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Neural network characterization of plasma-induced charging damage on thick oxide-based metal-oxide-semiconductor device
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10.1063/1.3122602
/content/aip/journal/jap/105/11/10.1063/1.3122602
http://aip.metastore.ingenta.com/content/aip/journal/jap/105/11/10.1063/1.3122602

Figures

Image of FIG. 1.
FIG. 1.

Schematic of p-MOSFET with antenna.

Image of FIG. 2.
FIG. 2.

Effect of source power on . The bias power and gas ratio were set to 450 W and 1.0, respectively.

Image of FIG. 3.
FIG. 3.

Effect of bias power on . The source power and gas ratio were to 450 W and 1.0, respectively.

Image of FIG. 4.
FIG. 4.

Effect of gas ratio on . The source power and bias power were to the same 450 W.

Image of FIG. 5.
FIG. 5.

Optimized model prediction with actual measurements.

Image of FIG. 6.
FIG. 6.

Predicted as a function of source power and bias power. The gas ratio was set to 4.8.

Image of FIG. 7.
FIG. 7.

Predicted as a function of source power and gas ratio. The bias power was set to 250 W.

Image of FIG. 8.
FIG. 8.

Predicted as a function of bias power and gas ratio. The source power was set to 450 W.

Tables

Generic image for table
Table I.

Experimental data collected according to a face-centered Box–Wilson experiment.

Generic image for table
Table II.

Experimental ranges of BPNN training factors used of GA optimization.

Generic image for table
Table III.

GA-optimized training factors and prediction error.

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/content/aip/journal/jap/105/11/10.1063/1.3122602
2009-06-01
2014-04-24
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Neural network characterization of plasma-induced charging damage on thick oxide-based metal-oxide-semiconductor device
http://aip.metastore.ingenta.com/content/aip/journal/jap/105/11/10.1063/1.3122602
10.1063/1.3122602
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