Year
Month
(Peer-Reviewed) Hybrid artificial neural networks and analytical model for prediction of optical constants and bandgap energy of 3D nanonetwork silicon structures
Shreeniket Joshi, Amirkianoosh Kiani
Silicon Hall: Micro/Nano Manufacturing Facility, Faculty of Engineering and Applied Science, Ontario Tech University, 2000 Simcoe St N, Oshawa, Ontario L1G 0C5, Canada
Opto-Electronic Advances, 2021-09-25
Abstract

The aim of this study is to develop a reliable method to determine optical constants for 3D-nanonetwork Si thin films manufactured using a pulsed-laser ablation technique that can be applied to other materials synthesized by this technique. An analytical method was introduced to calculate optical constants from reflectance and transmittance spectra.

Optical band gaps for this novel material and other important insights on the physical properties were derived from the optical constants. The existing optimization methods described in the literature were found to be complex and prone to errors while determining optical constants of opaque materials where only reflectance data is available.

A supervised Deep Learning Algorithm was developed to accurately predict optical constants from the reflectance spectrum alone. The hybrid method introduced in this study was proved to be effective with an accuracy of 95%.
Hybrid artificial neural networks and analytical model for prediction of optical constants and bandgap energy of 3D nanonetwork silicon structures_1
Hybrid artificial neural networks and analytical model for prediction of optical constants and bandgap energy of 3D nanonetwork silicon structures_2
Hybrid artificial neural networks and analytical model for prediction of optical constants and bandgap energy of 3D nanonetwork silicon structures_3
  • High-resolution tumor marker detection based on microwave photonics demodulated dual wavelength fiber laser sensor
  • Jie Hu, Weihao Lin, Liyang Shao, Chenlong Xue, Fang Zhao, Dongrui Xiao, Yang Ran, Yue Meng, Panpan He, Zhiguang Yu, Jinna Chen, Perry Ping Shum
  • Opto-Electronic Advances
  • 2024-12-16
  • High performance laser induced plasma assisted ablation by GHz burst mode femtosecond pulses
  • Jingbo Yin, Yulong Zhao, Minghui Hong
  • Opto-Electronic Advances
  • 2024-12-16
  • Sequential harmonic spin–orbit angular momentum generation in nonlinear optical crystals
  • Yutao Tang, Zixian Hu, Junhong Deng, Kingfai Li, Guixin Li
  • Opto-Electronic Advances
  • 2024-12-16
  • Design, setup, and facilitation of the speckle structured illumination endoscopic system
  • Elizabeth Abraham, Zhaowei Liu
  • Opto-Electronic Science
  • 2024-12-13
  • Ultra-high-Q photonic crystal nanobeam cavity for etchless lithium niobate on insulator (LNOI) platform
  • Zhi Jiang, Cizhe Fang, Xu Ran, Yu Gao, Ruiqing Wang, Jianguo Wang, Danyang Yao, Xuetao Gan, Yan Liu, Yue Hao, Genquan Han
  • Opto-Electronic Advances
  • 2024-10-31
  • Advanced biological imaging techniques based on metasurfaces
  • Yongjae Jo, Hyemi Park, Hyeyoung Yoon, Inki Kim
  • Opto-Electronic Advances
  • 2024-10-31
  • Orthogonal matrix of polarization combinations: concept and application to multichannel holographic recording
  • Shujun Zheng, Jiaren Tan, Hongjie Liu, Xiao Lin, Yusuke Saita, Takanori Nomura, Xiaodi Tan
  • Opto-Electronic Advances
  • 2024-10-23
  • Streamlined photonic reservoir computer with augmented memory capabilities
  • Changdi Zhou, Yu Huang, Yigong Yang, Deyu Cai, Pei Zhou, Kuenyao Lau, Nianqiang Li, Xiaofeng Li
  • Opto-Electronic Advances
  • 2024-10-22
  • High-precision multi-focus laser sculpting of microstructured glass
  • Kang Xu, Peilin Huang, Lingyu Huang, Li Yao, Zongyao Li, Jiantao Chen, Li Zhang, Shaolin Xu
  • Opto-Electronic Advances
  • 2024-10-09
  • Multi-physical field null medium: new solutions for the simultaneous control of EM waves and heat flow
  • Sailing He, Ruili Zhang, Junbo Liang
  • Opto-Electronic Advances
  • 2024-09-30
  • Adaptive decentralized AI scheme for signal recognition of distributed sensor systems
  • Shixiong Zhang, Hao Li, Cunzheng Fan, Zhichao Zeng, Chao Xiong, Jie Wu, Zhijun Yan, Deming Liu, Qizhen Sun
  • Opto-Electronic Advances
  • 2024-09-29
  • Data-driven polarimetric approaches fuel computational imaging expansion
  • Sylvain Gigan
  • Opto-Electronic Advances
  • 2024-09-28



  • Development of immune gene pair-based signature predictive of prognosis and immunotherapy in esophageal cancer                                Identification of lipid metabolism-related genes as prognostic indicators in papillary thyroid cancer
    About
    |
    Contact
    |
    Copyright © PubCard