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   Das, Shaon; Garg, Prachi; Mazumder, Baishakhi (December 2024, Journal of the American Ceramic Society)

   Abstract This study employs a data‐driven machine learning approach to investigate specific ferroelectric properties of Al_1−xSc_xN thin films, targeting their application in next‐generation nonvolatile memory (NVM) devices. This approach analyzes a vast design space, encompassing over a million data points, to predict a wide range of coercive field values that are crucial for optimizing Al_1−xSc_xN‐based NVM devices. We evaluated seven machine learning models to predict the coercive field across a range of conditions, identifying the random forest algorithm as the most accurate, with a testR²value of 0.88. The model utilized five key features: film thickness, measurement frequency, operating temperature, scandium concentration, and growth temperature to predict the design space. Our analysis spans 13 distinct scandium concentrations and 13 growth temperatures, encompassing thicknesses from 9–1000 nm, frequencies from 1 to 100 kHz, and operating temperatures from 273 to 700 K. The predictions revealed dominant coercive field values between 3.0 and 4.5 MV/cm, offering valuable insights for the precise engineering of Al_1−xSc_xN‐based NVM devices. This work underscores the potential of machine learning in guiding the development of advanced ferroelectric materials with tailored properties for enhanced device performance. 

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5. Strain phase equilibria and phase‐field method of ferroelectric polydomain: A case study of monoclinic K _x Na _{1 −  x} NbO ₃ thin films

   https://doi.org/10.1111/jace.20072  

   Wang, Bo; Zhou, Meng‐Jun; Ladera, Adriana; Chen, Long‐Qing (August 2024, Journal of the American Ceramic Society)

   Abstract Knowledge of the thermodynamic equilibria and domain structures of ferroelectrics is critical to establishing their structure–property relationships that underpin their applications from piezoelectric devices to nonlinear optics. Here, we establish the strain condition for strain phase separation and polydomain formation and analytically predict the corresponding domain volume fractions and wall orientations of, relatively low symmetry and theoretically more challenging, monoclinic ferroelectric thin films by integrating thermodynamics of ferroelectrics, strain phase equilibria theory, microelasticity, and phase‐field method. Using monoclinic K_xNa_1 − xNbO₃(0.5 < x < 1.0) thin films as a model system, we establish the polydomain strain–strain phase diagrams, from which we identify two types of monoclinic polydomain structures. The analytically predicted strain conditions of formation, domain volume fractions, and domain wall orientations for the two polydomain structures are consistent with phase‐field simulations and in good agreement with experimental results in the literature. The present study demonstrates a general, powerful analytical theoretical framework to predict the strain phase equilibria and domain wall orientations of polydomain structures applicable to both high‐ and low‐symmetry ferroelectrics and provide fundamental insights into the equilibrium domain structures of ferroelectric K_xNa_1 − xNbO₃thin films that are of technology relevance for lead‐free dielectric and piezoelectric applications. 

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