[1] [1] XU B, ??IGUEZ J, BELLAICHE L. Designing lead-free antiferroelectrics for energy storage[J]. Nat Commun, 2017, 8(1): 15682.

[2] [2] LI W, ZHENG J, HU B, et al. High-performance solar flow battery powered by a perovskite/silicon tandem solar cell[J]. Nat Mater, 2020, 19(12): 1326-1331.

[3] [3] LI J, SHEN Z, CHEN X, et al. Grain-orientation-engineered multilayer ceramic capacitors for energy storage applications[J]. Nat Mater, 2020, 19(9): 999-1005.

[4] [4] ACOSTA M, NOVAK N, ROJAS V, et al. BaTiO3-based piezoelectrics: Fundamentals, current status, and perspectives[J]. Appl Phys Rev, 2017, 4: 041305.

[5] [5] URBAN J J, YUN W S, GU Q, et al. Synthesis of single-crystalline perovskite nanorods composed of barium titanate and strontium titanate[J]. J Am Chem Soc, 2002, 124(7): 1186-1187.

[6] [6] LI C, HAO H, XU B, et al. A progressive learning method for predicting the band gap of ABO3 perovskites using an instrumental variable[J]. J Mater Chem C, 2020, 8(9): 3127-3136.

[7] [7] ZHAI X, CHEN M, LU W. Accelerated search for perovskite materials with higher Curie temperature based on the machine learning methods[J]. Comput Mater Sci, 2018, 151: 41-48.

[8] [8] HU J, SONG Y. Piezoelectric modulus prediction using machine learning and graph neural networks[J]. Chem Phys Lett, 2022, 791: 139359.

[9] [9] KIM E, KIM J, MIN K. Prediction of dielectric constants of ABO3-type perovskites using machine learning and first-principles calculations[J]. Phys Chem Cheml Phys, 2022, 24(11): 7050-7059.

[10] [10] LIN X, LI C, HAO H, et al. Accelerated search for ABO3-type the electronic contribution of polycrystalline dielectric constants by machine learning[J]. Comput Mater Sci, 2021, 193: 110404.

[11] [11] ZHANG Y, HE X, CHEN Z, et al. Unsupervised discovery of solid-state lithium ion conductors[J]. Nat Commun, 2019, 10(1): 5260.

[12] [12] JIA X, DENG Y, BAO X, et al. Unsupervised machine learning for discovery of promising half-Heusler thermoelectric materials[J]. npj Comput Mater, 2022, 8(1): 34.

[13] [13] ESTERHUIZEN J A, GOLDSMITH B R, LINIC S. Uncovering electronic and geometric descriptors of chemical activity for metal alloys and oxides using unsupervised machine learning[J]. Chem Catal, 2021, 1(4): 923-940.

[14] [14] ONG S P, RICHARDS W D, JAIN A, et al. Python Materials Genomics (pymatgen): A robust, open-source python library for materials analysis[J]. Comput Mater Sci, 2013, 68: 314-319.

[15] [15] Tilley J D.The ABX3 Perovskite Structure[M]. John Wiley & Sons, Ltd, 2016: 1-41.

[16] [16] Macqueen J. Some methods for classification and analysis of multivariate observations[J]. Proc Symp Math Statist and Probability, 1967, 5th: 1.

[20] [20] WANG J-M, ZHANG W, HUA T, et al. Unsupervised learning of topological phase transitions using the Calinski-Harabaz index[J]. Phys, Rev, 2021, 3(1): 013074.

[21] [21] KIM Y M, PARK C, HA T, et al. High-k perovskite gate oxide BaHfO3[J]. APL Mater, 2017, 5(1): 016104.