Role of topology in scaling laws for studying mechanics in open-porous solids: Moving beyond classical Gibson-Ashby scaling
Ameya Rege
Abstract
The elastic modulus of porous materials is commonly described using power-law scaling relations with relative density, where the scaling exponent is often interpreted in terms of the underlying deformation mechanism. However, in highly disordered porous networks, changes in density are generally accompanied by changes in network topology, which can substantially modify the apparent scaling behavior. In this paper, we propose a topology-informed framework that separates the intrinsic mechanical contribution from the effects of network structure. Three representative topological descriptors are considered: the mean coordination number, the fraction of the load-bearing backbone, and the tortuosity of the load paths. For each case, the corresponding density-dependent contribution to the apparent modulus-scaling exponent is derived and analyzed. The results show that variations in connectivity, mechanical participation of the solid phase, and load-path efficiency can all lead to apparent scaling exponents exceeding the intrinsic exponent associated with the local deformation mechanism. These effects are particularly pronounced at low relative densities, where network topology evolves most strongly. The framework provides a physically interpretable basis for understanding anomalous modulus-density scaling in disordered porous materials and highlights the need to consider topology explicitly alongside relative density.
Create a lesson
Related papers
Geometry-Controlled Relaxation Spectra in Viscoelastic Fluids
Niloyendu Roy, Rupayan Saha, Debankur Das et al.
Dense HeLa cell monolayers remain liquid-like despite strong crowding
Suravi Pal, Nen Saito, Takeshi Kawasaki et al.
Transport of Deformable Vesicles Driven by Chiral Active Brownian Particles
Dipak Patra, Anil Kumar Dasanna
Conformational landscape of a macrocycle from REST enhanced sampling
Valentin Kasper, Nicole Holzmann, Sanjoy Ray et al.
Prediction of the maximum penetration of a circular intruder in a two-dimensional granular bed from its early trajectory using Machine Learning
Patricia Altshuler
Odd slip at chiral active surfaces
Yuto Hosaka, Andrej Vilfan