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Effective Index of Silicon Nanowires on Silicon Substrates

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Conference

2022 ASEE Gulf Southwest Annual Conference

Location

Prairie View, Texas

Publication Date

March 16, 2022

Start Date

March 16, 2022

End Date

March 18, 2022

Tagged Topic

Diversity

Page Count

6

DOI

10.18260/1-2--39176

Permanent URL

https://peer.asee.org/39176

Download Count

228

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Paper Authors

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Toriano Armèl Thomas Norfolk State University

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Toriano graduated from Norfolk State University with his bachelor's in Electronics Engineering in the Summer of 2021. He is a lifelong competitive swimmer and water polo player and served on the Greater San Diego Science and Engineering Fair’s Student Advisory Board throughout high school. His passion for science and curiosity led him to pursue a degree in engineering. In his spare time, he enjoys photography, working on cars, and going to the beach. Toriano has an interest in green technology and hopes to work within the semiconductor industry. He is currently enrolled in the graduate program at Norfolk State University where he will obtain his master's in Electronics Engineering.

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Bini Ben

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Sacharia Albin Norfolk State University

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Dr. Sacharia Albin joined Norfolk State University in July 2011 as the Chair of the Engineering Department. He received his BS and MS degrees from the University of Kerala, and Ph.D. from the University of Poona, India. He was a design engineer in microelectronics at Hindustan Aeronautics, India for three years. He was awarded a Post-Doctoral Research Fellowship by the Science and Engineering Research Council at the University of Liverpool, UK. Dr. Albin conducted research on Si and GaAs electronic devices and semiconductor lasers at the research laboratories of GEC and ITT and published numerous articles in this field. He was a professor of Electrical and Computer Engineering at Dominion University. He has advised 14 PhD and 20 MS students. He received numerous awards: Doctoral Mentor Award 2010; Excellence in Teaching Award 2009; Most Inspiring Faculty Award 2008; Excellence in Research Award 2004; and Certificate of Recognition for Research - NASA, 1994. He is a Senior Member of the IEEE and a Member of the Electrochemical Society.

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Sunday Adeyinka Ajala Norfolk State University

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Ajala Sunday received the Bachelor of Science degree in Electrical and Electronics Engineering from the Obafemi Awolowo University, Nigeria, in August 2017. He is currently pursuing a master's degree in Electronics Engineering with NorfolkState University, Norfolk, VA, USA, where he works as a Research and Teaching Assistant with the Faculty of Engineering. His current research interests involve Dielectrophoresis, Microfluidic Biochip Fabrication, Deep Learning and Artificial Intelligence.

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Matthew Edward Bickett

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Ryan David Shahan Old Dominion University

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Ryan Shahan is a junior at Old Dominion University studying Applied Mathematics and Physics. This is his first research experience and he looks forward to applying the MATLAB skills he has learned during this program to his coursework at Old Dominion University.

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Puspita Panigrahi Norfolk State University

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Abstract

As the demand for renewable energy increases, developing a cost-effective method of manufacturing renewable energy systems, can aid in facilitating the growth of renewable energy consumption. It is the hope that driving down the cost of renewable energy systems will allow the technology to become more accessible around the world. In 2020, solar energy accounted for just 11% of all renewable energy consumption in the United States.[1] Current methods of manufacturing solar cells utilize costly anti-reflective coatings, to combat silicon’s natural reflectivity.[2] The bare surface of silicon reflects up to 35% of the light back into the atmosphere. In solar cells, the reflected light is wasted energy. By producing silicon nanowires (SiNWs) through Metal Assisted Chemical Etching, or the MACE process, the reflectivity can be reduced to near 0%. Our research highlights the process of analyzing silicon nanowire data to optimize the production of SiNWs through the MACE process. The MACE process produces SiNWs by chemically etching the bare surface of silicon in a solution of Hydrogen Peroxide (H₂O₂). The primary focus of the research involved analyzing the relationship between the variables of time and etchant concentration within the MACE process. Additionally, we have studied how such variables affect the refractive index and the reflectivity of the SiNW sample. This was achieved by collecting Scanning Electron Microscope (SEM) images of samples at varying durations of etching time, as well as varying concentrations of H₂O₂. The SEM images were then processed through MATLAB, where our written code would analyze the image, resulting in the air to silicon ratio. It is expected that a higher air/Si ratio will lower the refractive index of the SiNW layer, resulting in a low reflectivity. We have measured the reflectivity of the MACE treated samples, with varying wavelengths of light. We were able to conclude that the air/silicon ratio was directly proportional to H₂O₂ concentration. It was also found that the reflectivity decreased as both H₂O₂ concentration and etching time increased.

REFRENCES [1] “U.S. Energy Information Administration - EIA - independent statistics and analysis,” The United States consumed a record amount of renewable energy in 2020 - Today in Energy - U.S. Energy Information Administration (EIA). [Online]. Available: https://www.eia.gov/todayinenergy/detail.php?id=48396. [2] D. D. Rooij, “Anti reflective coating: Usage for solar panels,” Manage risks and maximize ROI for your PV and energy storage projects, 11-Oct-2021. [Online]. Available: https://sinovoltaics.com/learning-center/solar-cells/anti-reflective-coating-for-solar-panels/.

Thomas, T. A., & Ben, B., & Albin, S., & Ajala, S. A., & Bickett, M. E., & Shahan, R. D., & Panigrahi, P. (2022, March), Effective Index of Silicon Nanowires on Silicon Substrates Paper presented at 2022 ASEE Gulf Southwest Annual Conference, Prairie View, Texas. 10.18260/1-2--39176

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