Please wait a minute...
Acta Metall Sin  2020, Vol. 56 Issue (10): 1313-1323    DOI: 10.11900/0412.1961.2020.00199
Current Issue | Archive | Adv Search |
Progress in Materials Genome Engineering in China
SU Yanjing, FU Huadong, BAI Yang, JIANG Xue, XIE Jianxin()
Beijing Advanced Innovation Center for Materials Genome Engineering, Institute for Advanced Materials and Technology, University of Science and Technology Beijing, Beijing 100083, China
Download:  HTML  PDF(1951KB) 
Export:  BibTeX | EndNote (RIS)      

Materials genome engineering (MGE) is a frontier technology in the field of material science and engineering, which is well capable to revolutionize the research and development (R&D) mode of new materials, greatly improve the R&D efficiency, shorten the R&D time, and reduce the cost. This paper reviews the progress of MGE in China from the aspects of the fundamental theory and methods, key technology and equipment, the R&D of new materials and related engineering application, talents training, formation and promotion of new concept of material genetic engineering. The paper also looks forward to the future development of MGE in China.

Key words:  materials genome engineering      high-throughput calculation      high-throughput experiment      big data technology     
Received:  05 June 2020     
ZTFLH:  T-1  
Corresponding Authors:  XIE Jianxin     E-mail:

Cite this article: 

SU Yanjing, FU Huadong, BAI Yang, JIANG Xue, XIE Jianxin. Progress in Materials Genome Engineering in China. Acta Metall Sin, 2020, 56(10): 1313-1323.

URL:     OR

Fig.1  Schematic diagram for the research and development model revolutionized by material genome engineering (MGE)
Fig.2  New high-temperature bulk metallic glass (BMG) Ir-Ni-Ta-(B) discovered by MGE method (Tx—crystallization temperature, Tg—glass transition temperature)[5]
(a) combinatorial fabrication of new high-temperature BMGs
(b) high-throughput characterization of BMGs
(c) summary of the supercooled liquid region vs the glass transition temperature of BMGs
(d) strength vs temperature of high-temperature BMGs as well as other alloys
Fig.3  High-throughput preparation and characterization system of laser molecular beam epitaxy-scanning tunneling microscopy (STM)[26]
(a) experimental equipment for high-throughput preparation and characterization
(b) schematic of high-throughput preparation for combinatorial film chip
(c) in-situ STM photograph of Fe-based superconducting film prepared by high-throughput technology
(d) micro-area resistance of combinatorial film chip with gradient thickness (28 nm→280 nm, T—temperature)
(e) XRD spectra of combinatorial film chip with gradient deposition temperature Ts (350 ℃→600 ℃)
(f) micro-area temperature dependence of resistance R(T) for combinatorial film chip with gradient superconducting transition temperature
Fig.4  Database technology based on MGE concept
(a) high-throughput first-principles computational driving engine (MatCloud) and workflow[32]
(b) online computation platform for materials data mining (OCPMDM) and corresponding process[33]
(c) database technical architecture based on MGE concept
Fig.5  New high-strength and high-electrical conductivity copper alloys discovered by the machine learning design system (MLDS) (C2P: prediction model from composition to performance; P2C: prediction model from performance to composition)[39](a) machine learning strategy for performance-oriented alloys design(b) electrical conductivity vs ultimate tensile strength of the new copper alloys discovered by the machine learning method
[1] White House Office of Science and Technology Policy. Materials genome initiative for global competitiveness [EB/OL]. (2011-06).
[2] National Science and Technology Council, Committee on Technology and Subcommittee on the MGI Initiative. Materials Genome Initiative—Strategic Plan [EB/OL]. (2014).
[3] Scott T, Walsh A, Anderson B, et al. Economic analysis of national needs for technology infrastructure to support the materials genome initiative [EB/OL]. (2018-04).
[4] Minerals The, Metals & Materials Society. Creating the next-generation materials genome initiative workforce [EB/OL]. (2019).
[5] Li M X, Zhao S F, Lu Z, et al. High-temperature bulk metallic glasses developed by combinatorial methods [J]. Nature, 2019, 569: 99
doi: 10.1038/s41586-019-1145-z pmid: 31043727
[6] Lei Z F, Liu X J, Wu Y, et al. Enhanced strength and ductility in a high-entropy alloy via ordered oxygen complexes [J]. Nature, 2018, 563: 546
doi: 10.1038/s41586-018-0685-y pmid: 30429610
[7] Liu B Y, Liu F, Yang N, et al. Large plasticity in magnesium mediated by pyramidal dislocations [J]. Science, 2019, 365: 73
doi: 10.1126/science.aaw2843 pmid: 31273119
[8] Zhou X L, Feng Z Q, Zhu L L, et al. High-pressure strengthening in ultrafine-grained metals [J]. Nature, 2020, 579: 67
pmid: 32094661
[9] Zhang T T, Jiang Y, Song Z D, et al. Catalogue of topological electronic materials [J]. Nature, 2019, 566: 475
pmid: 30814713
[10] Tang F, Hoi C P, Vishwanath A, et al. Comprehensive search for topological materials using symmetry indicators [J]. Nature, 2019, 566: 486
doi: 10.1038/s41586-019-0937-5 pmid: 30814709
[11] Luo J J, Wang X M, Li S R, et al. Efficient and stable emission of warm-white light from lead-free halide double perovskites [J]. Nature, 2018, 563: 541
pmid: 30405238
[12] Jiang Q, Zhao Y, Zhang X W, et al. Surface passivation of perovskite film for efficient solar cells [J]. Nat. Photonics, 2019, 13: 460
doi: 10.1038/s41566-019-0398-2
[13] Liu T C, Lin L P, Bi X X, et al. In situ quantification of interphasial chemistry in Li-ion battery [J]. Nat. Nanotechnol., 2019, 14: 50
doi: 10.1038/s41565-018-0284-y pmid: 30420761
[14] Liu T C, Dai A, Lu J, et al. Correlation between manganese dissolution and dynamic phase stability in spinel-based lithium-ion battery [J]. Nat. Commun., 2019, 10: 4721
doi: 10.1038/s41467-019-12626-3 pmid: 31624258
[15] Shen Z H, Wang J J, Jiang J Y, et al. Phase-field modeling and machine learning of electric-thermal-mechanical breakdown of polymer-based dielectrics [J]. Nat. Commun., 2019, 10: 1843
doi: 10.1038/s41467-019-09874-8 pmid: 31015446
[16] Jiang J, Sun X, Chen X C, et al. Carrier lifetime enhancement in halide perovskite via remote epitaxy [J]. Nat. Commun., 2019, 10: 4145
doi: 10.1038/s41467-019-12056-1 pmid: 31515482
[17] Zhang K, Zhou Y, Xiao C, et al. Application of hydroxyapatite nanoparticles in tumor-associated bone segmental defect [J]. Sci. Adv., 2019, 5: eaax6946
doi: 10.1126/sciadv.aaw9485 pmid: 32064310
[18] Feng H L, Wang C Y. Electronic structure and multi-scale behaviour for the dislocation-doping complex in the gamma phase of nickel-base superalloys [J]. RSC Adv., 2017, 7: 19124
doi: 10.1039/C7RA00876G
[19] Wen M R, Wang C Y. Transition-metal alloying of γ'-Ni3Al: Effects on the ideal uniaxial compressive strength from first-principles calculations [J]. Phys. Rev., 2018, 97B: 024101
[20] Miao N H, Xu B, Zhu L G, et al. 2D intrinsic ferromagnets from van der Waals antiferromagnets [J]. J. Am. Chem. Soc., 2018, 140: 2417
doi: 10.1021/jacs.7b12976 pmid: 29400056
[21] Peng Q, Zhou J, Chen J T, et al. Cu single atoms on Ti2CO2 as a highly efficient oxygen reduction catalyst in a proton exchange membrane fuel cell [J]. J. Mater. Chem., 2019, 7A: 26062
[22] Li J Y, Zhang Y, Li J X, et al. A device for high throughput preparation of multicomponent gradient metal materials [P].ZL 201610267117.5, 2018
(李静媛, 张 源, 李建兴等. 一种高通量制备多组分梯度金属材料的装置 [P]. 中国专利, 201610267117.5, 2018)
[23] Wu H Y, Li J, Liu F, et al. A high-throughput methodology search for the optimum cooling rate in an advanced polycrystalline nickel base superalloy [J]. Mater. Des., 2017, 128: 176
doi: 10.1016/j.matdes.2017.05.025
[24] Wang Z C, Tavabi A H, Jin L, et al. Atomic scale imaging of magnetic circular dichroism by achromatic electron microscopy [J]. Nat. Mater., 2018, 17: 221
doi: 10.1038/s41563-017-0010-4 pmid: 29403052
[25] Chen K, Huang R Q, Li Y, et al. Rafting-enabled recovery avoids recrystallization in 3D-printing-repaired single-crystal superalloys [J]. Adv. Mater., 2020, 32: 1907164
doi: 10.1002/adma.v32.12
[26] He G, Wei Z X, Feng Z P, et al. Combinatorial laser molecular beam epitaxy system integrated with specialized low-temperature scanning tunneling microscopy [J]. Rev. Sci. Instrum., 2020, 91: 013904
doi: 10.1063/1.5119686 pmid: 32012528
[27] Yuan J, Stanev V, Gao C, et al. Recent advances in high-throughput superconductivity research [J]. Supercond. Sci. Technol., 2019, 32: 123001
doi: 10.1088/1361-6668/ab51b1
[28] Song Z M, Hong B, Zhu X D, et al. CdS/Au/Ti/Pb(Mg1/3Nb2/3)0.7-Ti0.3O3 photocatalysts and biphotoelectrodes with ferroelectric polarization in single domain for efficient water splitting [J]. Appl. Catal., 2018, 238B: 248
[29] Jiang L, Ye X X, Wang D J, et al. Synchrotron radiation-based materials characterization techniques shed light on molten salt reactor alloys [J]. Nucl. Sci. Tech., 2020, 31: 6
doi: 10.1007/s41365-019-0719-7
[30] Su Y Q, Yao X F, Wang S, et al. Simultaneous determination of virtual fields and material parameters for thermo-mechanical coupling deformation in orthotropic materials [J]. Mech. Mater., 2018, 124: 33
doi: 10.1016/j.mechmat.2018.05.008
[31] Fu C, Chen Y D, Li L F, et al. Evaluation of service conditions of high pressure turbine blades made of DS Ni-base superalloy by artificial neural networks [J]. Mater. Today Commun., 2020, 22: 100838
[32] Yang X Y, Wang Z G, Zhao X S, et al. MatCloud: A high-throughput computational infrastructure for integrated management of materials simulation, data and resources [J]. Comput. Mater. Sci., 2018, 146: 319
doi: 10.1016/j.commatsci.2018.01.039
[33] Zhang Q, Chang D P, Zhai X Y, et al. OCPMDM: Online computation platform for materials data mining [J]. Chemom. Intell. Lab. Syst., 2018, 177: 26
doi: 10.1016/j.chemolab.2018.04.004
[34] Wang Y, Liu Y J, Song S W, et al. Accelerating the discovery of insensitive high-energy-density materials by a materials genome approach [J]. Nat. Commun., 2018, 9: 2444
pmid: 29934564
[35] Lu S H, Zhou Q H, Ouyang Y X, et al. Accelerated discovery of stable lead-free hybrid organic-inorganic perovskites via machine learning [J]. Nat. Commun., 2018, 9: 3405
doi: 10.1038/s41467-018-05761-w pmid: 30143621
[36] Wen C, Zhang Y, Wang C X, et al. Machine learning assisted design of high entropy alloys with desired property [J]. Acta Mater., 2019, 170: 109
doi: 10.1016/j.actamat.2019.03.010
[37] Zhang Y, Wen C, Wang C X, et al. Phase prediction in high entropy alloys with a rational selection of materials descriptors and machine learning models [J]. Acta Mater., 2020, 185: 528
doi: 10.1016/j.actamat.2019.11.067
[38] Liu P, Huang H Y, Antonov S, et al. Machine learning assisted design of γ′-strengthened Co-base superalloys with multi- performance optimization [J]. npj Comput. Mater., 2020, 6: 62
doi: 10.1038/s41524-020-0334-5
[39] Wang C S, Fu H D, Jiang L, et al. A property-oriented design strategy for high performance copper alloys via machine learning [J]. npj Comput. Mater., 2019, 5: 87
doi: 10.1038/s41524-019-0227-7
[40] Shanghai Jiaotong University, Sichuan University, Beijing University of Science and Technology, et al. T/CSTM 00120-2019 General rule for materials genome engineering data [S]. Beijing: Metallurgical Industry Press, 2019
(上海交通大学, 四川大学, 北京科技大学, 等. T/CSTM 00120-2019 材料基因工程数据通则 [S].北京: 冶金工业出版社, 2019)
[41] Wang H, Xiang X D, Zhang L T. Data+AI: The core of materials genomic engineering [J]. Sci. Technol. Rev., 2018, 36(14): 15
(汪 洪, 项晓东, 张澜庭. 数据+人工智能是材料基因工程的核心 [J]. 科技导报, 2018, 36(14): 15)
[42] Wang Z D, Cichocka M O, Luo Y, et al. Controllable direct-syntheses of delaminated MWW-type zeolites [J]. Chin. J. Catal., 2020, 41: 1062
doi: 10.1016/S1872-2067(20)63545-8
[43] Yang W M, Wang Z D. Development of zeolite catalysts for production of ethylbenzene [J]. Hydrocarbon Process., 2019, 3: 47
[44] Luo Y, Smeets S, Peng F, et al. Synthesis and structure determination of large-pore zeolite SCM-14 [J]. Chem. Eur. J., 2017, 23: 16829
doi: 10.1002/chem.201703361 pmid: 28967679
[45] Luo Y, Smeets S, Wang Z D, et al. Synthesis and structure determination of SCM-15: A 3D large pore zeolite with interconnected straight 12×12×10-ring channels [J]. Chem. Eur. J., 2019, 25: 2184
doi: 10.1002/chem.201805187 pmid: 30521132
[46] Zhu J M, Wang D, Gao Y P, et al. Linear-superelastic metals by controlled strain release via nanoscale concentration-gradient engineering [J]. Mater. Today, 2020, 33: 17
doi: 10.1016/j.mattod.2019.10.003
[47] Wang H, Bao Q L, Zhou G, et al. Dynamic recrystallization initiated by direct grain reorientation at high-angle grain boundary in α-titanium [J]. J. Mater. Res., 2019, 34: 1608
doi: 10.1557/jmr.2019.125
[48] Hua K, Zhang Y D, Gan W M, et al. Hot deformation behavior originated from dislocation activity and β to α phase transformation in a metastable β titanium alloy [J]. Int. J. Plast., 2019, 119: 200
doi: 10.1016/j.ijplas.2019.03.011
[49] Zhang X X, Zheng Z, Gao Y, et al. Progress in high throughput fabrication and characterization of metal matrix composites [J]. Acta Metall. Sin., 2019, 55: 109
doi: 10.11900/0412.1961.2018.00307
(张学习, 郑 忠, 高 莹等. 金属基复合材料高通量制备及表征技术研究进展 [J]. 金属学报, 2019, 55: 109)
doi: 10.11900/0412.1961.2018.00307
[50] Chen J, Lan H, Cao Y G, et al. Application of composite phosphor ceramics by tape-casting in white light-emitting diodes [J]. J. Alloys Compd., 2017, 709: 267
doi: 10.1016/j.jallcom.2017.03.034
[51] Yang K C, Wang J, Yao Q R, et al. Phase diagrams of permanent magnet alloys: Binary rare earth alloy systems [J]. J. Rare Earths, 2019, 37: 1040
doi: 10.1016/j.jre.2019.02.003
[52] Wang J F, Zhou H B, Zhu S J, et al. Microstructure, mechanical properties and deformation mechanisms of an as-cast Mg-Zn-Y-Nd alloy for stent applications [J]. J. Mater. Sci. Technol., 2019, 35: 1211
doi: 10.1016/j.jmst.2019.01.007
[53] Yan B J, Cheng L, Li B Q, et al. Bi-directional prediction of structural characteristics and effective thermal conductivities of composite fuels through learning from finite element simulation results [J]. Mater. Des., 2020, 189: 108483
doi: 10.1016/j.matdes.2020.108483
[1] ZHANG Guoqing,ZHANG Yiwen,ZHENG Liang,PENG Zichao. Research Progress in Powder Metallurgy Superalloys and Manufacturing Technologies for Aero-Engine Application[J]. 金属学报, 2019, 55(9): 1133-1144.
No Suggested Reading articles found!