Literature DB >> 30397419

Stochasticity in materials structure, properties, and processing-A review.

Robert Hull1, Pawel Keblinski1, Dan Lewis1, Antoinette Maniatty2, Vincent Meunier3, Assad A Oberai2, Catalin R Picu2, Johnson Samuel2, Mark S Shephard2, Minoru Tomozawa1, Deepak Vashishth4, Shengbai Zhang3.   

Abstract

We review the concept of stochasticity-i.e., unpredictable or uncontrolled fluctuations in structure, chemistry, or kinetic processes-in materials. We first define six broad classes of stochasticity: equilibrium (thermodynamic) fluctuations; structural/compositional fluctuations; kinetic fluctuations; frustration and degeneracy; imprecision in measurements; and stochasticity in modeling and simulation. In this review, we focus on the first four classes that are inherent to materials phenomena. We next develop a mathematical framework for describing materials stochasticity and then show how it can be broadly applied to these four materials-related stochastic classes. In subsequent sections, we describe structural and compositional fluctuations at small length scales that modify material properties and behavior at larger length scales; systems with engineered fluctuations, concentrating primarily on composite materials; systems in which stochasticity is developed through nucleation and kinetic phenomena; and configurations in which constraints in a given system prevent it from attaining its ground state and cause it to attain several, equally likely (degenerate) states. We next describe how stochasticity in these processes results in variations in physical properties and how these variations are then accentuated by-or amplify-stochasticity in processing and manufacturing procedures. In summary, the origins of materials stochasticity, the degree to which it can be predicted and/or controlled, and the possibility of using stochastic descriptions of materials structure, properties, and processing as a new degree of freedom in materials design are described.

Entities:  

Year:  2018        PMID: 30397419      PMCID: PMC6214486          DOI: 10.1063/1.4998144

Source DB:  PubMed          Journal:  Appl Phys Rev        ISSN: 1931-9401            Impact factor:   19.162


  17 in total

1.  Using fluctuation microscopy to characterize structural order in metallic glasses.

Authors:  Jing Li; X Gu; T C Hufnagel
Journal:  Microsc Microanal       Date:  2003-12       Impact factor: 4.127

2.  Chemical potential dependence of defect formation energies in GaAs: Application to Ga self-diffusion.

Authors: 
Journal:  Phys Rev Lett       Date:  1991-10-21       Impact factor: 9.161

3.  Glassy quasithermal distribution of local geometries and defects in quenched amorphous silicon.

Authors: 
Journal:  Phys Rev Lett       Date:  1988-08-01       Impact factor: 9.161

4.  Computer generation of structural models of amorphous Si and Ge.

Authors: 
Journal:  Phys Rev Lett       Date:  1985-04-01       Impact factor: 9.161

5.  Enhancing semiconductor device performance using ordered dopant arrays.

Authors:  Takahiro Shinada; Shintaro Okamoto; Takahiro Kobayashi; Iwao Ohdomari
Journal:  Nature       Date:  2005-10-20       Impact factor: 49.962

6.  Entropy rate of diffusion processes on complex networks.

Authors:  Jesús Gómez-Gardeñes; Vito Latora
Journal:  Phys Rev E Stat Nonlin Soft Matter Phys       Date:  2008-12-11

7.  Preparation, structure, dynamics, and energetics of amorphous silicon: A molecular-dynamics study.

Authors: 
Journal:  Phys Rev B Condens Matter       Date:  1989-07-15

8.  Molecular-dynamics simulation of amorphous germanium.

Authors: 
Journal:  Phys Rev B Condens Matter       Date:  1986-11-15

Review 9.  Clues for biomimetics from natural composite materials.

Authors:  Shaul Lapidot; Sigal Meirovitch; Sigal Sharon; Arnon Heyman; David L Kaplan; Oded Shoseyov
Journal:  Nanomedicine (Lond)       Date:  2012-09       Impact factor: 5.307

10.  Softening in Random Networks of Non-Identical Beams.

Authors:  Ehsan Ban; Victor H Barocas; Mark S Shephard; Catalin R Picu
Journal:  J Mech Phys Solids       Date:  2016-02-01       Impact factor: 5.471

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