The CALYPSO methodology for structure prediction

doi:10.1088/1674-1056/ab4174

中国物理B ›› 2019, Vol. 28 ›› Issue (10): 106105-106105.doi: 10.1088/1674-1056/ab4174

所属专题： TOPICAL REVIEW — CALYPSO structure prediction methodology and its applications to materials discovery

• TOPICAL REVIEW—CALYPSO structure prediction methodology and its applications to materials discovery • 上一篇下一篇

The CALYPSO methodology for structure prediction

Qunchao Tong(童群超), Jian Lv(吕健), Pengyue Gao(高朋越), Yanchao Wang(王彦超)

Innovation Center of Computational Physics Methods and Software, State Key Laboratory of Superhard Materials, College of Physics, Jilin University, Changchun 130012, China

收稿日期:2019-07-30 修回日期:2019-08-28 出版日期:2019-10-05 发布日期:2019-10-05
通讯作者: Jian Lv, Yanchao Wang E-mail:lvjian@calypso.cn;wyc@calypso.cn
基金资助:
Project supported by the National Natural Science Foundation of China (Grant Nos. 11534003 and 11604117), the National Key Research and Development Program of China (Grant No. 2016YFB0201201), the Program for JLU Science and Technology Innovative Research Team (JLUSTIRT) of China, and the Science Challenge Project of China (Grant No. TZ2016001).

The CALYPSO methodology for structure prediction

Qunchao Tong(童群超), Jian Lv(吕健), Pengyue Gao(高朋越), Yanchao Wang(王彦超)

Innovation Center of Computational Physics Methods and Software, State Key Laboratory of Superhard Materials, College of Physics, Jilin University, Changchun 130012, China

Received:2019-07-30 Revised:2019-08-28 Online:2019-10-05 Published:2019-10-05
Contact: Jian Lv, Yanchao Wang E-mail:lvjian@calypso.cn;wyc@calypso.cn
Supported by:
Project supported by the National Natural Science Foundation of China (Grant Nos. 11534003 and 11604117), the National Key Research and Development Program of China (Grant No. 2016YFB0201201), the Program for JLU Science and Technology Innovative Research Team (JLUSTIRT) of China, and the Science Challenge Project of China (Grant No. TZ2016001).

摘要/Abstract

摘要： Structure prediction methods have been widely used as a state-of-the-art tool for structure searches and materials discovery, leading to many theory-driven breakthroughs on discoveries of new materials. These methods generally involve the exploration of the potential energy surfaces of materials through various structure sampling techniques and optimization algorithms in conjunction with quantum mechanical calculations. By taking advantage of the general feature of materials potential energy surface and swarm-intelligence-based global optimization algorithms, we have developed the CALYPSO method for structure prediction, which has been widely used in fields as diverse as computational physics, chemistry, and materials science. In this review, we provide the basic theory of the CALYPSO method, placing particular emphasis on the principles of its various structure dealing methods. We also survey the current challenges faced by structure prediction methods and include an outlook on the future developments of CALYPSO in the conclusions.

关键词: structure prediction, CALYPSO method, crystal structure, potential energy surface

Abstract: Structure prediction methods have been widely used as a state-of-the-art tool for structure searches and materials discovery, leading to many theory-driven breakthroughs on discoveries of new materials. These methods generally involve the exploration of the potential energy surfaces of materials through various structure sampling techniques and optimization algorithms in conjunction with quantum mechanical calculations. By taking advantage of the general feature of materials potential energy surface and swarm-intelligence-based global optimization algorithms, we have developed the CALYPSO method for structure prediction, which has been widely used in fields as diverse as computational physics, chemistry, and materials science. In this review, we provide the basic theory of the CALYPSO method, placing particular emphasis on the principles of its various structure dealing methods. We also survey the current challenges faced by structure prediction methods and include an outlook on the future developments of CALYPSO in the conclusions.

Key words: structure prediction, CALYPSO method, crystal structure, potential energy surface

中图分类号: (Theory of crystal structure, crystal symmetry; calculations and modeling)

61.50.Ah

31.50.-x (Potential energy surfaces) 02.60.Pn (Numerical optimization)

童群超, 吕健, 高朋越, 王彦超. The CALYPSO methodology for structure prediction[J]. 中国物理B, 2019, 28(10): 106105-106105.

Qunchao Tong(童群超), Jian Lv(吕健), Pengyue Gao(高朋越), Yanchao Wang(王彦超). The CALYPSO methodology for structure prediction[J]. Chin. Phys. B, 2019, 28(10): 106105-106105.

参考文献 75

[33]	Yang L M, Bačić V, Popov I A, Boldyrev A I, Heine T, Frauenheim T and Ganz E 2015 J. Am. Chem. Soc. 137 2757 doi: 10.1021/ja513209c
[1]	Wang L S 2016 Int. Rev. Phys. Chem. 35 69 doi: 10.1080/0144235X.2016.1147816
[34]	Woodley S M and Catlow R 2008 Nat. Mater. 7 937 doi: 10.1038/nmat2321
[35]	Zhao J, Shi R, Sai L, Huang X and Su Y 2016 Mol. Simul. 42 809 doi: 10.1080/08927022.2015.1121386
[36]	Wang H, Wang Y, Lv J, Li Q, Zhang L and Ma Y 2016 Comput. Mater. Sci. 112 406 doi: 10.1016/j.commatsci.2015.09.037
[2]	Oger E, Crawford N R M, Kelting R, Weis P, Kappes M M and Ahlrichs R 2007 Angew. Chem. Int. Ed. 46 8503
[37]	Wang Y, Lv J, Zhu L, Lu S, Yin K, Li Q, Wang H, Zhang L and Ma Y 2015 J. Phys. Condens. Matter 27 203203 doi: 10.1088/0953-8984/27/20/203203
[3]	Zhang L, Wang Y, Lv J and Ma Y 2017 Nat. Rev. Mater. 2 17005 doi: 10.1038/natrevmats.2017.5
[38]	Stillinger F H 1999 Phys. Rev. E 59 48 doi: 10.1103/PhysRevE.59.48
[4]	Maddox J 1988 Nature 335 201 doi: 10.1038/335201a0
[39]	Tsai C J and Jordan K D 1993 J. Phys. Chem. 97 11227 doi: 10.1021/j100145a019
[40]	Doye J P K and Wales D J 1995 J. Chem. Phys. 102 9659 doi: 10.1063/1.468785
[5]	Wang Y and Ma Y 2014 J. Chem. Phys. 140 040901 doi: 10.1063/1.4861966
[41]	Wales D 2004 Energy Landscapes: Applications to Clusters, Biomolecules and Glasses (Cambridge: Cambridge University Press)
[6]	Oganov A R, Pickard C J, Zhu Q and Needs R J 2019 Nat. Rev. Mater. 4 331 doi: 10.1038/s41578-019-0101-8
[42]	Jensen F 2007 Introduction to Computational Chemistry (Wiley)
[7]	Kirkpatrick S, Gelatt C D and Vecchi M P 1983 Science 220 671 doi: 10.1126/science.220.4598.671
[43]	Roy S, Goedecker S and Hellmann V 2008 Phys. Rev. E 77 56707 doi: 10.1103/PhysRevE.77.056707
[8]	Wales D J and Doye J P K 1997 J. Phys. Chem. A 101 5111 doi: 10.1021/jp970984n
[9]	Goedecker S 2004 J. Chem. Phys. 120 9911 doi: 10.1063/1.1724816
[44]	Wales D J 1998 Chem. Phys. Lett. 285 330 doi: 10.1016/S0009-2614(98)00044-X
[10]	Martoňák R, Laio A and Parrinello M 2003 Phys. Rev. Lett. 90 075503 doi: 10.1103/PhysRevLett.90.075503
[45]	Wolpert D H and Macready W G 1997 IEEE Trans. Evol. Comput. 1 67 doi: 10.1109/4235.585893
[11]	Pickard C J and Needs R J 2011 J. Phys. Condens. Matter 23 053201 doi: 10.1088/0953-8984/23/5/053201
[46]	Zhang M, Liu H, Li Q, Gao B, Wang Y, Li H, Chen C and Ma Y 2015 Phys. Rev. Lett. 114 15502 doi: 10.1103/PhysRevLett.114.015502
[12]	Oganov A R and Glass C W 2006 J. Chem. Phys. 124 244704 doi: 10.1063/1.2210932
[47]	Chen F, Ju M, Kuang X and Yeung Y 2018 Inorg. Chem. 57 4563 doi: 10.1021/acs.inorgchem.8b00316
[13]	Lonie D C and Zurek E 2011 Comput. Phys. Commun. 182 372 doi: 10.1016/j.cpc.2010.07.048
[48]	Xie T and Grossman J C 2018 Phys. Rev. Lett. 120 145301 doi: 10.1103/PhysRevLett.120.145301
[14]	Kolmogorov A N, Shah S, Margine E R, Bialon A F, Hammerschmidt T and Drautz R 2010 Phys. Rev. Lett. 105 217003 doi: 10.1103/PhysRevLett.105.217003
[49]	Lv J, Wang Y, Zhu L and Ma Y 2012 J. Chem. Phys. 137 084104 doi: 10.1063/1.4746757
[15]	Trimarchi G and Zunger A 2007 Phys. Rev. B 75 104113 doi: 10.1103/PhysRevB.75.104113
[50]	Oganov A R and Valle M 2009 J. Chem. Phys. 130 104504 doi: 10.1063/1.3079326
[16]	Bahmann S and Kortus J 2013 Comput. Phys. Commun. 184 1618 doi: 10.1016/j.cpc.2013.02.007
[51]	Zhu L, Amsler M, Fuhrer T, Schaefer B, Faraji S, Rostami S, Ghasemi S A, Sadeghi A, Grauzinyte M, Wolverton C and Goedecker S 2016 J. Chem. Phys. 144 034203 doi: 10.1063/1.4940026
[17]	Bi W, Meng Y, Kumar R S, Cornelius A L, Tipton W W, Hennig R G, Zhang Y, Chen C and Schilling J S 2011 Phys. Rev. B 83 104106 doi: 10.1103/PhysRevB.83.104106
[52]	Sadeghi A, Ghasemi S A, Schaefer B, Mohr S, Lill M A and Goedecker S 2013 J. Chem. Phys. 139 184118 doi: 10.1063/1.4828704
[18]	Wang Y, Lv J, Zhu L and Ma Y 2010 Phys. Rev. B 82 094116 doi: 10.1103/PhysRevB.82.094116
[53]	Behler J 2011 J. Chem. Phys. 134 074106 doi: 10.1063/1.3553717
[19]	Wang Y, Lv J, Zhu L and Ma Y 2012 Comput. Phys. Commun. 183 2063 doi: 10.1016/j.cpc.2012.05.008
[54]	Bartók A P, Kondor R and Csányi G 2013 Phys. Rev. B 87 184115 doi: 10.1103/PhysRevB.87.184115
[20]	Li Y, Wang L, Liu H, Zhang Y, Hao J, Pickard C J, Nelson J R, Needs R J, Li W, Huang Y, Errea I, Calandra M, Mauri F and Ma Y 2016 Phys. Rev. B 93 020103
[55]	Todeschini R and Consonni V 2009 Mol. Descriptors For Chemoinformatics: Volume I: Alphabetical Listing/volume Ⅱ: Appendices References Vol 41 (John Wiley & Sons) doi: Descriptors For Chemoinformatics: Volume I: Alphabetical Listingvolume a??: Appendices References Vol 41 ???John Wiley\|\|
[21]	Li Y, Hao J, Liu H, Lu S and Tse J S 2015 Phys. Rev. Lett. 115 105502 doi: 10.1103/PhysRevLett.115.105502
[56]	Steinhardt P J, Nelson D R and Ronchetti M 1983 Phys. Rev. B 28 784 doi: 10.1103/PhysRevB.28.784
[22]	Li Y, Hao J, Liu H, Tse J S, Wang Y and Ma Y 2015 Sci. Rep. 5 9948 doi: 10.1038/srep09948
[57]	Kennedy J and Eberhart R 1995 Proc. ICNN'95-Int. Conf. Neural Netw. 4 1942 doi: ICNN
[23]	Li Y, Wang Y, Pickard C J, Needs R J, Wang Y and Ma Y 2015 Phys. Rev. Lett. 114 125501 doi: 10.1103/PhysRevLett.114.125501
[58]	Eberhart R and Kennedy J 1995 Proc. Sixth Int. Symp. Micro Mach. Hum. Sci. p. 39
[24]	Li Y, Feng X, Liu H, Hao J, Redfern S A T, Lei W, Liu D and Ma Y 2018 Nat. Commun. 9 722 doi: 10.1038/s41467-018-03200-4
[59]	Wang Y, Liu H, Lv J, Zhu L, Wang H and Ma Y 2011 Nat. Commun. 2 563 doi: 10.1038/ncomms1566
[25]	Li Y, Hao J, Liu H, Li Y and Ma Y 2014 J. Chem. Phys. 140 174712 doi: 10.1063/1.4874158
[60]	Wang Y, Miao M, Lv J, Zhu L, Yin K, Liu H and Ma Y 2012 J. Chem. Phys. 137 224108 doi: 10.1063/1.4769731
[26]	Duan D, Liu Y, Tian F, Li D, Huang X, Zhao Z, Yu H, Liu B, Tian W and Cui T 2015 Sci. Rep. 4 6968 doi: 10.1038/srep06968
[61]	Lu S, Wang Y, Liu H, Miao M and Ma Y 2014 Nat. Commun. 5 3666 doi: 10.1038/ncomms4666
[27]	Peng F, Sun Y, Pickard C J, Needs R J, Wu Q and Ma Y 2017 Phys. Rev. Lett. 119 107001 doi: 10.1103/PhysRevLett.119.107001
[62]	Gao B, Gao P, Lu S, Lv J, Wang Y and Ma Y 2019 Sci. Bull. 64 301 doi: 10.1016/j.scib.2019.02.009
[28]	Liu H, Naumov I I, Hoffmann R, Ashcroft N W and Hemley R J 2017 Proc. Natl. Acad. Sci. 114 6990 doi: 10.1073/pnas.1704505114
[63]	Gao B, Shao X, Lv J, Wang Y and Ma Y 2015 J. Phys. Chem. C 119 20111 doi: 10.1021/acs.jpcc.5b05035
[29]	Drozdov A P, Eremets M I, Troyan I A, Ksenofontov V and Shylin S I 2015 Nature 525 73 doi: 10.1038/nature14964
[64]	Gao P, Wang S, Lv J, Wang Y and Ma Y 2017 RSC Adv. 7 39869 doi: 10.1039/C7RA07461A
[30]	Ahart M, Somayazulu M, Meng Y, Struzhkin V V, Baldini M, Mishra A K, Geballe Z M and Hemley R J 2019 Phys. Rev. Lett. 122 27001 doi: 10.1103/PhysRevLett.122.027001
[65]	Zhang X, Wang Y, Lv J, Zhu C, Li Q, Zhang M, Li Q and Ma Y 2013 J. Chem. Phys. 138 114101 doi: 10.1063/1.4794424
[31]	Drozdov A P, Kong P P, Minkov V S, Besedin S P, Kuzovnikov M A, Mozaffari S, Balicas L, Balakirev F F, Graf D E, Prakapenka V B, Greenberg E, Knyazev D A, Tkacz M and Eremets M I 2019 Nature 569 528 doi: 10.1038/s41586-019-1201-8
[66]	Gao P, Tong Q, Lv J, Wang Y and Ma Y 2017 Comput. Phys. Commun. 213 40 doi: 10.1016/j.cpc.2016.11.007
[32]	Zhang W, Oganov A R, Goncharov A F, Zhu Q, Boulfelfel S E, Lyakhov A O, Stavrou E, Somayazulu M, Prakapenka V B and Konôpková Z 2013 Science 342 1502 doi: 10.1126/science.1244989
[67]	Zhang Y, Wang H, Wang Y, Zhang L and Ma Y 2017 Phys. Rev. X 7 011017
[33]	Yang L M, Bačić V, Popov I A, Boldyrev A I, Heine T, Frauenheim T and Ganz E 2015 J. Am. Chem. Soc. 137 2757 doi: 10.1021/ja513209c
[68]	Su C, Lv J, Li Q, Wang H, Zhang L, Wang Y and Ma Y 2017 J. Phys. Condens. Matter 29 165901 doi: 10.1088/1361-648X/aa63cd
[34]	Woodley S M and Catlow R 2008 Nat. Mater. 7 937 doi: 10.1038/nmat2321
[69]	Behler J 2016 J. Chem. Phys. 145 170901 doi: 10.1063/1.4966192
[35]	Zhao J, Shi R, Sai L, Huang X and Su Y 2016 Mol. Simul. 42 809 doi: 10.1080/08927022.2015.1121386
[70]	Jacobsen T L, Jorgensen M S and Hammer B 2018 Phys. Rev. Lett. 120 026102 doi: 10.1103/PhysRevLett.120.026102
[36]	Wang H, Wang Y, Lv J, Li Q, Zhang L and Ma Y 2016 Comput. Mater. Sci. 112 406 doi: 10.1016/j.commatsci.2015.09.037
[71]	Deringer V L, Csányi G and Proserpio D M 2017 ChemPhysChem. 18 873 doi: 10.1002/cphc.201700151
[37]	Wang Y, Lv J, Zhu L, Lu S, Yin K, Li Q, Wang H, Zhang L and Ma Y 2015 J. Phys. Condens. Matter 27 203203 doi: 10.1088/0953-8984/27/20/203203
[72]	Deringer V L, Pickard C J and Csányi G 2018 Phys. Rev. Lett. 120 156001 doi: 10.1103/PhysRevLett.120.156001
[38]	Stillinger F H 1999 Phys. Rev. E 59 48 doi: 10.1103/PhysRevE.59.48
[73]	Bartók A P, Payne M C, Kondor R and Csányi G 2010 Phys. Rev. Lett. 104 136403 doi: 10.1103/PhysRevLett.104.136403
[39]	Tsai C J and Jordan K D 1993 J. Phys. Chem. 97 11227 doi: 10.1021/j100145a019
[74]	Tong Q, Xue L, Lv J, Wang Y and Ma Y 2018 Faraday Discuss. 211 31 doi: 10.1039/C8FD00055G
[75]	Reilly A M, Cooper R I, Adjiman C S, et al. 2016 Acta Crystallogr. Sect. B 72 439 doi: 10.1107/S2052520616007447
[40]	Doye J P K and Wales D J 1995 J. Chem. Phys. 102 9659 doi: 10.1063/1.468785
[41]	Wales D 2004 Energy Landscapes: Applications to Clusters, Biomolecules and Glasses (Cambridge: Cambridge University Press)
[42]	Jensen F 2007 Introduction to Computational Chemistry (Wiley)
[43]	Roy S, Goedecker S and Hellmann V 2008 Phys. Rev. E 77 56707 doi: 10.1103/PhysRevE.77.056707
[44]	Wales D J 1998 Chem. Phys. Lett. 285 330 doi: 10.1016/S0009-2614(98)00044-X
[45]	Wolpert D H and Macready W G 1997 IEEE Trans. Evol. Comput. 1 67 doi: 10.1109/4235.585893
[46]	Zhang M, Liu H, Li Q, Gao B, Wang Y, Li H, Chen C and Ma Y 2015 Phys. Rev. Lett. 114 15502 doi: 10.1103/PhysRevLett.114.015502
[47]	Chen F, Ju M, Kuang X and Yeung Y 2018 Inorg. Chem. 57 4563 doi: 10.1021/acs.inorgchem.8b00316
[48]	Xie T and Grossman J C 2018 Phys. Rev. Lett. 120 145301 doi: 10.1103/PhysRevLett.120.145301
[49]	Lv J, Wang Y, Zhu L and Ma Y 2012 J. Chem. Phys. 137 084104 doi: 10.1063/1.4746757
[50]	Oganov A R and Valle M 2009 J. Chem. Phys. 130 104504 doi: 10.1063/1.3079326
[51]	Zhu L, Amsler M, Fuhrer T, Schaefer B, Faraji S, Rostami S, Ghasemi S A, Sadeghi A, Grauzinyte M, Wolverton C and Goedecker S 2016 J. Chem. Phys. 144 034203 doi: 10.1063/1.4940026
[52]	Sadeghi A, Ghasemi S A, Schaefer B, Mohr S, Lill M A and Goedecker S 2013 J. Chem. Phys. 139 184118 doi: 10.1063/1.4828704
[53]	Behler J 2011 J. Chem. Phys. 134 074106 doi: 10.1063/1.3553717
[54]	Bartók A P, Kondor R and Csányi G 2013 Phys. Rev. B 87 184115 doi: 10.1103/PhysRevB.87.184115
[55]	Todeschini R and Consonni V 2009 Mol. Descriptors For Chemoinformatics: Volume I: Alphabetical Listing/volume Ⅱ: Appendices References Vol 41 (John Wiley & Sons) doi: Descriptors For Chemoinformatics: Volume I: Alphabetical Listingvolume a??: Appendices References Vol 41 ???John Wiley\|\|
[56]	Steinhardt P J, Nelson D R and Ronchetti M 1983 Phys. Rev. B 28 784 doi: 10.1103/PhysRevB.28.784
[57]	Kennedy J and Eberhart R 1995 Proc. ICNN'95-Int. Conf. Neural Netw. 4 1942 doi: ICNN
[58]	Eberhart R and Kennedy J 1995 Proc. Sixth Int. Symp. Micro Mach. Hum. Sci. p. 39
[59]	Wang Y, Liu H, Lv J, Zhu L, Wang H and Ma Y 2011 Nat. Commun. 2 563 doi: 10.1038/ncomms1566
[60]	Wang Y, Miao M, Lv J, Zhu L, Yin K, Liu H and Ma Y 2012 J. Chem. Phys. 137 224108 doi: 10.1063/1.4769731
[61]	Lu S, Wang Y, Liu H, Miao M and Ma Y 2014 Nat. Commun. 5 3666 doi: 10.1038/ncomms4666
[62]	Gao B, Gao P, Lu S, Lv J, Wang Y and Ma Y 2019 Sci. Bull. 64 301 doi: 10.1016/j.scib.2019.02.009
[63]	Gao B, Shao X, Lv J, Wang Y and Ma Y 2015 J. Phys. Chem. C 119 20111 doi: 10.1021/acs.jpcc.5b05035
[64]	Gao P, Wang S, Lv J, Wang Y and Ma Y 2017 RSC Adv. 7 39869 doi: 10.1039/C7RA07461A
[65]	Zhang X, Wang Y, Lv J, Zhu C, Li Q, Zhang M, Li Q and Ma Y 2013 J. Chem. Phys. 138 114101 doi: 10.1063/1.4794424
[66]	Gao P, Tong Q, Lv J, Wang Y and Ma Y 2017 Comput. Phys. Commun. 213 40 doi: 10.1016/j.cpc.2016.11.007
[67]	Zhang Y, Wang H, Wang Y, Zhang L and Ma Y 2017 Phys. Rev. X 7 011017
[68]	Su C, Lv J, Li Q, Wang H, Zhang L, Wang Y and Ma Y 2017 J. Phys. Condens. Matter 29 165901 doi: 10.1088/1361-648X/aa63cd
[69]	Behler J 2016 J. Chem. Phys. 145 170901 doi: 10.1063/1.4966192
[70]	Jacobsen T L, Jorgensen M S and Hammer B 2018 Phys. Rev. Lett. 120 026102 doi: 10.1103/PhysRevLett.120.026102
[71]	Deringer V L, Csányi G and Proserpio D M 2017 ChemPhysChem. 18 873 doi: 10.1002/cphc.201700151
[72]	Deringer V L, Pickard C J and Csányi G 2018 Phys. Rev. Lett. 120 156001 doi: 10.1103/PhysRevLett.120.156001
[73]	Bartók A P, Payne M C, Kondor R and Csányi G 2010 Phys. Rev. Lett. 104 136403 doi: 10.1103/PhysRevLett.104.136403
[74]	Tong Q, Xue L, Lv J, Wang Y and Ma Y 2018 Faraday Discuss. 211 31 doi: 10.1039/C8FD00055G
[75]	Reilly A M, Cooper R I, Adjiman C S, et al. 2016 Acta Crystallogr. Sect. B 72 439 doi: 10.1107/S2052520616007447

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[12]	Chun-Hua Chen(陈春华), Yong-Hui Zhou(周永惠), Ying Zhou(周颖), Yi-Fang Yuan(袁亦方), Chao An(安超), Xu-Liang Chen(陈绪亮), Zhao-Ming Tian(田召明), and Zhao-Rong Yang(杨昭荣). Pressure-induced anomalous insulating behavior in frustrated iridate La₃Ir₃O₁₁[J]. 中国物理B, 2021, 30(6): 67402-067402.
[13]	Ziyue Lin(林子越), Hongyu Yu(于洪雨), Hao Song(宋昊), Zihan Zhang(张子涵), Tianxiao Liang(梁天笑), Mingyang Du(杜明阳), and Defang Duan(段德芳). Novel rubidium polyfluorides with F₃, F₄, and F₅ species[J]. 中国物理B, 2021, 30(6): 66102-066102.
[14]	Wanrun Jiang(姜万润), Yuzhi Zhang(张与之), Linfeng Zhang(张林峰), and Han Wang(王涵). Accurate Deep Potential model for the Al-Cu-Mg alloy in the full concentration space[J]. 中国物理B, 2021, 30(5): 50706-050706.
[15]	Teng Ma(马腾), Pinwen Zhu(朱品文), and Xiaohui Yu(于晓辉). Progress in functional studies of transition metal borides[J]. 中国物理B, 2021, 30(10): 108103-108103.