REFERENCES

1. Lin J, Ge G, Zhu K, et al. Simultaneously achieving high performance of energy storage and transparency via A-site non-stoichiometric defect engineering in KNN-based ceramics. Chem Eng J 2022;444:136538.

2. Ren X, Jin L, Peng Z, et al. Regulation of energy density and efficiency in transparent ceramics by grain refinement. Chem Eng J 2020;390:124566.

3. Lin J, Zhai J, Wu X, Ye H, Wang H. Expedient red emitting and transparency dual modulation in KNN-based transparent ceramics via sensitive photothermochromic behavior. ACS Appl Electron Mater 2021;3:1394-402.

4. Liu X, Tan P, Ma X, et al. Ferroelectric crystals with giant electro-optic property enabling ultracompact Q-switches. SCI 2022;376:371-7.

5. Wu X, Lin J, Xu Z, et al. Defect management and multi-mode optoelectronic manipulations via photo-thermochromism in smart windows. Laser Photonics Rev 2021;15:2100211.

6. Qiu C, Wang B, Zhang N, et al. Transparent ferroelectric crystals with ultrahigh piezoelectricity. Nature 2020;577:350-4.

7. Lin J, Wang P, Wang H, et al. Significantly Photo-Thermochromic KNN-Based “smart window” for sustainable optical data storage and anti-counterfeiting. Adv Opt Mater 2021;9:2100580.

8. Wang H, Lin J, Deng B, et al. Reversible multi-mode modulations of optical behavior in photochromic-translucent Nd-doped K_0.5Na_0.5NbO₃ ceramics. J Mater Chem C 2020;8:2343-52.

9. Zhao X, Chao X, Wu D, Liang P, Yang Z. Evaluation of birefringence contribution to transparency in (1-x)KNN-xSr(Al_0.5Ta_0.5)O₃ ceramics: a phase structure tailoring. J.Alloys Compd 2019;798:669-77.

10. Li K, Li FL, Wang Y, Kwok KW, Chan HLW. Hot-pressed K_0.48Na_0.52Nb_1-xBi_xO₃ (x = 0.05-0.15) lead-free ceramics for electro-optic applications. Mater Chem Phys 2011;131:320-4.

11. Xing J, Huang Y, Wu B, et al. Energy storage behavior in ErBiO₃ -Doped (K,Na)NbO₃ lead-free piezoelectric ceramics. ACS Appl Electron Mater 2020;2:3717-27.

12. Lin J, Jing W, Wang H, et al. Emission color-tunable and optical temperature sensing properties of Er³⁺/La³⁺ co-doped (K_0.5Na_0.5)NbO₃ optoelectronic transparent ceramic. J.Lumin 2019;213:158-63.

13. Yang D, Ma C, Yang Z, et al. Optical and electrical properties of pressureless sintered transparent (K_0.37Na_0.63)NbO₃-based ceramics. Ceram Int 2016;42:4648-57.

14. Zhang L, He M, Shao S. Machine learning for halide perovskite materials. Nano Energy 2020;78:105380.

15. Tao Q, Xu P, Li M, Lu W. Machine learning for perovskite materials design and discovery. npj Comput Mater 2021;7:23.

16. Mao X, Li Z, Li M, et al. Computational design and experimental validation of the optimal bimetal-doped SrCoO_3-δ perovskite as solid oxide fuel cell cathode. J Am Chem Soc 2021;143:9507-14.

17. Lu T, Li M, Lu W, Zhang T. Recent progress in the data-driven discovery of novel photovoltaic materials. J Mater Inf 2022;2:7.

18. Pan Z, Zhou Y, Zhang L. Photoelectrochemical properties, machine learning, and symbolic regression for molecularly engineered halide perovskite materials in water. ACS Appl Mater Interfaces 2022;14:9933-43.

19. Weng B, Song Z, Zhu R, et al. Simple descriptor derived from symbolic regression accelerating the discovery of new perovskite catalysts. Nat Commun 2020;11:3513.

20. Yuan R, Liu Z, Balachandran PV, et al. Accelerated discovery of large electrostrains in BaTiO₃-based piezoelectrics using active learning. Adv Mater 2018;30:1702884.

21. Umeda Y, Hayashi H, Moriwake H, Tanaka I. Prediction of dielectric constants using a combination of first principles calculations and machine learning. Jpn J Appl Phys 2019;58:SLLC01.

22. Liu D, Bai G, Gao C. Phase diagrams classification based on machine learning and phenomenological investigation of physical properties in K_1-_xNa_xNbO₃ thin films. J Appl Phys 2020;127:154101.

23. Yang Z, Gao Z, Sun X, Cai H, Zhang F, Wu X. High critical transition temperature of lead-based perovskite ferroelectric crystals: a machine learning study. Acta Phys Sin 2019;68:210502.

24. Zhai X, Chen M, Lu W. Accelerated search for perovskite materials with higher Curie temperature based on the machine learning methods. Comput Mater Sci 2018;151:41-8.

25. Balachandran PV, Kowalski B, Sehirlioglu A, Lookman T. Experimental search for high-temperature ferroelectric perovskites guided by two-step machine learning. Nat Commun 2018;9:1668.

26. Liu Y, Yan W, Han S, et al. How machine learning predicts and explains the performance of perovskite solar cells. Solar RRL 2022;6:2101100.

27. Pilania G, Mannodi-Kanakkithodi A, Uberuaga BP, Ramprasad R, Gubernatis JE, Lookman T. Machine learning bandgaps of double perovskites. Sci Rep 2016;6:19375.

28. Qin J, Liu Z, Ma M, Li Y. Machine learning approaches for permittivity prediction and rational design of microwave dielectric ceramics. J Materiomics 2021;7:1284-93.

29. Lu S, Zhou Q, Ma L, Guo Y, Wang J. Rapid discovery of ferroelectric photovoltaic perovskites and material descriptors via machine learning. Small Methods 2019;3:1900360.

30. Yuan R, Tian Y, Xue D, et al. Accelerated search for BaTiO₃-based ceramics with large energy storage at low fields using machine learning and experimental design. Adv Sci 2019;6:1901395.

31. He J, Yu C, Hou Y, et al. Accelerated discovery of high-performance piezocatalyst in BaTiO₃-based ceramics via machine learning. Nano Energy 2022;97:107218.

32. Xue D, Balachandran PV, Yuan R, et al. Accelerated search for BaTiO₃-based piezoelectrics with vertical morphotropic phase boundary using Bayesian learning. Proc Natl Acad Sci U S A 2016;113:13301-6.

33. Yuan R, Xue D, Xue D, et al. Knowledge-based descriptor for the compositional dependence of the phase transition in BaTiO₃-based ferroelectrics. ACS Appl Mater Interfaces 2020;12:44970-80.

34. Yu F, Chi Y, Wang P, et al. Highly responsive photochromic behavior with large coloration contrast in Ba/Sm co-doped (K_0.5Na_0.5)NbO₃ transparent ceramics. Ceram Int 2022;48:18899-908.

35. Ma Y, Yang S, Zhao C, et al. Photochromic and electric field-regulating luminescence in high-transparent (K,Na)NbO₃-based ferroelectric ceramics with two-phase coexistence. ACS Appl Mater Interfaces 2022;14:35940-8.

36. Jia Q, Zhang Q, Sun H, Hao X. High transmittance and optical storage behaviors in Tb³⁺ doped K_0.5Na_0.5NbO₃-based ferroelectric materials. J Eur Ceram 2021;41:1211-20.

37. Wu X, Yu F, Xiong R, et al. How to Realize ultrahigh photochromic performance for real-time optical recording in transparent ceramics. ACS Appl Mater Interfaces 2023;15:16828-41.

38. Lundberg S, Lee SI. A unified approach to interpreting model predictions. Available from: https://arxiv.org/abs/1705.07874. [Last accessed on 8 Jun 2023].

39. Gao D, Kwok KW, Lin D, Chan HLW. Microstructure and electrical properties of La-modified K_0.5Na_0.5NbO₃ lead-free piezoelectric ceramics. J Phys D: Appl Phys 2009;42:035411.

40. Lin J, Lu Q, Wu X, et al. In situ boost and reversible modulation of dual-mode photoluminescence under an electric field in a tape-casting-based Er-doped K_0.5Na_0.5NbO₃ laminar ceramic. J Mater Chem C 2019;7:7885-92.

41. Qu B, Du H, Yang Z. Lead-free relaxor ferroelectric ceramics with high optical transparency and energy storage ability. J Mater Chem C 2016;4:1795-803.