A brief review of data-driven ICME for intelligently discovering advanced structural metal materials: Insight into atomic and electronic building blocks
Source abstract
Abstract
This article presents a brief review of our case studies of data-driven Integrated Computational Materials Engineering (ICME) for intelligently discovering advanced structural metal materials, including light-weight materials (Ti, Mg, and Al alloys), refractory high-entropy alloys, and superalloys. The basic bonding in terms of topology and electronic structures is recommended to be considered as the building blocks/units constructing the microstructures of advanced materials. It is highlighted that the bonding charge density could not only provide an atomic and electronic insight into the physical nature of chemical bond of materials but also reveal the fundamental strengthening/embrittlement mechanisms and the local phase transformations of planar defects, paving a path in accelerating the development of advanced metal materials via interfacial engineering. Perspectives on the knowledge-based modeling/simulations, machine-learning knowledge base, platform, and next-generation workforce for sustainable ecosystem of ICME are highlighted, thus to call for more duty on the developments of advanced structural metal materials and enhancement of research productivity and collaboration.
Source: expertdata · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Machine Learning in Materials Science · X-ray Diffraction in Crystallography · Titanium Alloys Microstructure and Properties
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
References (100+)
Show source-provided references
1. 10.1016/j.scriptamat.2013.08.03210.1016/j.scriptamat.2013.08.032 ↗
2. 10.1557/JMR.2001.021810.1557/JMR.2001.0218 ↗
3. 10.1016/S1002-0071(12)60080-X10.1016/S1002-0071(12)60080-X ↗
4. 10.1103/PhysRevMaterials.2.12030110.1103/PhysRevMaterials.2.120301 ↗
5. 10.1016/j.intermet.2018.04.00910.1016/j.intermet.2018.04.009 ↗
6. Effects of microstructure on hydrogen-induced cracking in aluminum alloys10.1016/j.scriptamat.2011.04.008 ↗
7. 10.1016/j.actamat.2019.03.03010.1016/j.actamat.2019.03.030 ↗
8. 10.1557/jmr.2018.32310.1557/jmr.2018.323 ↗
9. 10.1016/j.matlet.2017.03.03510.1016/j.matlet.2017.03.035 ↗
10. 10.1016/j.actamat.2014.08.00510.1016/j.actamat.2014.08.005 ↗
11. 10.1088/1361-6528/aad67810.1088/1361-6528/aad678 ↗
12. 10.1088/0022-3719/20/32/00110.1088/0022-3719/20/32/001 ↗
13. 10.1038/ncomms1567910.1038/ncomms15679 ↗
14. 10.1080/21663831.2017.130897310.1080/21663831.2017.1308973 ↗
15. Giustino · 2014
16. 10.1007/s11837-015-1555-910.1007/s11837-015-1555-9 ↗
17. 10.1016/j.scriptamat.2016.04.00310.1016/j.scriptamat.2016.04.003 ↗
18. 10.1007/s10820-005-3173-210.1007/s10820-005-3173-2 ↗
19. 10.1016/j.actamat.2015.07.00110.1016/j.actamat.2015.07.001 ↗
20. 10.1002/9781119018377.ch810.1002/9781119018377.ch8 ↗
21. 10.1038/s41467-019-10921-710.1038/s41467-019-10921-7 ↗
22. 10.1016/j.actamat.2017.10.04110.1016/j.actamat.2017.10.041 ↗
23. 10.1038/s41524-019-0173-410.1038/s41524-019-0173-4 ↗
24. 10.1038/nmat349010.1038/nmat3490 ↗
25. 10.1007/s11837-009-0143-210.1007/s11837-009-0143-2 ↗
26. 10.1038/s41586-019-1617-110.1038/s41586-019-1617-1 ↗
27. 10.1080/21663831.2013.85808510.1080/21663831.2013.858085 ↗
28. 10.1038/ncomms1334110.1038/ncomms13341 ↗
29. 2013
30. 10.1103/PhysRevB.95.22410610.1103/PhysRevB.95.224106 ↗
31. 10.1038/s41524-017-0024-010.1038/s41524-017-0024-0 ↗
32. 10.1016/j.actamat.2012.10.02310.1016/j.actamat.2012.10.023 ↗
33. 10.1557/mrs.2013.26710.1557/mrs.2013.267 ↗
34. Frankel · 2017 · 23
35. 10.1007/s10853-019-03884-z10.1007/s10853-019-03884-z ↗
36. 10.1557/mrs.2018.20510.1557/mrs.2018.205 ↗
37. 10.1557/JMR.2002.038210.1557/JMR.2002.0382 ↗
38. 10.1103/PhysRevLett.65.35310.1103/PhysRevLett.65.353 ↗
39. Liu · March 2018
40. 10.1063/1.361447510.1063/1.3614475 ↗
41. 10.1007/978-3-319-68280-810.1007/978-3-319-68280-8 ↗
42. 10.1007/BF0264853710.1007/BF02648537 ↗
43. 10.1073/pnas.130637111010.1073/pnas.1306371110 ↗
44. 10.1557/jmr.2011.4110.1557/jmr.2011.41 ↗
45. 10.1002/adma.20120228610.1002/adma.201202286 ↗
46. 10.1016/j.commatsci.2019.03.02910.1016/j.commatsci.2019.03.029 ↗
47. Pollock · 2008
48. 10.1016/j.actamat.2010.12.01310.1016/j.actamat.2010.12.013 ↗
49. 10.1016/j.pmatsci.2013.10.00110.1016/j.pmatsci.2013.10.001 ↗
50. 10.1016/j.eng.2018.01.00210.1016/j.eng.2018.01.002 ↗
51. 10.1016/j.cplett.2012.09.02810.1016/j.cplett.2012.09.028 ↗
52. 10.1016/S1359-6454(03)00239-810.1016/S1359-6454(03)00239-8 ↗
53. 10.1126/science.122936910.1126/science.1229369 ↗
54. 10.1016/j.jmat.2017.08.00210.1016/j.jmat.2017.08.002 ↗
55. Structural stability of one-dimensional long-period structures in the TiAl3 compound
56. June 2011
57. 10.1038/nmat113610.1038/nmat1136 ↗
58. 10.1126/science.268.5218.173810.1126/science.268.5218.1738 ↗
59. 2016
60. 10.1038/s41467-019-12452-710.1038/s41467-019-12452-7 ↗
61. Aspuru-Guzik · 2018
62. 10.1080/21663831.2013.76592710.1080/21663831.2013.765927 ↗
63. 10.1016/j.matchemphys.2015.06.05110.1016/j.matchemphys.2015.06.051 ↗
64. 10.1016/j.commatsci.2018.11.00110.1016/j.commatsci.2018.11.001 ↗
65. 10.1126/science.111861610.1126/science.1118616 ↗
66. 10.1103/RevModPhys.89.04050110.1103/RevModPhys.89.040501 ↗
67. 10.1103/PhysRevLett.94.15550110.1103/PhysRevLett.94.155501 ↗
68. Criteria for predicting the formation of single-phase high-entropy alloys
69. 10.1126/science.112173810.1126/science.1121738 ↗
70. 10.1038/nmat470910.1038/nmat4709 ↗
71. 10.1016/j.jallcom.2013.10.06810.1016/j.jallcom.2013.10.068 ↗
72. 10.1016/j.commatsci.2019.03.00510.1016/j.commatsci.2019.03.005 ↗
73. 10.1007/s11434-014-0140-x10.1007/s11434-014-0140-x ↗
74. Perspective on materials genome (in Chinese)
75. 10.1007/s11669-017-0565-410.1007/s11669-017-0565-4 ↗
76. 10.1016/j.pmatsci.2005.10.00110.1016/j.pmatsci.2005.10.001 ↗
77. 10.1103/PhysRevB.69.14410910.1103/PhysRevB.69.144109 ↗
78. 2019
79. 10.1103/PhysRevLett.116.07550210.1103/PhysRevLett.116.075502 ↗
80. 10.3390/e1510450410.3390/e15104504 ↗
81. 10.1039/C4TA07062C10.1039/C4TA07062C ↗
82. 10.1126/science.118586610.1126/science.1185866 ↗
83. 10.1038/nmat430010.1038/nmat4300 ↗
84. 10.1126/science.108195710.1126/science.1081957 ↗
85. 10.1007/s10853-018-2140-810.1007/s10853-018-2140-8 ↗
86. 10.1016/j.commatsci.2018.05.02810.1016/j.commatsci.2018.05.028 ↗
87. 10.1016/j.actamat.2012.10.04310.1016/j.actamat.2012.10.043 ↗
88. 10.1103/PhysRevLett.91.13550310.1103/PhysRevLett.91.135503 ↗
89. October 2018
90. 10.1016/j.actamat.2014.04.03310.1016/j.actamat.2014.04.033 ↗
91. 10.1007/s11837-013-0755-410.1007/s11837-013-0755-4 ↗
92. 10.1103/PhysRevLett.87.15640110.1103/PhysRevLett.87.156401 ↗
93. 10.1038/s41565-017-0060-410.1038/s41565-017-0060-4 ↗
94. Chen · 2017 · 169
95. 10.1016/j.intermet.2014.07.00610.1016/j.intermet.2014.07.006 ↗
96. 10.1063/1.358578610.1063/1.3585786 ↗
97. 10.1038/s41529-018-0027-410.1038/s41529-018-0027-4 ↗
98. 10.1016/j.actamat.2014.09.00510.1016/j.actamat.2014.09.005 ↗
99. 10.1038/ncomms703510.1038/ncomms7035 ↗
100. 10.1007/s11837-011-0187-y10.1007/s11837-011-0187-y ↗