Prediction of Lattice Constant of Pyrochlore Compounds Using Optimized Machine Learning Model
Author:
Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-99-3963-3_15
Reference10 articles.
1. Alade IO, Oyedeji MO, Rahman MAA, Saleh TA (2022) Prediction of the lattice constants of pyrochlore compounds using machine learning. Soft comput 26:8307–8315. https://doi.org/10.1007/s00500-022-07218-1
2. Nickolsky MS (2015) Predicting the lattice constants of the ternary pyrochlores A2B2O6O′. Acta Crystallogr B Struct Sci Cryst Eng Mater 71:235–240. https://doi.org/10.1107/S2052520615001973
3. Brik MG, Srivastava AM (2012) Pyrochlore structural chemistry: predicting the lattice constant by the ionic radii and electronegativities of the constituting ions. J Am Ceram Soc 95:1454–1460. https://doi.org/10.1111/j.1551-2916.2012.05115.x
4. Wei J, Chu X, Sun XY, Xu K, Deng HX, Chen J, Wei Z, Lei M (2019) Machine learning in materials science. https://doi.org/10.1002/inf2.12028
5. Zhang Y, Xu X (2021) Machine learning the lattice constant of cubic pyrochlore compounds. Int J Appl Ceram Technol 18:661–676. https://doi.org/10.1111/ijac.13709
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