Page 60 - Read Online
P. 60

Page 12 of 12                          Liu et al. J Mater Inf 2022;2:20  https://dx.doi.org/10.20517/jmi.2022.29

               21.      Tong Y, Qiao J, Pelletier J, Yao Y. Rate-dependent plastic deformation of TiZrHfCuNiBe high entropy bulk metallic glass. J Alloys
                   Compd 2019;785:542-52.  DOI
               22.      Zhang L, Wang Y, Pineda E, Kato H, Yang Y, Qiao J. Sluggish dynamics of homogeneous flow in high-entropy metallic glasses. Scr
                   Mater 2022;214:114673.  DOI
               23.      Zhang L, Duan Y, Crespo D, et al. Identifying the high entropy characteristic in La-based metallic glasses. Appl Phys Lett
                   2021;119:051905.  DOI
               24.      Gu J, Luan H, Zhao S, et al. Unique energy-storage behavior related to structural heterogeneity in high-entropy metallic glass. Mater
                   Sci Eng A 2020;786:139417.  DOI
               25.      Duan Y, Qiao J, Wada T, et al. Stress relaxation in high-entropy Pd Pt Cu Ni P  metallic glass: experiments, modeling and theory.
                                                               20  20  20  20 20
                   Mech Mater 2021;160:103959.  DOI
               26.      Wu J, Zhou Z, Yang H, et al. Structure related potential-upsurge during tensile creep of high entropy Al Ce La Ni Y  metallic
                                                                                         20  20  20  20  20
                   glass. J Alloys Compd 2020;827:154298.  DOI
               27.      Cubuk ED, Schoenholz SS, Rieser JM, et al. Identifying structural flow defects in disordered solids using machine-learning methods.
                   Phys Rev Lett 2015;114:108001.  DOI  PubMed
               28.      Wang Q, Jain A. A transferable machine-learning framework linking interstice distribution and plastic heterogeneity in metallic
                   glasses. Nat Commun 2019;10:5537.  DOI  PubMed  PMC
               29.      Fan Z, Ding J, Ma E. Machine learning bridges local static structure with multiple properties in metallic glasses. Mater Today
                   2020;40:48-62.  DOI
               30.      Peng Z, Yang Z, Wang Y. Machine learning atomic-scale stiffness in metallic glass. Extreme Mech Lett 2021;48:101446.  DOI
               31.      Yang Z, Wei D, Zaccone A, Wang Y. Machine-learning integrated glassy defect from an intricate configurational-thermodynamic-
                   dynamic space. Phys Rev B 2021:104.  DOI
               32.      Takeuchi A, Wang J, Chen N, et al. Al TiZrPdCuNi high-entropy (H-E) alloy developed through Ti Zr Pd Cu Ni  H-E glassy
                                             0.5                                      20  20  20  20  20
                   alloy comprising inter-transition metals. Mater Trans 2013;54:776-82.  DOI
               33.      Zhou XW, Johnson RA, Wadley HNG. Misfit-energy-increasing dislocations in vapor-deposited CoFe/NiFe multilayers. Phys Rev B
                   2004:69.  DOI
               34.      Liu X, He Q, Lu W, et al. Machine learning atomic dynamics to unfold the origin of plasticity in metallic glasses: from thermo- to
                   acousto-plastic flow. Sci China Mater 2022;65:1952-62.  DOI
               35.      Robnik-Šikonja M, Kononenko I. Theoretical and empirical analysis of reliefF and RReliefF. Mach Learn 2003;53:23-69.  DOI
               36.      Spikes H. Stress-augmented thermal activation: tribology feels the force. Friction 2018;6:1-31.  DOI
               37.      Xu Z, Qiao J, Wang J, Pineda E, Crespo D. Comprehensive insights into the thermal and mechanical effects of metallic glasses via
                   creep. J Mater Sci Technol 2022;99:39-47.  DOI
               38.      Park K, Fleury E, Seok H, Kim Y. Deformation behaviors under tension and compression: atomic simulation of Cu Zr  metallic
                                                                                                65  35
                   glass. Intermetallics 2011;19:1168-73.  DOI
               39.      Qiao J, Pelletier J, Yao Y. Creep in bulk metallic glasses. Transition from linear to non linear regime. Mater Sci Eng A 2019;743:185-
                   9.  DOI
               40.      Wu Y, Wang B, Hu Y, et al. The critical strain - a crossover from stochastic activation to percolation of flow units during stress
                   relaxation in metallic glass. Scr Mater 2017;134:75-9.  DOI
               41.      Huo L, Zeng J, Wang W, Liu C, Yang Y. The dependence of shear modulus on dynamic relaxation and evolution of local structural
                   heterogeneity in a metallic glass. Acta Mater 2013;61:4329-38.  DOI
               42.      Falk ML, Langer JS. Dynamics of viscoplastic deformation in amorphous solids. Phys Rev E 1998;57:7192-205.  DOI
               43.      Xu TD, Wang XD, Zhang H, Cao QP, Zhang DX, Jiang JZ. Structural evolution and atomic dynamics in Ni-Nb metallic glasses: a
                   molecular dynamics study. J Chem Phys 2017;147:144503.  DOI  PubMed
               44.      Lu W, Tseng J, Feng A, Shen J. Structural origin of the enhancement in glass-forming ability of binary Ni-Nb metallic glasses. J Non-
                   Cryst Solids 2021;564:120834.  DOI
               45.      Cargill G, Spaepen F. Description of chemical ordering in amorphous alloys. J Non-Cryst Solids 1981;43:91-7.  DOI
               46.      Takeuchi A, Inoue A. Classification of bulk metallic glasses by atomic size difference, heat of mixing and period of constituent
                   elements and its application to characterization of the main alloying element. Mater Trans 2005;46:2817-29.  DOI
   55   56   57   58   59   60   61   62   63   64   65