوم پایه
مهندسی مواد
سطوح، پوششها و فیلمها
پیش نمایش صفحه اول مقاله
![عکس صفحه اول مقاله: Prediction of plasma-induced DC bias using polynomial neural network Prediction of plasma-induced DC bias using polynomial neural network](/preview/png/9821518.png)
چکیده انگلیسی
DC bias plays an important role in characterizing or controlling plasma processes. A predictive DC bias model is constructed using a polynomial neural network (PNN) and a genetic algorithm (GA). The GA was used to optimize PNN training factors, including the number of input variables to a partial description (PD), the selection of input variables, and the type of polynomial for PD. The DC bias data were collected during the etching of silicon carbide in a C2F6 inductively coupled plasma. The process parameters involved are a radio frequency (rf) source power, bias power, pressure, gap, and O2 fraction. The etch process was characterized by a 25 full factorial experiment. Additional 17 experiments were conducted to test the predictive performance of constructed models. Compared to statistical regression models, GA-PNN demonstrated a drastic improvement in predicting DC bias under various plasma conditions. The GA-PNN can generally be applied to model other plasma processes.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Vacuum - Volume 79, Issues 3â4, 19 August 2005, Pages 111-118
Journal: Vacuum - Volume 79, Issues 3â4, 19 August 2005, Pages 111-118
نویسندگان
Byungwhan Kim, Dong-Won Kim, Gwi-Tae Park,