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Related papers: Roughness density

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Disordered solids exhibit unusual properties of their vibrational states and thermal conductivities. Recent progresses have well established the concept of "elastic heterogeneity", i.e., disordered materials show spatially inhomogeneous…

Disordered Systems and Neural Networks · Physics 2014-01-09 Hideyuki Mizuno , Stefano Mossa , Jean-Louis Barrat

When two macromolecules come very near in a fluid, the surrounding molecules, having finite volume, are less likely to get in between. This leads to a pressure difference manifesting as an entropic attraction, called depletion force. Here…

Soft Condensed Matter · Physics 2020-02-26 Nathaniel Rupprecht , Dervis Can Vural

The driven transport of plastic systems in various disordered backgrounds is studied within mean field theory. Plasticity is modeled using non-convex interparticle potentials that allow for phase slips. This theory most naturally describes…

Disordered Systems and Neural Networks · Physics 2009-11-10 Karl Saunders , J. M. Schwarz , M. Cristina Marchetti , A. Alan Middleton

Disordered elastic networks provide a framework for describing a wide variety of physical systems, ranging from amorphous solids, through polymeric fibrous materials to confluent cell tissues. In many cases, such networks feature two widely…

Soft Condensed Matter · Physics 2024-09-02 Edan Lerner , Eran Bouchbinder

A rigidity theory is developed for bar-joint frameworks in $\mathbb{R}^{d+1}$ whose vertices are constrained to lie on concentric $d$-spheres with independently variable radii. In particular, combinatorial characterisations are established…

Metric Geometry · Mathematics 2017-02-14 Anthony Nixon , Bernd Schulze , Shin-ichi Tanigawa , Walter Whiteley

The review is devoted to the theory of collective and it local pinning effects in various disordered non-linear driven systems. Although the emphasis is put on charge and spin density waves and magnetic domain walls, the theory has also…

Statistical Mechanics · Physics 2009-11-10 Serguei Brazovskii , Thomas Nattermann

A phase field model is presented to investigate dislocation formation (coherency loss) and workhardening in two-phase binary alloys. In our model the elastic energy density is a periodic function of the shear and tetragonal strains, which…

Statistical Mechanics · Physics 2013-05-29 Akihiko Minami , Akira Onuki

The effect of disorder on flux lattices at equilibrium is studied quantitatively in the absence of free dislocations using both the Gaussian variational method and the renormalization group. Our results for the mean square relative…

Condensed Matter · Physics 2016-08-31 T. Giamarchi , P. Le Doussal

The simultaneous effect of both disorder and crystal-lattice pinning on the equilibrium behavior of oriented elastic objects is studied using scaling arguments and a functional renormalization group technique. Our analysis applies to…

Statistical Mechanics · Physics 2009-10-31 Thorsten Emig , Thomas Nattermann

A comprehensive field theory is developed for superconductors with quenched disorder. We first show that the matrix field theory, used previously to describe a disordered Fermi liquid and a disordered itinerant ferromagnet, also has a…

Superconductivity · Physics 2009-11-10 Lubo Zhou , T. R. Kirkpatrick

The complicated dynamics of the contact line of a moving droplet on a solid substrate often hamper the efficient modeling of microfluidic systems. In particular, the selection of the effective boundary conditions, specifying the contact…

Self-affine rough interfaces are ubiquitous in experimental systems, and display characteristic scaling properties as a signature of the nature of disorder in their supporting medium, i.e. of the statistical features of its heterogeneities.…

Disordered Systems and Neural Networks · Physics 2021-07-21 Sebastian Bustingorry , Jill Guyonnet , Patrycja Paruch , Elisabeth Agoritsas

Under the application of a force, a material will deform and, hence, the crystal lattice will experience strain. This induced strain will alter the electronic properties of the material. In particular, strain in graphene generates an…

Mesoscale and Nanoscale Physics · Physics 2014-07-08 J. A. Crosse

The measurement of cellular traction forces on soft elastic substrates has become a standard tool for many labs working on mechanobiology. Here we review the basic principles and different variants of this approach. In general, the…

Quantitative Methods · Quantitative Biology 2015-06-09 Ulrich S. Schwarz , Jerome R. D. Soine

Soft solids and their surface deformations control the response of many natural and artificial systems. Yet, their underlying properties are vigorously debated, particularly for polymer networks. While molecular-scale theories predict no…

Semiflexible polymers in poor solvents exhibit a rich variety of collapsed morphologies, including globules, toroids, and rodlike bundles, arising from the competition between attractive interactions and chain stiffness. Computer…

Statistical Mechanics · Physics 2026-01-22 Biman Bagchi

Twisted assemblies of filaments in ropes, cables and bundles are essential structural elements in wide use in macroscopic materials as well as within the cells and tissues of living organisms. We develop the unique, non-linear elastic…

Soft Condensed Matter · Physics 2015-05-18 Gregory M. Grason

A new variational method for studying the equilibrium states of an interacting particles system has been proposed. The statistical description of the system is realized by means of a density matrix. This method is used for description of…

General Physics · Physics 2014-12-19 Boris Bondarev

The vertex model is widely used to describe the dynamics of epithelial tissues, because of its simplicity and versatility and the direct inclusion of biophysical parameters. Here, it is shown that quite generally, when cells modify their…

Soft Condensed Matter · Physics 2020-11-25 Fernanda Perez-Verdugo , Jean-Francois Joanny , Rodrigo Soto

The same machine learning model running on different edge devices may produce highly-divergent outputs on a nearly-identical input. Possible reasons for the divergence include differences in the device sensors, the device's signal…

Machine Learning · Computer Science 2020-10-20 Eyal Cidon , Evgenya Pergament , Zain Asgar , Asaf Cidon , Sachin Katti