Automated system for measuring electrophysical parameters of semiconductor structures
Author:
Publisher
Springer Science and Business Media LLC
Subject
Applied Mathematics,Instrumentation,General Engineering,Engineering (miscellaneous)
Link
https://link.springer.com/content/pdf/10.1007/s11018-023-02252-3.pdf
Reference11 articles.
1. M.A. Bronovets, N. M. Volodin, and Yu. N. Mishin, “New materials in semiconductor tensometry,” Mater. Lett., 267, 127467 (2022,). https://doi.org/10.1016/j.matlet.2020.127467
2. J. Xu, J. Wu, and X. Hu. “A Novel Electronic Component Classification Algorithm Based on Hierarchical Convolution Neural Network,” IOP Conf. Ser.: Earth Environ. Energy, 1, 042004 (2020). https://doi.org/10.1088/1755-1315/474/5/052081
3. J. Wade, J.R. Hollis, and S. Wood, Printed Electronics: Materials, Technologies and Applications, London, Published by IOP Publishing, wholly owned by The Institute of Physics (2018). https://doi.org/10.1088/978-0-7503-1608-8
4. D. Ma, “Optimizing Research on Solar Cell Semiconductor Materials in Optoelectronic Materials and Devices,” J. Phys.: Conf. Ser., 1865, 02207 (2021). https://doi.org/10.1088/1742-6596/1865/2/022078
5. S.N. Hood, A. Walsh, C. Persson et. al., “Status of materials and device modeling for kesterite solar cells,” J. Phys. Energy, 1, 042004 (2019). https://doi.org/10.1088/2515-7655/ab2dda
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