Title: A Fourier-transformed feature engineering design for predicting ternary perovskite properties by coupling a two-dimensional convolutional neural network with a support vector machine (Conv2D-SVM)
Authors: *Ericsson Tetteh Chenebuah, Michel Nganbe and Alain Beaudelaire Tchagang
*Corresponding author: echen013@uottawa.ca
Department of Mechanical Engineering, University of Ottawa, 161 Louis-Pasteur, Ottawa, ON, K1N 6N5 Canada
Digital Technologies Research Centre, National Research Council of Canada, 1200 Montréal Road, Ottawa, ON, K1A 0R6 Canada
Cite as: Ericsson Tetteh Chenebuah et al 2023 Mater. Res. Express 10 026301, DOI: 10.1088/2053-1591/acb683 https://iopscience.iop.org/article/10.1088/2053-1591/acb683
Keywords: Perovskite, Fourier transformation, Convolutional Neural Network, Support Vector Machine, Energy bandgap.
This research was supported by the Natural Sciences and Engineering Research Council of Canada [NSERC Discovery Grant number: 210487-180599-2001]; and the National Research Council of Canada (NRC) through its Artificial Intelligence for Design Program led by the Digital Technologies Research Centre.
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