Berg Carl Fredrik, Sahimi Muhammad
PoreLab, Department of Geosciences, <a href="https://ror.org/05xg72x27">Norwegian University of Science and Technology</a>, Trondheim, Norway.
Mork Family Department of Chemical Engineering and Materials Science, <a href="https://ror.org/03taz7m60">University of Southern California</a>, Los Angeles, California 90089-1211, USA.
Phys Rev E. 2024 Oct;110(4):L042104. doi: 10.1103/PhysRevE.110.L042104.
A central unsolved problem in percolation theory over the past five decades has been whether there is a direct relationship between the critical exponents that characterize the power-law behavior of the transport properties near the percolation threshold, particularly the effective electrical conductivity σ_{e}, and the exponents that describe the morphology of percolation clusters. The problem is also relevant to the relation between the static exponents of percolation clusters and the critical dynamics of spin waves in dilute ferromagnets, the elasticity of gels and composite solids, hopping conductivity in semiconductors, solute transport in porous media, and many others. We propose an approach to address the problem by showing that the contributions to σ_{e} can be decomposed into several groups representing the structure of percolation networks, including their mass and tortuosity, as well as constrictivity that describes the fluctuations in the driving potential gradient along the transport paths. The decomposition leads to a relationship between the critical exponent t of σ_{e} and other percolation exponents in d dimensions, t/ν=(d-D_{bb})+2(D_{op}-1)+d_{C}, where ν, D_{bb}, D_{op}, and d_{C} are, respectively, the correlation length exponent, the fractal dimensions of the backbones and the optimal paths, and the exponent that characterizes the constrictivity. Numerical simulations in two and three dimensions, as well as analytical results in d=1 and d=6, the upper critical dimension of percolation, validate the relationship. We, therefore, believe that the solution to the 50-year-old problem has been derived.
在过去五十年里,渗流理论中一个核心的未解决问题是,表征渗流阈值附近输运性质幂律行为的临界指数,特别是有效电导率σₑ,与描述渗流团簇形态的指数之间是否存在直接关系。这个问题还与渗流团簇的静态指数和稀磁体中自旋波的临界动力学、凝胶和复合固体的弹性、半导体中的跳跃电导率、多孔介质中的溶质输运等之间的关系相关。我们提出一种解决该问题的方法,通过表明对σₑ的贡献可以分解为几组,分别代表渗流网络的结构,包括其质量和曲折度,以及描述沿输运路径驱动势梯度波动的收缩性。这种分解导致了d维中σₑ的临界指数t与其他渗流指数之间的关系,即t/ν = (d - Dₜₜ) + 2(Dₒₚ - 1) + dₙ,其中ν、Dₜₜ、Dₒₚ和dₙ分别是关联长度指数、骨架和最优路径的分形维数,以及表征收缩性的指数。二维和三维的数值模拟,以及d = 1和d = 6(渗流的上临界维数)的解析结果,验证了这种关系。因此,我们相信已经得出了这个五十年来问题的解决方案。