Summary
In statistical physics and mathematics, percolation theory describes the behavior of a network when nodes or links are added. This is a geometric type of phase transition, since at a critical fraction of addition the network of small, disconnected clusters merge into significantly larger connected, so-called spanning clusters. The applications of percolation theory to materials science and in many other disciplines are discussed here and in the articles Network theory and Percolation (cognitive psychology). A representative question (and the source of the name) is as follows. Assume that some liquid is poured on top of some porous material. Will the liquid be able to make its way from hole to hole and reach the bottom? This physical question is modelled mathematically as a three-dimensional network of n × n × n vertices, usually called "sites", in which the edge or "bonds" between each two neighbors may be open (allowing the liquid through) with probability p, or closed with probability 1 – p, and they are assumed to be independent. Therefore, for a given p, what is the probability that an open path (meaning a path, each of whose links is an "open" bond) exists from the top to the bottom? The behavior for large n is of primary interest. This problem, called now bond percolation, was introduced in the mathematics literature by , and has been studied intensively by mathematicians and physicists since then. In a slightly different mathematical model for obtaining a random graph, a site is "occupied" with probability p or "empty" (in which case its edges are removed) with probability 1 – p; the corresponding problem is called site percolation. The question is the same: for a given p, what is the probability that a path exists between top and bottom? Similarly, one can ask, given a connected graph at what fraction 1 – p of failures the graph will become disconnected (no large component). The same questions can be asked for any lattice dimension. As is quite typical, it is actually easier to examine infinite networks than just large ones.
About this result
This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.
Related publications (14)

Mechanical Reinforcement of Hydrogels through Physical Crosslinks and Double Network Granular Architecture

Alvaro Lino Boris Charlet

Throughout nature, organisms fabricate a myriad of materials to sustain their lifestyle. Many of the soft materials are composed of water-swollen networks of organic molecules, so-called hydrogels. Th
EPFL2022

Recycling of Load-Bearing 3D Printable Double Network Granular Hydrogels

Esther Amstad, Matteo Hirsch, Alvaro Lino Boris Charlet, Sanjay Phileas Schreiber

Sustainable materials, such as recyclable polymers, become increasingly important as they are often environmentally friendlier than their one-time-use counterparts. In parallel, the trend toward more
WILEY-V C H VERLAG GMBH2022

Geometric Percolation of Spherically Symmetric Fractal Aggregates

Claudio Grimaldi

The connectedness percolation threshold (phi(c)) for spherically symmetric, randomly distributed fractal aggregates is investigated as a function of the fractal dimension (d(F)) of the aggregates thro
SPRINGER2022
Show more
Related concepts (21)
Percolation
In physics, chemistry, and materials science, percolation () refers to the movement and filtering of fluids through porous materials. It is described by Darcy's law. Broader applications have since been developed that cover connectivity of many systems modeled as lattices or graphs, analogous to connectivity of lattice components in the filtration problem that modulates capacity for percolation.
Percolation theory
In statistical physics and mathematics, percolation theory describes the behavior of a network when nodes or links are added. This is a geometric type of phase transition, since at a critical fraction of addition the network of small, disconnected clusters merge into significantly larger connected, so-called spanning clusters. The applications of percolation theory to materials science and in many other disciplines are discussed here and in the articles Network theory and Percolation (cognitive psychology).
Percolation threshold
The percolation threshold is a mathematical concept in percolation theory that describes the formation of long-range connectivity in random systems. Below the threshold a giant connected component does not exist; while above it, there exists a giant component of the order of system size. In engineering and coffee making, percolation represents the flow of fluids through porous media, but in the mathematics and physics worlds it generally refers to simplified lattice models of random systems or networks (graphs), and the nature of the connectivity in them.
Show more
Related courses (7)
MATH-434: Lattice models
Lattice models consist of (typically random) objects living on a periodic graph. We will study some models that are mathematically interesting and representative of physical phenomena seen in the real
COM-512: Networks out of control
The goal of this class is to acquire mathematical tools and engineering insight about networks whose structure is random, as well as learning and control techniques applicable to such network data.
PHYS-435: Statistical physics III
This course introduces statistical field theory, and uses concepts related to phase transitions to discuss a variety of complex systems (random walks and polymers, disordered systems, combinatorial o
Show more
Related lectures (32)
Random Growth Models and Hamilton-Jacobi Equation
Explores random growth models, shocks, and the Airy sheet in the context of Hamilton-Jacobi equation.
Phase Transitions: Percolation in 2D Networks
Explores phase transitions through percolation in 2D networks.
Percolation Theory
Covers percolation theory, absorbed polymers, giant molecules, phase transition, scaling assumptions, and universal behavior in percolation models.
Show more