REFERENCES

1. White House Office of Science and Technology Policy. Materials genome initiative for global competitiveness. Available from: https://obamawhitehouse.archives.gov/sites/default/files/microsites/ostp/materials_genome_initiative-final.pdf [Last accessed on 13 Sep 2022].

2. Su Y, Fu H, Bai Y, Jiang X, Xie J. Progress in materials genome engineering in China. Acta Metallurgica Sinica 2020;56:1313-23.

3. Xie J, Su Y, Xue D, Jiang X, Fu H, Huang H. Machine learning for materials research and development. Acta Metallurgica Sinica 2021;57:1343-61.

4. Xie J, Su Y, Zhang D, Feng Q. A vision of materials genome engineering in China. Engineering 2022;10:10-2.

5. Wen C, Zhang Y, Wang C, et al. Machine learning assisted design of high entropy alloys with desired property. Acta Materialia 2019;170:109-17.

6. Liu P, Huang H, Antonov S, et al. Machine learning assisted design of γ′-strengthened Co-base superalloys with multi-performance optimization. npj Comput Mater 2020:6.

7. Zhang Y, Wen C, Wang C, et al. Phase prediction in high entropy alloys with a rational selection of materials descriptors and machine learning models. Acta Materialia 2020;185:528-39.

8. Hart GLW, Mueller T, Toher C, Curtarolo S. Machine learning for alloys. Nat Rev Mater 2021;6:730-55.

9. Liu Y, Guo B, Zou X, Li Y, Shi S. Machine learning assisted materials design and discovery for rechargeable batteries. Energy Stor Mater 2020;31:434-50.

10. Wang T, Zhang C, Snoussi H, Zhang G. Machine learning approaches for thermoelectric materials research. Adv Funct Mater 2020;30:1906041.

11. Lookman T, Balachandran PV, Xue D, Yuan R. Active learning in materials science with emphasis on adaptive sampling using uncertainties for targeted design. npj Comput Mater 2019:5.

12. Xia Z, Liu Q. Progress in discovery and structural design of color conversion phosphors for LEDs. Progr Mater Sci 2016;84:59-117.

13. Xia Z, Meijerink A. Ce3+-doped garnet phosphors: composition modification, luminescence properties and applications. Chem Soc Rev 2017;46:275-99.

14. Li S, Wang L, Hirosaki N, Xie R. Color conversion materials for high - brightness laser - driven solid - state lighting. Laser & Phot Revi 2018;12:1800173.

15. Wang Y, Ding J, Wang Y, et al. Structural design of new Ce3+/Eu2+ -doped or co-doped phosphors with excellent thermal stabilities for WLEDs. J Mater Chem C 2019;7:1792-820.

16. Tian J, Zhuang W. Thermal stability of nitride phosphors for light-emitting diodes. Inorg Chem Front 2021;8:4933-54.

17. He M, Jia J, Zhao J, Qiao X, Du J, Fan X. Glass-ceramic phosphors for solid state lighting: a review. Ceram Int 2021;47:2963-80.

18. Dang P, Wang W, Lian H, Li G, Lin J. How to obtain anti-thermal-quenching inorganic luminescent materials for light-emitting diode applications. Adv Opt Mater 2022;10:2102287.

19. Zhao F, Song Z, Liu Q. Advances in chromium-activated phosphors for near-infrared light sources. Laser & Photonics Rev ;2022:2200380.

20. Xiahou J, Zhu Q, Zhu L, Li S, Li J. Local structure Regulation in near-infrared persistent phosphor of ZnGa2O4:Cr3+ to fabricate natural-light rechargeable optical thermometer. ACS Appl Electron Mater 2021;3:3789-803.

21. Jiang L, Jiang X, Xie J, Zheng T, Lv G, Su Y. Structural induced tunable NIR luminescence of (Y,Lu)3(Mg,Al)2(Al,Si)3O12:Cr3+ phosphors. J Lumin 2022;247:118911.

22. Liu T, Cai H, Mao N, Song Z, Liu Q. Efficient near-infrared pyroxene phosphor LiInGe 2O6:Cr 3+ for NIR spectroscopy application. J Am Ceram Soc 2021;104:4577-84.

23. Zeng H, Zhou T, Wang L, Xie R. Two-Site Occupation for exploring ultra-broadband near-infrared phosphor - double-perovskite La2MgZrO6:Cr3+. Chem Mater 2019;31:5245-53.

24. He C, Ji H, Huang Z, et al. Red-shifted emission in Y3MgSiAl3O12:Ce3+ garnet phosphor for blue light-pumped white light-emitting diodes. J Phys Chem C 2018;122:15659-65.

25. Yan Y, Shang M, Huang S, et al. Photoluminescence properties of AScSi2O6:Cr3+ (A = Na and Li) phosphors with high efficiency and thermal stability for near-infrared phosphor-converted light-emitting diode light sources. ACS Appl Mater Interfaces 2022;14:8179-90.

26. Wang Y, Wang Z, Wei G, et al. Ultra-broadband and high efficiency near-infrared Gd3ZnGa5-2GeO12:Cr3+ (x = 0-2.0) garnet phosphors via crystal field engineering. Chem Eng J 2022;437:135346.

27. Zhang L, Wang D, Hao Z, et al. Cr3+-doped broadband NIR garnet phosphor with enhanced luminescence and its application in NIR spectroscopy. Adv Optical Mater 2019;7:1900185.

28. Jiang L, Zhang X, Tang H, et al. A Mg2+-Ge4+ substituting strategy for optimizing color rendering index and luminescence of YAG: Ce3+ phosphors for white LEDs. Mater Res Bull 2018;98:180-6.

29. Jiang L, Jiang X, Xie J, et al. Ultra-broadband near-infrared Gd3MgScGa2SiO12:Cr, Yb phosphors: photoluminescence properties and LED applications. J Alloys Comp 2022;920:165912.

30. Zhuo Y, Mansouri Tehrani A, Oliynyk AO, Duke AC, Brgoch J. Identifying an efficient, thermally robust inorganic phosphor host via machine learning. Nat Commun 2018;9:4377.

31. Barai VL, Dhoble S. Prediction of excitation wavelength of phosphors by using machine learning model. J Lumin 2019;208:437-42.

32. Zhuo Y, Hariyani S, You S, Dorenbos P, Brgoch J. Machine learning 5d-level centroid shift of Ce3+ inorganic phosphors. J Appl Phys 2020;128:013104.

33. Zhuo Y, Hariyani S, Armijo E, Abolade Lawson Z, Brgoch J. Evaluating thermal quenching temperature in eu3+-substituted oxide phosphors via machine learning. ACS Appl Mater Interfaces 2020;12:5244-50.

34. Park C, Lee J, Kim M, et al. A data-driven approach to predicting band gap, excitation, and emission energies for Eu2+-activated phosphors. Inorg Chem Front 2021;8:4610-24.

35. Lv R, Xiao L, Jiang X, Feng M, Yang F, Tian J. Optimization of red luminescent intensity in Eu3+-doped lanthanide phosphors using genetic algorithm. ACS Biomater Sci Eng 2018;4:4378-84.

36. Lv R, Xiao L, Wang Y, Yang F, Tian J, Lin J. Searching for the optimized luminescent lanthanide phosphor using heuristic algorithms. Inorg Chem 2019;58:6458-66.

37. Yang F, Wang Y, Jiang X, Lin B, Lv R. Optimized multimetal sensitized phosphor for enhanced red up-conversion luminescence by machine learning. ACS Comb Sci 2020;22:285-96.

38. Yuan H, Qi L, Paris M, et al. Machine learning guided design of single-phase hybrid lead halide white phosphors. Adv Sci (Weinh) 2021;8:e2101407.

39. Jiang L, Jiang X, Zhang Y, et al. Multiobjective machine learning-assisted discovery of a novel cyan-green garnet: Ce phosphors with excellent thermal stability. ACS Appl Mater Interfaces 2022;14:15426-36.

40. Lin Y, Bettinelli M, Sharma SK, et al. Unraveling the impact of different thermal quenching routes on the luminescence efficiency of the Y3Al5O12:Ce3+ phosphor for white light emitting diodes. J Mater Chem C 2020;8:14015-27.

41. Hermus M, Brgoch J. Phosphors by design: approaches toward the development of advanced luminescent materials. Interface magazine 2015;24:55-9.

42. Kushner H J. A new method of locating the maximum of an arbi-trary multipeak curve in the presence of noise. J Basic Eng 1964;86:97-106.

43. Carr SF, Garnett R, Lo CS. Accelerating the search for global minima on potential energy surfaces using machine learning. J Chem Phys 2016;145:154106.

44. de Jong M, Chen W, Notestine R, et al. A statistical learning framework for materials science: application to elastic moduli of k-nary inorganic polycrystalline compounds. Sci Rep 2016;6:34256.

45. Cox DD, John S. A statistical method for global optimization. IEEE Int Conf Syst, Man, Cybern 1992:1241-46.

46. Cox DD, John S. A statistical method for global optimization. IEEE Int Conf Syst, Man, Cybern 1997:315-29.

47. Burger B, Maffettone PM, Gusev VV, et al. A mobile robotic chemist. Nature 2020;583:237-41.

48. Song Z, Liu Q. Structural indicator to characterize the crystal-field splitting of Ce 3+ in garnets. J Phys Chem C 2020;124:870-3.

49. Song Z, Zhou D, Liu Q. Tolerance factor and phase stability of the garnet structure. Acta Crystallogr C Struct Chem 2019;75:1353-8.

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