Structure-property relationships from universal signatures of plasticity in disordered solids

Ekin D. Cubuk(Google (United States)), Robert Ivancic(University of Pennsylvania), Samuel S. Schoenholz(Google (United States)), Daniel J. Strickland(University of Pennsylvania), Anindita Basu(University of Pennsylvania), Zoey S. Davidson(University of Pennsylvania), J.-C. Fontaine(Université Claude Bernard Lyon 1), Jyo Lyn Hor(University of Pennsylvania), Yun-Ru Huang(University of Pennsylvania), Yijie Jiang(University of Pennsylvania), Nathan C. Keim(California Polytechnic State University), Komlavi Dzidula Koshigan(Université Claude Bernard Lyon 1), Joel A. Lefever(University of Pennsylvania), Tianyi Liu(University of Pennsylvania), Xiaoguang Ma(Solvay (Belgium)), Daniel J. Magagnosc(University of Pennsylvania), E. Morrow(Houghton University), C. Ortíz(University of Pennsylvania), Jennifer M. Rieser(University of Pennsylvania), Amit Shavit(University of Pennsylvania), Tim Still(University of Pennsylvania), Ye Xu(University of Pennsylvania), Y. Zhang(University of Pennsylvania), Kerstin Nordstrom(Mount Holyoke College), Paulo E. Arratia(University of Pennsylvania), Robert W. Carpick(University of Pennsylvania), D. J. Durian(University of Pennsylvania), Zahra Fakhraai(University of Pennsylvania), D. J. Jerolmack(University of Pennsylvania), Daeyeon Lee(University of Pennsylvania), Ju Li(Massachusetts Institute of Technology), Robert A. Riggleman(University of Pennsylvania), Kevin T. Turner(University of Pennsylvania), Arjun G. Yodh(University of Pennsylvania), Daniel S. Gianola(University of California, Santa Barbara), Andrea J. Liu(University of Pennsylvania)
Science
November 23, 2017
Cited by 313Open Access
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Abstract

When deformed beyond their elastic limits, crystalline solids flow plastically via particle rearrangements localized around structural defects. Disordered solids also flow, but without obvious structural defects. We link structure to plasticity in disordered solids via a microscopic structural quantity, "softness," designed by machine learning to be maximally predictive of rearrangements. Experimental results and computations enabled us to measure the spatial correlations and strain response of softness, as well as two measures of plasticity: the size of rearrangements and the yield strain. All four quantities maintained remarkable commonality in their values for disordered packings of objects ranging from atoms to grains, spanning seven orders of magnitude in diameter and 13 orders of magnitude in elastic modulus. These commonalities link the spatial correlations and strain response of softness to rearrangement size and yield strain, respectively.


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