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1 The Statistical Physics of Athermal Particles (The Edwards Ensemble at 25) Karen Daniels Dept. of Physics NC State University http://nile.physics.ncsu.edu
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The Statistical Physics of Athermal Particles (The Edwards ...

Feb 02, 2022

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Page 1: The Statistical Physics of Athermal Particles (The Edwards ...

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The Statistical Physicsof Athermal Particles

(The Edwards Ensemble at 25)Karen Daniels

Dept. of PhysicsNC State University

http://nile.physics.ncsu.edu

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Sir Sam Edwards

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Why Consider Ensembles? for ordinary materials, statistical mechanics explains many phenomena

– Example: Ideal Gas microstate: list of the positions and velocities of each

atom in the gas ri, vi

macrostate: global quantities P, V, T, N, S, E equation of state: PV = NkT

– Generally: a collection of microstates, each occurring with a probability that depends on a few macroscopic parameters

granular materials also exhibit particle-scale probability distributions that depend on a few macroscopic quantities V, P

– Can we study the ensemble of microstates? find useful macroscopic variables? equation of state?

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Why Not Consider Ensembles?

Can we study the ensemble of microstates?

Find useful macroscopic variables?

Write predictive equations of state?

Or is this a crazy idea?

athermal: kBT ~ 10-12 mgd (so temperature has little effect)

dissipative (friction & collisions) invalidates fundamental →postulate of energy conservation

poor separation of micro/macroscopic scales history-dependence due to frictional contacts without temperature, how does the system explore the

ensemble?

d

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Simplify the Problem

Granular Materials non-cohesive,non-attractive,

macroscopic particles which interact only

when in contact

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Solid Liquid Gas

Jaeger, Nagel, BehringerPhysics Today. (1996)

consider an ensemble of

“blocked” packings (mechanically-stable,

jammed)

Θ (r i)= 1, blocked0, unblocked

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Boltzmann Refresher 1

1st Law total energy → E of a system in isolation is constant

microcanonical ensemble: set of microstates (ν) with total energy E(ri, pi) for particles i

E is a macroscopic, extensive variable all microstates with energy E are assumed to occur

with equal probability (“flat measure”) a physical system is characterized by its density of

states:

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Boltzmann Refresher 2 canonical ensemble allows consideration of a

subsystem (with fluctuating energy E) in contact with a large heat bath

density of states: Ω = # of microstates with energy E

entropy: S = kB ln Ω(E)

maximization of entropy temperature →

temperature T is an intensive macroscopic variable, associated with the extensive variable E

1T=(∂ S (E)

∂ E )V

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Edwards' Central Idea

smallest system volume

only one validconfiguration

larger volume

more validconfigurations

S=k E lnΩ(V )

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Edwards' Granular Ensemble

count blocked microstates at volume V– cannot move grains without causing a finite overlap

density of states: Ω(V) = Σν δ(V – Vν)

– sum is over blocked states:

– all blocked states are equiprobable (?)

Edwards' entropy: S = λ ln Ω(V)

Edwards' temperature “compactivity”→

1X=(∂ S (V )

∂V )

Θ (r i)=1

1

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Boltzmann Ensemble Edwards Ensemble

Energy is conservedTemperature equilibratesΩ(E) counts valid states

Volume is conservedCompactivity equilibratesΩ(V) counts jammed states

1T=∂ S∂ E

1X=∂ S∂V

e−

EkB T

e−

VX

S=k B lnE S=k E lnV

C v=d ⟨E ⟩d T

=1

k B T 2 ⟨ dE 2⟩d ⟨V ⟩

d X=

1X 2 ⟨dV 2

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Packing Fraction

high low

data visualization with Voro++ Rycroft et. al. PRE (2006) http://math.lbl.gov/voro++/

φ=N V particle

V system

φ=V particle

V Voronoï

local definition

global definition

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Measuring Compactivity

X 0→

– random close packing: φRCP

– densest packing that still has no crystalline order

– large φ little free space → →can't be compacted more

X → ∞– random loose packing: φRLP

– loosest packing that still has mechanical stability

– small φ lots of free space → →high susceptibility to compaction

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Method 1: “Specific Heat”

record steady state volume fluctuations

integrate to measure changes in compactivity

C v=d ⟨E ⟩d T

=1

k B T 2 ⟨dE2⟩

d ⟨V ⟩

d X=

1X 2 ⟨dV 2

Nowak, Knight, Ben-Naim, Jaeger, Nagel. PRE (1998)

translate Boltzmann to Edwards

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Example 1: Tapping a Granular Column

Knight, Fandrich, Lau, Jaeger, Nagel. PRE (1995)Nowak, Knight, Ben-Naim, Jaeger, Nagel. PRE (1998)

packing fraction fluctuations

tapping

measure volume

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Example 1: Tapping a Granular Column

Nowak, Knight, Ben-Naim, Jaeger, Nagel. PRE (1998)

use volume fluctuations to calculate changes in compactivity

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Example 2: Sedimentation in a Fluid

Schröter, Goldman, Swinney. PRE (2005)

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Method 2: “Overlapping Histograms” by analogy with Boltzmann, calculate the probability of observing a

macroscopic volume V:

for density of states Ω(V) generally not known, but independent of → X

partition function Z(X) generally not known→

RATIO of two measurement provides RELATIVE temperatures

Dean & Lefèvre, PRL (2003)McNamara, Richard, de Richter, Le Caër, Delannay. PRE (2009)

P (V )=Ω(V )Z (X )

e−

VX

P (V 1)

P (V 2)=

Z (X 2)

Z (X 1)e

V ( 1X 2

−1X 1 )

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Example: Particle-Scale Volumes

numerical simulations, subjected to virtual “tapping” histogram of local (Voronoï) volumes

McNamara, Richard, de Richter, Le Caër, Delannay. PRE (2009)

more taps, lower volume

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Example: Calculate Compactivity

McNamara, Richard, de Richter, Le Caër, Delannay. PRE (2009)

P (V 1)

P (V 2)=

Z (X 2)

Z (X 1)e

V ( 1X 2

−1X 1 )

V1 V2

logP (V 1)

P (V 2)=const.+V ( 1

X 2

−1

X 1)

measure relative compactivities from the slope

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Compactivity Decreases with Taps

McNamara, Richard, de Richter, Le Caër, Delannay. PRE (2009)

more taps = smaller volume = higher φ

smaller compactivity

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Testing Equiprobability Assumption consider 7 particles in a box

generate millions of blocked configurations in matched simulations and experiments

enumerate all possible configurations

Gao, Blawzdziewicz, O’Hern, Shattuck. PRE (2009)

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Equiprobability Assumption Fails

Gao, Blawzdziewicz, O’Hern, Shattuck. PRE (2009)

simulationexperiment

some configurations are 106 more likely than others → Ω(V) is non-trivial

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Summary so Far

compactivity can be measured using two methods: “specific heat” or “overlapping histograms”

compactivity increases as packing fraction decreases

does compactivity behave like a temperature?equilibration?

useful state variable?

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Test the “Zeroth Law”

Zeroth lawrequires

temperatureequilibration

Does Xbath = Xsubsys

?

lowfriction

highfriction

Puckett & Daniels. PRL (2013)

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Generate Many Independent Configurations

particles float on an air table (microporous frit)

walls alternately create loose and dense packings

record particle positions

analyze high and low friction regions separately

Pist

on 1

Piston 2gravity

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Local Voronoï Volumes

Puckett & Daniels. PRL (2013)

3 example histograms (for subsystem only)

sample Voronoï tessellation

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Plot the Overlapping Histograms

Puckett & Daniels. PRL (2013)

logP (V 1)

P (V 2)=const.+V ( 1

X 2

−1

X 1)

log

slope difference in compactivity→

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Compactivity Fails to Equilibratered (low-friction system) and black (high-friction bath) do not

have the same compactivity

Puckett & Daniels PRL 2013

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Summary so Far

compactivity can be measured using two methods: “specific heat” or “overlapping histograms”

compactivity increases as packing fraction decreases

does compactivity behave like a temperature? equilibration?

useful state variable?

Questions ? ! ? !

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Summary so Far

compactivity can be measured using two methods: “specific heat” or “overlapping histograms”

compactivity increases as packing fraction decreases

does compactivity behave like a temperature? equilibration?

useful state variable?

compactivity just considers volume: what about the pressure/stress?

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Including Forces

Newton, Principia

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Force Network Ensemble

Snoeijer, van Hecke, Somfai, van Saarloos. PRE (2004)Tighe, Snoeijer, Vlugt, van Hecke. Soft Matter (2010)

many possible arrangements of forces, for the same set of particle positions

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Quantifying Interparticle Forces

d mn

f mn

particle m

particle n

Σ=∑m ,n

d mn f mn

force moment tensor:

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Angoricity α force moment tensor: sum over all interparticle

contact positions and forces:

Σ plays the role of Ε in the Boltzmann ensemble (is extensive, but now also tensorial)

its associated intensive parameter is angoricity (means “stress” in modern Greek)

Σ=∑m ,n

d mn f mn

αμ λ=(∂ S ( Σμλ)∂ Σμλ

)no reciprocal!

Edwards. Physica A. (2005) Blumenfeld & Edwards. J. Phys. Chem. (2009) Metzger. PRE (2008)Henkes, O'Hern, Chakraborty. PRL (2007) PRE (2009) Tighe, van Eerd, Vlugt. PRL (2008)

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Summary

Bi, Henkes, Daniels, Chakraborty. Ann. Rev. Cond. Matt. (2015). arXiv: 1404.1854

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Angoricity a Tensor

for a 2D granular system:

force moment tensor is 2×2 matrix:

has two eigenvalues: Σ1 and Σ2

– pressure:

– shear:

each component has its own angoricity

α p=∂ S (Σ p)

∂ Σ pατ=

∂ S (Στ )∂ Στ

Σ=∑ d mn f mn

Σ p=12 (Σ1+Σ2 )=Tr Σ

Σ τ=12 (Σ1−Σ2 )

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Example 1: 2D Simulations (Microcanonical)

2D simulations of frictionless, deformable grains prepare system at different pressures

no tangential forces → Στ = 0

calculate angoricity α using overlapping histogram method

Henkes, O’Hern, Chakraborty. PRL (2007)

Γ=Σ p=Tr Σ

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Equilibration & Equation of State

angoricity doesn't depend on patch size (equilibration within a single system)

equation of state: 1/α = ½ Γ

a configuration entropy estimate gives slope ~ 2/ ziso

Henkes, O’Hern, Chakraborty. PRL (2007)

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Pist

on

Pistongravity

Example 2: 2D Experiments (Canonical)

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Test the “Zeroth Law”

Zeroth lawrequires

temperatureequilibration

Does Xbath = Xsubsys

bath = subsys

?

lowfriction

highfriction

Puckett & Daniels. PRL (2013)

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polarizer¼ wave

camera

air

porous

LED

photoelastic diskmirrored surface

James Puckett

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3 lighting schemes

white light

particle positions

polarized light

contact forces

fluorescence

identify low-friction

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Measuring contact forces

http://nile.physics.ncsu.edu/pub/download/peDiscSolve/

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Angoricity Equilibrates!

Γ=Tr ΣPuckett & Daniels PRL 2013

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“Specific Heat” vs. “Overlapping Histograms”

d ⟨Γ ⟩dα

=1α

2 ⟨d Γ2⟩

Puckett & Daniels PRL 2013

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What's the Difference?volume ensemble compactivity → X fails to equilibrate volume is only conserved globally

stress ensemble angoricity → α successfully equilibrates Newton's 3rd Law: forces and torques

balance at each contact (local constraint)

Questions ? ! ? !

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Formal Aspects of the Stress Ensemble

d mn

f mn

particle m

particle n

Σ=∑m ,n

d mn f mn

force moment tensor:

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Constraints on Interparticle Forces

What do you know about the 5 black arrows?

Bi, Henkes, Daniels, Chakraborty. Ann. Rev. Cond. Matt. (2015). arXiv: 1404.1854

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Force Balance Tiles→

Bi, Henkes, Daniels, Chakraborty. Ann. Rev. Cond. Matt. (2015). arXiv: 1404.1854

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Represent Whole Packing in Force Space

moving this point corresponds to adjusting the contact forces

in a way that preserves force balance

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Forces Field Theory→

define a vector gauge field h(x, y) on the dual space of voids (, )

going counterclockwise around a grain, increment the height field by the contact force between the two voids:

Ball & Blumenfeld PRL (2002) DeGiuli & McElwaine PRE (2011) Henkes & Chakraborty PRL (2005) PRE (2009)

h∗= h+ f lm

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Relationship to Continuum Mechanics

forces are locally balanced is conserved→ Cauchy stress tensor can be calculated from the

height field: σ=∇× h

Σ=V σ

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Outstanding Questions

?

relationship to other temperature-like variables

the role of– friction

– particle shape

– shear vs. compression

systems with dynamics segregation

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What's “Temperature” in a Granular Material?

kinetic theory

entropy & energy

fluctuation-dissipation

k B T=12

m ⟨v−v 2 ⟩

1T=∂ S∂ E

C(t) = -kBT R(t)

Do these “temperatures” measure the same thing?Play a role in a useful equation of state?

Describe phase transitions?

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All 3 phases in coexistence

Forterre & Pouliquen Ann. Rev. Fluid Mech. (2008)

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The Role of Friction

count equations & constraints # of degrees of →freedom

friction – provides history-dependence

– changes the counting of valid states

Tighe, Snoeijer, Vlugt, van Hecke. Soft Matter (2010)

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Friction can cause non-convexity

Sarkar, Bi, Zhang, Behringer, Chakraborty. PRL (2013)Bi, Henkes, Daniels, Chakraborty. Ann. Rev. Cond. Matt. (2015). arXiv: 1404.1854

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Shear vs. Compression

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Forgotten Section: Segregation!

Edwards & Oakeshott. Physica A (1989)

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Segregation Spinodal Decomposition?↔