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Prestress in amorphous solids bears the memory of their formation, and plays a profound role in their mechanical properties, from stiffening or softening elastic moduli to shifting frequencies of vibrational modes, as well as directing…

Soft Condensed Matter · Physics 2021-10-15 Shang Zhang , Ethan Stanifer , Vishwas Vasisht , Leyou Zhang , Emanuela Del Gado , Xiaoming Mao

Tuning of active prestress e.g. through activity of molecular motors constitutes a powerful cellular tool to adjust cellular stiffness through nonlinear material properties. Understanding this tool is an important prerequisite for our…

Soft Condensed Matter · Physics 2018-08-24 Elisabeth Fischer-Friedrich

The mechanics of disordered fibrous networks such as those that make up the extracellular matrix are strongly dependent on the local connectivity or coordination number. For biopolymer networks this coordination number is typically between…

Soft Condensed Matter · Physics 2019-05-01 Sadjad Arzash , Jordan L. Shivers , Albert J. Licup , Abhinav Sharma , Fred C. MacKintosh

States of self stress, organizations of internal forces in many-body systems that are in equilibrium with an absence of external forces, can be thought of as the constitutive building blocks of the elastic response of a material. In…

Soft Condensed Matter · Physics 2016-01-15 Daniel M. Sussman , Carl P. Goodrich , Andrea J. Liu

Collagen is the main structural and load-bearing element of various connective tissues, where it forms the extracellular matrix that supports cells. It has long been known that collagenous tissues exhibit a highly nonlinear stress-strain…

The paper presents a methodology for the enhanced stiffness analysis of parallel manipulators with internal preloading in passive joints. It also takes into account influence of the external loading and allows computing both the non-linear…

Robotics · Computer Science 2010-12-10 Anatoly Pashkevich , Alexandr Klimchik , Damien Chablat

Unlike classical elasticity, where stresses arise from deformations relative to a stress-free reference configuration, rigidity in amorphous systems is maintained by disordered force networks that generate internal prestress. Previously, we…

Disordered spring networks are a useful paradigm to examine macroscopic mechanical properties of amorphous materials. Here, we study the elastic behavior of under-constrained spring networks, i.e.\ networks with more degrees of freedom than…

Soft Condensed Matter · Physics 2023-01-18 Cheng-Tai Lee , Matthias Merkel

By applying effective medium-style calculations to random spring networks, we demonstrate that internal stresses fundamentally alter the nature of the rigidity transition in disordered materials, changing it from continuous to first-order…

Materials Science · Physics 2009-11-11 D. A. Head

Disordered filamentous networks with compliant crosslinks exhibit a low linear elastic shear modulus at small strains, but stiffen dramatically at high strains. Experiments have shown that the elastic modulus can increase by up to three…

Biological Physics · Physics 2015-01-06 Knut M. Heidemann , Abhinav Sharma , Florian Rehfeldt , Christoph F. Schmidt , Max Wardetzky

Disordered spring networks that are undercoordinated may abruptly rigidify when sufficient strain is applied. Since the deformation in response to applied strain does not change the generic quantifiers of network architecture - the number…

Soft Condensed Matter · Physics 2017-11-29 Mathijs F. J. Vermeulen , Anwesha Bose , Cornelis Storm , Wouter G. Ellenbroek

Analytical and numerical calculations are presented for the mechanical response of fiber networks in a state of axisymmetric prestress, in the limit where geometric non-linearities such as fiber rotation are negligible. This allows us to…

Biological Physics · Physics 2014-02-27 D. A. Head , D. Mizuno

Elastic structures can be designed to exhibit precise, complex, and exotic functions. While recent work has focused on the quasistatic limit governed by force balance, the mechanics at a finite driving rate are governed by Newton's…

Soft Condensed Matter · Physics 2024-12-17 Marc Berneman , Daniel Hexner

Athermal models of disordered fibrous networks are highly useful for studying the mechanics of elastic networks composed of stiff biopolymers. The underlying network architecture is a key aspect that can affect the elastic properties of…

Soft Condensed Matter · Physics 2016-01-20 Albert James Licup , Abhinav Sharma , Fred C. MacKintosh

Cells and tissues change shape both to carry out their function and during pathology. In most cases, these deformations are driven from within the systems themselves. This is permitted by a range of molecular actors, such as active…

Biological Physics · Physics 2022-10-18 Alexander Erlich , Jocelyn Étienne , Jonathan Fouchard , Tom Wyatt

The non-linear stress-strain relation for crosslinked polymer networks is studied using molecular dynamics simulations. Previously we demonstrated the importance of trapped entanglements in determining the elastic and relaxational…

Soft Condensed Matter · Physics 2009-10-31 Gary S. Grest , Mathias Puetz , Kurt Kremer , Ralf Everaers

To assess the role of single-chain elasticity, non-affine strain fields and pre-stressed reference states we present and discuss the results of numerical and analytical analyses of modified 8-chain Arruda-Boyce model for cross-linked…

Soft Condensed Matter · Physics 2016-04-20 Adrian Cioroianu , Ewa Spiesz , Cornelis Storm

Amorphous particulate matter constitutes a wide range of natural and synthetic materials. Despite this ubiquity, the way in which these systems' disordered microstructure couples to their often subtle and complex dynamical behavior is not…

Soft Condensed Matter · Physics 2026-03-09 Erin G. Teich , Jason Z. Kim , Dani S. Bassett

Stress-strain curves, or more generally, stress functions, are an extremely important characterization of a material's mechanical properties. However, stress functions are often difficult to derive and are narrowly tailored to a specific…

Materials Science · Physics 2023-12-21 Garrett Blum , Ryan Doris , Diego Klabjan , Horacio Espinosa , Ron Szalkowski

Evaluating the mechanical response of fiber-reinforced composites can be extremely time consuming and expensive. Machine learning (ML) techniques offer a means for faster predictions via models trained on existing input-output pairs and…

Materials Science · Physics 2024-10-03 Yixuan Sun , Imad Hanhan , Michael D. Sangid , Guang Lin
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