T HE P HYSICS OF F OAM Boulder School for Condensed Matter and Materials Physics July 1-26, 2002: Physics of Soft Condensed Matter 1. Introduction Formation.

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Presentation transcript:

T HE P HYSICS OF F OAM Boulder School for Condensed Matter and Materials Physics July 1-26, 2002: Physics of Soft Condensed Matter 1. Introduction Formation Microscopics 2. Structure Experiment Simulation 3. Stability Coarsening Drainage 4. Rheology Linear response Rearrangement & flow Douglas J. DURIAN UCLA Physics & Astronomy Los Angeles, CA

local structure recap liquid fraction  ~ [(border radius r) / (bubble radius R)] 2 Plateau’s rules for mechanical equilibrium: (1) films have constant curvature & intersect three at a time at 120 o (2) Plateau borders intersect four at a time at cos -1 (1/3)= o Plateau border vertex

Periodic foams, 2D the simplest structure to satisfy Plateau’s rules is a honeycomb –seems obvious, but only proved in 2001 by T.C. Hales to be the partitioning of 2D space into cells of equal area with the minimum perimeter

Periodic foams, 3D it’s not possible to satisfy Plateau’s rules with regular solids having flat faces & straight Plateau borders –Kelvin foam: like Wigner-Seitz cell for BCC lattice, but with films and Plateau borders curved to satisfy Plateau tetrakaidecahedron (14 sided): 6 quadrilaterals + 8 hexagons {1/r 1 + 1/r 2 = 0}

Honeycomb for a 4D bee? Bees build a 2D foam that minimizes perimeter/cell What foam structure minimizes area at unit cell volume? –values for Wigner-Seitz cells curved according to Plateau SC {1 x 1 x 1}:6 FCC: BCC/Kelvin: {sphere: (36  ) 1/3 = } Long believed to be the optimal 3D periodic foam

A15/Weaire-Phelan foam BCC/Kelvin: A15/Weaire-Phelan: –constructed from two different cell types tetrakaidecahedron: 12 pentagons and 2 opposing hexagons –these stack into three sets of orthogonal columns dodecahedron: 12 pentagons –these fit into interstices between columns A new champion! (0.3% improvement) {P 12 > P 14 }

Bubbles in a tube other ordered structures can readily be produced by blowing monodisperse bubbles into a tall tube:

Random structures bulk foams are naturally polydisperse and disordered! –(we’ll see later that ordered foams are unstable)

A tedious experiment Matzke (J. Botany 1946) constructed random monodisperse foams by individually blowing ~10 3 bubbles and placing them into a container by hand –most abundant cell: 13-hedron 1 quadrilateral, 10 pentagons, 2 hexagons Matzke didn’t find even a single Kelvin tetrakaidecadedron! –almost all faces were 4, 5, or 6 sided –average number of faces per cell =13.70

easier for 2D foams –bubbles squashed between glass plates –bubbles floating at an air/water interface (“raft”) –domains of phase-separated lipid monolayers distribution of edges per bubble, p(n) –average number of edges per bubble: =  [n p(n)] = 6 –second moment,  2 =  [(n-6) 2 p(n)] = 1.4 hexagons are common, but there is considerable width neighbor correlations –average number of edges of neighbors to n-sided bubbles, m(n) –Aboav law: m(n) = 5 + 8/n combined with Lewis “law” (A n ~ n+n o, which actually doesn’t work so well) big bubbles are surrounded by small bubbles and vice-versa

Topology Euler equation for total # of cells, faces, edges, vertices: N F – N E + N V = 1 (2D) – N C + N F – N E + N V = 1 (3D) Combine with Plateau in 2D N V = 2/3 N E, so large N F = N E – N V = 1/3 N E hence = 2 N E / N F = 6 –as observed Combine with Plateau in 3D = 12/(6 – ) –Matzke result =13.70 implies = 5.12

Imaging methods ordinary microscopy / photography (eg Matzke) –good only for very dry foams a few bubbles across large numerical-aperture lens –image one 2D slice at a time, but same defect as (1) confocal microscopy – reject scattered light –slightly wetter foams / larger samples medical (MRI, tomography) –slow

Other structural probes Moving fiber probe –drive optical fiber through a bulk foam: reflection spikes indicate proximity of a film; gives ~cell-size distribution doesn’t pop the bubbles! Electrical conductance –conductivity is proportional to liquid fraction independent of bubble size! Archimedes – depth of submerged foam –deduce liquid fraction foam

Photon diffusion 3D foams are white / opaque clear foams do not exist! –photons reflect & refract from gas/liquid interfaces –multiple scattering events amount to a random walk (diffusion!) while this limits optical imaging methods, it can also be exploited as a probe of foam structure & dynamics… <<r

Transmission probability how much light gets through a sample of thickness L? –ballistic transmission is set by scattering length T b =Exp[-L/l s ] (vanishingly small: or less) –diffuse transmission is set by transport mean free path (D=cl * /3) T d =(z p +z e )/(L/l * +2z e )~l*/L (easily detectable: 0.01 – 0.1)

Foam optics Plateau borders are the primary source of scattering –recall liquid fraction  ~ (border radius r / bubble radius R) 2 –estimate the photon transport mean free path from their number density and geometrical cross section: FAST & NON-INVASIVE PROBE: diffuse transmission gives l* l* gives bubble size or liquid fraction

How random is the walk? the foam absorbs more light than expected based on the volume fraction of liquid {l a /l a soln = 1/  } –Plateau borders act like a random network of optical fibers effect vanishes for very wet foams: Plateau border length vanishes effect vanishes for very dry foams: photons exit at vertices

Diffusing-wave spectroscopy Form a speckle pattern at plane of detector As scattering sites move, the speckle pattern fluctuates –for maximum intensity variation: detection spot = speckle size –measure to deduce nature & rate of motion

Simulation of structure in 2D the elements are all circular arcs (wet or dry) otherwise the gas pressure wouldn’t be constant across the cell adjust endpoints and curvature, while maintaining constant area, until Plateau is satisfied everywhere iteratively or all at once

Surface Evolver in 3D it’s much harder… –films have constant curvature but are not spherical –Plateau borders have arbitrary shape The “Surface Evolver” program by Ken Brakke minimizes film area at fixed topology –approximate surfaces by flat triangular plaquets eg successive refinement of Kelvin cell:

Surface Evolver – uses discovery of A15/Weaire-Phelan foam wet Kelvin foams

Surface Evolver – uses random monodisperse foams polydisperse foams

Surface Evolver – uses Apply shear to any of the above Reconstruct full structure from partial tomographic data –eg finding films and volumes knowing only Plateau borders In general: statistics of dry foams in static equilibrium Drawbacks –fixed topology (must be reset by hand during equilibration / flow / evolution) –progressively slower for wetter foams –no true dynamics (film-level dissipation mechanisms cannot be included)

Q-state Potts model each lattice site has a spin, with a value that depends on the cell to which it belongs; eg: –energy penalty for neighbors of different spin –flip spins at interface by Monte-Carlo minimizes interfacial area, like Surface Evolver, but slower avoids the issue of setting topology by hand but no true dynamics

Bubble model Consider bubbles, not films, as the structural elements –ignore shape degrees of freedom –move bubbles according to pairwise interactions: 1.Spring force for overlapping bubbles (strictly repulsive) {exact in 2D, good approximation in 3D} 2.Dynamic friction for neighboring bubbles (~velocity difference)

Bubble model – uses rough caricature of essential microscopic physics –exact for wet foam limit of close-packed spheres no need to keep track of topology by hand true dynamics, and computationally cheap –not useful for topology statistics –good for evolution and flow

Next time… {not yet ready foam rheology} evolution of aqueous foams –coarsening, in response to gas diffusion –drainage, in response to gravity