ANFIS-based Models for Coating Quality Prediction for Thin-Film Deposition Processes

Thin-film deposition processes have gained much popularity due to their unique capability to enhance the physical and chemical properties of various materials. Identification of the best parametric combination for a deposition process to achieve desired coating quality is often considered to be challenging due to the involvement of a large number of input process parameters and conflicting responses. This study discusses the development of adaptive neuro-fuzzy inference system-based models for the prediction of quality measures of two thin-film deposition processes, i.e., SiCN thin-film coating using thermal chemical vapor deposition (CVD) process and Ni–Cr alloy thin-film coating using direct current magnetron sputtering process. The predicted response values obtained from the developed models are validated and compared based on actual experimental results which exhibit a very close match between both the values. The corresponding surface plots obtained from the developed models illustrate the effect of each process parameter on the considered responses. These plots will help the operator in selecting the best parametric mix to achieve enhanced coating quality. Also, analysis of variance results identifies the importance of each process parameter in the determination of response values. The proposed approach can be applied to various deposition processes for modeling and prediction of observed response values. It will also assist as an operator in selecting the best parametric mix for achieving desired response values.

Ag-Yb Alloy-Novel Tunable Plasmonic Material

Metals are commonly used in plasmonic devices because of their strong plasmonic property. However, such properties are not easily tuned. For applications such as spatial light modulators and beam steering, tunable plasmonic properties are essential, and neither metals nor other plasmonic materials possess truly tunable plasmonic properties. In this work, we show that the silver alloy silver–ytterbium (Ag-Yb) possesses tunable plasmonic properties; its plasmonic response strength can be adjusted as a function of Yb concentration. Such tunability can be explained in terms of the influence of Yb on bound charge and interaction of its dielectric with the dielectric of Ag. The change in transition characteristics progressively weakens Ag’s plasmonic properties. With a spectral ellipsometric measurement, it was shown that the Ag-Yb alloy thin film retains the properties of Ag with high transmission efficiency. The weakened surface plasmon coupling strength without dramatic change in the coupling wavelengths implies that the tunability of the Ag-Yb alloy is related to its volume ratio. The principle mechanism of the plasmonic change is theoretically explained using a model. This work points to a potential new type of tunable plasmonic material.

Thermal Analysis of Energy Storage Capacity According to Thickness of Nickel/Chromium Alloy Layer

This paper examines a microconstruction consisting of nickel (Ni)/chromium (Cr) alloy thin-film. The total length of the microconstruction was 28 mm, the width was 0.2 mm, and the height was designed to be 1 μm. A thin-film of Ni/Cr alloy was co-sputtered on a silicon dioxide wafer patterned with photoresist via a RF magnetron sputtering system. The RF power ratios applied to the 4 inch target of Ni and Cr were 300 W:100 W (3:1), 300 W:150 W (2:1), and 150 W:150 W (1:1). The electrical resistance of the manufactured microconstruction was calculated and measured through Hall measurements. The temperature generated by applying 1–10 V to the microconstruction electrode was observed by using an infrared camera, and was summarized using a linear equation according to the power applied to each sample.