Thermodynamics and dielectric response of BaTiO3 by data-driven modeling

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Abstract
Cite
Gigli, Lorenzo, et al. “Thermodynamics and Dielectric Response of BaTiO3 by Data-Driven Modeling”. Npj Computational Materials, vol. 8, no. 1, 2022, https://doi.org/10.1038/s41524-022-00845-0.
Gigli, L., Veit, M., Kotiuga, M., Pizzi, G., Marzari, N., & Ceriotti, M. (2022). Thermodynamics and dielectric response of BaTiO3 by data-driven modeling. Npj Computational Materials, 8(1). https://doi.org/10.1038/s41524-022-00845-0
Gigli, Lorenzo, Max Veit, Michele Kotiuga, Giovanni Pizzi, Nicola Marzari, and Michele Ceriotti. “Thermodynamics and Dielectric Response of BaTiO3 by Data-Driven Modeling”. Npj Computational Materials 8, no. 1 (2022). https://doi.org/10.1038/s41524-022-00845-0.
Gigli L, Veit M, Kotiuga M, Pizzi G, Marzari N, Ceriotti M. Thermodynamics and dielectric response of BaTiO3 by data-driven modeling. npj Computational Materials. 2022;8(1).
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Refrences
Title Journal Journal Categories Citations Publication Date
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10.1103/PhysRevB.105.014304 Physical Review B 2022
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Citations Analysis
The category Technology: Electrical engineering. Electronics. Nuclear engineering: Materials of engineering and construction. Mechanics of materials 13 is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Ab initio structural optimization at finite temperatures based on anharmonic phonon theory: Application to the structural phase transitions of BaTiO3 and was published in 2022. The most recent citation comes from a 2024 study titled Ferroelectric and magnetic properties of Dy-doped BaTiO3 films. This article reached its peak citation in 2023, with 10 citations. It has been cited in 14 different journals, 21% of which are open access. Among related journals, the Journal of Applied Physics cited this research the most, with 2 citations. The chart below illustrates the annual citation trends for this article.
Citations used this article by year