Theses and Dissertations

Date of Award


Document Type


Degree Name

Master of Science (MS)


Electrical Engineering

First Advisor

Dr. Hasina F. Huq

Second Advisor

Dr. Heinrich Foltz

Third Advisor

Dr. Ahmed Touhami


In our work, we applied Taguchi Signal-to-noise (SNR) analysis to investigate the effect of varying three process parameters, namely- sputtering power, working pressure, and Ar gas flow rate on the surface and morphological properties of the RF sputtered p-Si and n-Si on Si substrate. We also inspected the contribution of process parameters on those properties by applying Analysis of Variance (ANOVA). Characteristics of thin films fabricated by RF magnetron sputtering vary with the recipes. Process parameters such as power, pressure, process gas flow rate, substrate temperature, and target to substrate distance determine the quality of the thin films. Some of these parameters contribute more significantly towards a specific property of the thin film than other parameters. For RF sputtered p-Si on Si Substrate, we tried to determine which parameters contribute most to surface properties like grain size, micro-stress, and surface roughness and the effect of variation of these parameters. We applied the same procedure for n-Si thin films. Using 2" diameter targets of thickness 0.125" each, thin films of two kinds were fabricated on Si substrate using RF magnetron sputtering system. For each material (p-Si / n-Si), two sets of inputs for the three mentioned process parameters were chosen; for power, we chose 100W, 150W, and 200W; 5mTorr, 10mTorr, and 15mTorr were chosen for pressure, and we varied Ar gas flow rate at 5, 10 and 15 sccm (standard cubic centimeter per minute). We applied the Taguchi Design of experiments method to find out the optimized process parameter combination. By performing Taguchi L9 orthogonal array, nine combinations of the recipe were prepared for sputtering p-Si and n-Si. The surface and morphological properties of those nine samples were therefore inspected. We studied surface roughness (form AFM & Profilometer), grain size and shape ( from XRD diffractometer) and micro-stress (from W-H plot). Signal-to-noise (SNR) analysis presents how the properties like roughness and grain size change with the process parameters' variation. We found that among the three process parameters, the contribution of sputtering power towards surface roughness and Ar pressure towards grain size are the greatest. We also observed that more sputtering power resulted in smoother surfaces and larger grain sizes. No significant effect was found for Ar gas flow rate from ANOVA test.


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