Controllable Crystalline Phases of Multi‐Cation Oxides
Source abstract
Abstract
Abstract Multi‐cation oxides have been extensively studied over the past decade for various solid‐state applications. The source of their functionality lies in a wide compositional search space derived from countless cation combinations and diverse crystal structures formed in metal oxides. However, due to the vast space and complexity of structure control, material exploration has been limited to dispersed compositions under different synthesis conditions, hindering their systematic understanding and rational design. Here, a crystalline‐phase map of multi‐cation rare‐earth titanates is reported, where three types of crystals, i.e., cubic and hexagonal, and orthorhombic phases, emerge depending on the composition and temperature and exhibit systematic changes. The crystal structures of each phase are thoroughly characterized with X‐ray diffraction, electron microscopy, and first‐principles calculations. The configurational entropies calculated from the crystallographic information support the phase‐boundary shift between hexagonal and orthorhombic phases observed in the phase map. Further, a machine learning procedure is proposed for constructing the map from sparse experimental data, allowing predictive exploration for stable crystalline phases across a large compositional space. These findings may facilitate the design of multi‐cation oxides with a desired structure dispersed in a large search space.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Electronic and Structural Properties of Oxides · Ferroelectric and Piezoelectric Materials · Machine Learning in Materials Science
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Nanostructures Research Laboratory Japan Fine Ceramics Center 2‐4‐1 Mutsuno, Atsuta‐ku Nagoya Aichi 456‐8587 Japan
Materials Research and Development Laboratory Japan Fine Ceramics Center 2‐4‐1 Mutsuno, Atsuta‐ku Nagoya Aichi 456‐8587 Japan
Tokyo University of Technology 1404‐1, Katakura Hachioji Tokyo 192‐0982 Japan
Funding
Japan Society for the Promotion of Science London
References (97)
Show source-provided references
1. 10.1038/ncomms948510.1038/ncomms9485 ↗
2. 10.1038/s41578-019-0170-810.1038/s41578-019-0170-8 ↗
3. 10.1007/s40145-021-0477-y10.1007/s40145-021-0477-y ↗
4. 10.1039/D1EE00505G10.1039/D1EE00505G ↗
5. 10.1111/jace.1925210.1111/jace.19252 ↗
6. 10.1016/j.matlet.2023.13478510.1016/j.matlet.2023.134785 ↗
7. 10.1038/s41563-020-00816-010.1038/s41563-020-00816-0 ↗
8. 10.1038/s41586-022-05115-z10.1038/s41586-022-05115-z ↗
9. 10.1126/science.abq134610.1126/science.abq1346 ↗
10. 10.1021/jacs.2c0235310.1021/jacs.2c02353 ↗
11. 10.1002/adma.20221024310.1002/adma.202210243 ↗
12. 10.1002/advs.20220267110.1002/advs.202202671 ↗
13. 10.1002/advs.20220039110.1002/advs.202200391 ↗
14. 10.1111/ijac.1385610.1111/ijac.13856 ↗
15. 10.1039/D3TC00958K10.1039/D3TC00958K ↗
16. 10.1063/5.013887710.1063/5.0138877 ↗
17. 10.1002/adma.20180500410.1002/adma.201805004 ↗
18. 10.1016/j.scriptamat.2020.02.01110.1016/j.scriptamat.2020.02.011 ↗
19. 10.1016/j.actamat.2020.06.01210.1016/j.actamat.2020.06.012 ↗
20. 10.1016/j.jeurceramsoc.2023.06.05210.1016/j.jeurceramsoc.2023.06.052 ↗
21. 10.1016/j.jallcom.2023.17294210.1016/j.jallcom.2023.172942 ↗
22. 10.1007/s11666-024-01744-010.1007/s11666-024-01744-0 ↗
23. 10.1016/j.jeurceramsoc.2019.02.02210.1016/j.jeurceramsoc.2019.02.022 ↗
24. 10.1016/j.jeurceramsoc.2023.06.03010.1016/j.jeurceramsoc.2023.06.030 ↗
25. 10.1038/s41529-024-00462-w10.1038/s41529-024-00462-w ↗
26. 10.1016/j.scriptamat.2017.08.04010.1016/j.scriptamat.2017.08.040 ↗
27. 10.1016/j.jeurceramsoc.2017.12.05810.1016/j.jeurceramsoc.2017.12.058 ↗
28. 10.1021/acs.chemmater.0c0270210.1021/acs.chemmater.0c02702 ↗
29. 10.1111/jace.1765910.1111/jace.17659 ↗
30. 10.1016/j.jeurceramsoc.2021.05.04410.1016/j.jeurceramsoc.2021.05.044 ↗
31. 10.1016/j.actamat.2020.10.06110.1016/j.actamat.2020.10.061 ↗
32. 10.1016/j.ceramint.2021.11.25210.1016/j.ceramint.2021.11.252 ↗
33. 10.1038/s41524-024-01282-x10.1038/s41524-024-01282-x ↗
34. 10.1016/j.actamat.2018.04.03310.1016/j.actamat.2018.04.033 ↗
35. 10.1126/sciadv.adi296010.1126/sciadv.adi2960 ↗
36. 10.1111/jace.1930110.1111/jace.19301 ↗
37. 10.1038/s41586-023-06786-y10.1038/s41586-023-06786-y ↗
38. 10.1016/j.ceramint.2022.10.25810.1016/j.ceramint.2022.10.258 ↗
39. 10.3390/ma1606221910.3390/ma16062219 ↗
40. 10.3390/ma1606221410.3390/ma16062214 ↗
41. 10.1038/s41467-023-36947-610.1038/s41467-023-36947-6 ↗
42. 10.1016/j.jmat.2023.11.01710.1016/j.jmat.2023.11.017 ↗
43. 10.1016/j.actamat.2020.10.04310.1016/j.actamat.2020.10.043 ↗
44. 10.1021/jacs.2c1160810.1021/jacs.2c11608 ↗
45. 10.1016/j.jeurceramsoc.2021.03.03510.1016/j.jeurceramsoc.2021.03.035 ↗
46. 10.1021/acs.cgd.3c0071210.1021/acs.cgd.3c00712 ↗
47. 10.1016/j.jeurceramsoc.2016.09.01810.1016/j.jeurceramsoc.2016.09.018 ↗
48. 10.1038/s41467-018-05774-510.1038/s41467-018-05774-5 ↗
49. 10.1016/j.scriptamat.2019.02.03910.1016/j.scriptamat.2019.02.039 ↗
50. 10.1016/j.jssc.2020.12132810.1016/j.jssc.2020.121328 ↗
51. 10.2109/jcersj2.2016510.2109/jcersj2.20165 ↗
52. 10.1111/jace.1911010.1111/jace.19110 ↗
53. 10.1038/s41586-021-03428-z10.1038/s41586-021-03428-z ↗
54. 10.1038/s41467-021-25264-510.1038/s41467-021-25264-5 ↗
55. 10.1038/nmat458110.1038/nmat4581 ↗
56. 10.1126/sciadv.abc275810.1126/sciadv.abc2758 ↗
57. 10.1111/jace.1475610.1111/jace.14756 ↗
58. 10.1038/s41467-022-30674-010.1038/s41467-022-30674-0 ↗
59. 10.1111/jace.2022310.1111/jace.20223 ↗
60. 10.1016/j.actamat.2024.12028910.1016/j.actamat.2024.120289 ↗
61. 10.1021/jacs.0c1073910.1021/jacs.0c10739 ↗
62. 10.1021/jacs.2c0676810.1021/jacs.2c06768 ↗
63. 10.1016/j.ceramint.2021.05.14810.1016/j.ceramint.2021.05.148 ↗
64. 10.1016/j.jallcom.2023.17294510.1016/j.jallcom.2023.172945 ↗
65. 10.1038/s41467-022-30018-y10.1038/s41467-022-30018-y ↗
66. 10.1002/adma.20220743610.1002/adma.202207436 ↗
67. 10.1039/D3NR05176E10.1039/D3NR05176E ↗
68. Shepelev Y. F. · Inorg. Mater. (Engl. Transl.) · 2008 · 44 · 1496
69. 10.1111/jace.1731810.1111/jace.17318 ↗
70. 10.1038/nphys27010.1038/nphys270 ↗
71. 10.1016/j.ceramint.2023.03.12810.1016/j.ceramint.2023.03.128 ↗
72. Petrova M. A. · Izv. Akad. Nauk SSSR, Neorg. Mater; · 1986 · 22 · 1225
73. 10.1016/j.actamat.2021.11685810.1016/j.actamat.2021.116858 ↗
74. 10.1016/j.jssc.2007.10.02510.1016/j.jssc.2007.10.025 ↗
75. 10.1016/j.jssc.2014.02.02910.1016/j.jssc.2014.02.029 ↗
76. 10.1016/j.actamat.2020.11651810.1016/j.actamat.2020.116518 ↗
77. 10.1016/j.scriptamat.2019.12.02710.1016/j.scriptamat.2019.12.027 ↗
78. 10.1016/j.actamat.2021.11758110.1016/j.actamat.2021.117581 ↗
79. 10.1016/j.jallcom.2020.15842910.1016/j.jallcom.2020.158429 ↗
80. 10.1016/j.pmatsci.2006.09.00210.1016/j.pmatsci.2006.09.002 ↗
81. 10.1038/npjcompumats.2016.2810.1038/npjcompumats.2016.28 ↗
82. 10.1016/j.cossms.2023.10105710.1016/j.cossms.2023.101057 ↗
83. 10.1021/acs.chemmater.1c0236110.1021/acs.chemmater.1c02361 ↗
84. 10.1111/jace.1951810.1111/jace.19518 ↗
85. 10.1038/s41467-023-38423-710.1038/s41467-023-38423-7 ↗
86. 10.1002/aenm.20210235510.1002/aenm.202102355 ↗
87. 10.1038/s44160-024-00502-y10.1038/s44160-024-00502-y ↗
88. 10.4028/www.scientific.net/SSP.130.1510.4028/www.scientific.net/SSP.130.15 ↗
89. 10.1090/S0025-5718-1980-0572855-710.1090/S0025-5718-1980-0572855-7 ↗
90. 10.1017/S088571561300002X10.1017/S088571561300002X ↗
91. 10.1107/S002188981103897010.1107/S0021889811038970 ↗
92. 10.1016/0927-0256(96)00008-010.1016/0927-0256(96)00008-0 ↗
93. 10.1103/PhysRevB.59.175810.1103/PhysRevB.59.1758 ↗
94. 10.1103/PhysRevLett.100.13640610.1103/PhysRevLett.100.136406 ↗
95. 10.1016/j.calphad.2013.06.00610.1016/j.calphad.2013.06.006 ↗
96. Pedregosa F. · J. Machine Learn. Res. · 2011 · 12 · 2825
97. T.Akiba S.Sano T.Yanase T.Ohta M.Koyama InProceedings of the 25th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining2019.