Thermodynamics AP Physics Chapter 15. Thermodynamics 13.3 Zeroth Law of Thermodynamics.
Introduction to Stochastic Thermodynamics: Application...
Transcript of Introduction to Stochastic Thermodynamics: Application...
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Introduction to Stochastic Thermodynamics: Introduction to Stochastic Thermodynamics: Application to Thermo- and Photo-electricity Application to Thermo- and Photo-electricity
in small devicesin small devices
Université Libre de Bruxelles
Massimiliano Esposito
Center for Nonlinear Phenomena and Complex Systems
Hasselt, October 2011
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Collaborators:Collaborators:
Bart Cleuren & Bob Cleuren, University of Hasselt, Belgium.
Ryoichi Kawai, University of Alabama at Birmingham, USA.
Katja Lindenberg, University of California San Diego, USA.
Shaul Mukamel, University of California Irvine, USA.
Christian Van Den Broeck, University of Hasselt, Belgium.
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Large fluctuations Small systems
Far from equilibrium(large surf/vol ratio)
Quantum effects(low temperatures)
Average behavior contains limited information
Higher moments or full probability distribution is needed
Linear response theories fail
Nonlinear response and nonperturbative methods
need to be developed
Traditional stochastic descriptions fail
Stochastic descriptions taking coherent effects
into account are needed
Challenges when dealing with small systemsChallenges when dealing with small systems
Stochastic thermodynamicsStochastic thermodynamics
Esposito, Harbola, Mukamel Rev. Mod. Phys. 81 1665 (2009)
Esposito, Lindenberg, Van den BroeckNJP 12 013013 (2010)
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OutlineOutline
I) Introduction to stochastic thermodynamics
A) From stochastic dynamics to nonequilibrium thermodynamics (at the level of averages)
B) The trajectory level and fluctuation theorems
II) Efficiency at maximum power A) Steady state (or autonomous) devices
B) Externally driven (or nonautonomous) devices
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I) Introduction to stochastic thermodynamics:I) Introduction to stochastic thermodynamics:
A) From stochastic dynamics to nonequilibrium A) From stochastic dynamics to nonequilibrium thermodynamics (at the level of averages)thermodynamics (at the level of averages)
Esposito, Harbola, Mukamel, PRE 76 031132 (2007)
Esposito, Van den Broeck, PRE 82 011143 & 011144 (2010)
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Markovian stochastic master equation
Each reservoir is always at equilibrium
“Local Detailed Balance”
Time-dependent rate matrix
Very slow external driving:
Stochastic dynamics of closed systemsStochastic dynamics of closed systems(i.e. energy but no particle exchange):
External driving force
ReservoirsSystem states
Steady state: No external driving:
1)
2)
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First law of thermodynamicsFirst law of thermodynamics
System energy:
Work: Heat:
Heat from reservoir :
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System entropy:
Second law of thermodynamicsSecond law of thermodynamics
Entropy flow: “Local detailed balance”
Measures the breaking of detailed balance
Entropy production:
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the stationary distribution satisfies detailed balance (i.e. equilibrium)
If all the reservoirs have the same thermodynamic properties
If the reservoirs have different thermodynamic properties
the stationary distribution breaks detailed balance
Autonomous system (i.e. no external driving):Autonomous system (i.e. no external driving):
Equilibrium Steady State
Nonequilibrium Steady State
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For a slow transformation (reversible transformation):
Nonautonomous system (i.e. externally driven)Nonautonomous system (i.e. externally driven)in contact with a single reservoir:in contact with a single reservoir:
For a fast transformation (irreversible transformation):
Clausius inequality
Integrated heat becomes a state function
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Thermodynamics emerges at the level of averages from an underlying stochastic dynamics
What did we gain?
Time scales
Finite time thermodynamics
Fluctuations
Fluctuation theoremsEfficiency at maximum power
Optimal work extraction
Trajectory level thermodynamics
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I) Introduction to stochastic thermodynamics:I) Introduction to stochastic thermodynamics:
B) The trajectory level and Fluctuation TheoremsB) The trajectory level and Fluctuation Theorems
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First Law:
Second Law:
Thermodynamics at the trajectory level:Thermodynamics at the trajectory level:
represents a singletrajectory (i.e. an history)
=0 if detail balance is satisfied
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Fluctuation theorem:
Entropy production:
Symmetry relations betweennonlinear coefficients
Fluctuation theoremsFluctuation theorems
Crooks J.Stat.Phys. 90 1481 (1998) & PRE 60 2721 (1999)
Jarzynski PRL 78 2690 (1997) Andrieux, Gaspard JSTAT P01011 (2006)Esposito, Harbola, Mukamel PRB 75 155316 (2007)
Current FT:Work FT:
Andrieux, Gaspard JSM P02006
General formulation: Esposito, Van den Broeck, PRL 104 090601 (2010)
Seifert PRL 95 040602 (2005)
Review: Esposito, Harbola, Mukamel, Rev. Mod. Phys. 81 1665 (2009)
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II) Efficiency at maximum powerII) Efficiency at maximum power
A) Steady state (or autonomous) devicesA) Steady state (or autonomous) devices
(i.e. no external time-dependent driving)
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Open systems: energy and matter echangeOpen systems: energy and matter echange
Heat:
Local Detailed Balance
Entropy flow
Energy current Matter current
different reservoirs
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At steady stateAt steady state
Power:
Energy and matter conservation at steady state:
Entropy conservation at steady state
Fluxes: Forces:
Entropy production:
Entropy and matter conservation at steady state
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Efficiency:
Work extracted from the system
Heat extracted from the hot reservoirThermal machines:
Efficiency of thermal machinesEfficiency of thermal machines
Carnot efficiency
where
since
only at equilibrium:
Therefore and
Generically (but not always!) this will require:
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Constant (independent of the thermodynamic forces)
Current Independent
efficiency
Collapse of forces
Tight couplingTight coupling
is reached at equilibrium and leads to finite value of
But we still have that because at equilibrium
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Linear response:
Maximum power vs leads to
Efficiency at maximum power in the linear regimeEfficiency at maximum power in the linear regime
Strong couplingcase
Strong couplingcase
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Van den Broeck, PRL 95, 190602 (2005)
Esposito, Lindenberg, Van den Broeck, PRL 102, 130602 (2009)
I. I. Novikov & P. Chambadal (1957) ; F. Curzon and B. Ahlborn, Am. J. Phys. 43, 22 (1975).
Linear Nonlinear(in presence of a
left-right symmetry)
Seifert, PRL 106, 020601 (2011)
Not too far from equilibrium:
Far from equilibrium:
Phenomenologically:
tight coupling
Efficiency at maximum power beyond linear regimeEfficiency at maximum power beyond linear regime
Study of model systems Everything is possible
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Application: Thermoelectric single level quantum dotApplication: Thermoelectric single level quantum dotM.E., Lindenberg, Van den Broeck, EPL 85, 60010 (2009)
Fermi distribution
1: empty electronic level2: filled electronic level
Two states:
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Maximum power:
Change of variable:
Details of the calculationDetails of the calculation
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One can prove perturbatively:
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Application: Photoelectric nanocellApplication: Photoelectric nanocellRutten, Esposito, Cleuren, PRB 80, 235122 (2009)
Fermi distribution
Bose distribution
Three states(two electronic levels l & r)
0 : l and r emptyr : r filled and l empty l : r empty and l filled
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Steady state currents:
Power:
Efficiency:
Forces:
Entropy production:
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Maximum power vs
Tight coupling
No tight coupling
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II) Efficiency at maximum powerII) Efficiency at maximum power
B) Externally driven (or nonautonomous) devicesB) Externally driven (or nonautonomous) devices
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Finite time Carnot cycleFinite time Carnot cycle
for reversible cycle
Carnot efficiencyEfficiency:
Power:
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Maximize power vs and :
Extracted power:
Assumptions:
- cycle with a proper reversible limit - weak dissipation
- instantaneous adiabatic step
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Curzon-Ahlborn in the symmetric dissipation:
M.E., Kawai, Lindenberg, Van den Broeck, PRL 105 150603 (2010)
Expansion in :
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is the dot occupation probability
Application: Driven quantum dotApplication: Driven quantum dot
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M.E., Kawai, Lindenberg, Van den Broeck ,EPL 89, 20003 (2010).
The optimal protocol contains an initial and final jump!
Optimal work extractionOptimal work extraction
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Efficiency of the finite-time Carnot cycleEfficiency of the finite-time Carnot cycle
M.E., Kawai, Lindenberg, Van den Broeck, Phys. Rev. E 81, 041106 (2010).
In the low dissipation regimeefficiency at maximum power:
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ConclusionsConclusions
● It can be used to study finite time thermodynamics
- Efficiencies: Tight coupling and Curzon-Ahlborn efficiency
- Optimal work extraction: jumps in the protocol
● It can be used to study fluctuations around average behaviors
- Fluctuation theorems, ...
● Further directions: quantum effects, feedbacks and information...
● Stochastic thermodynamics is a natural and powerful tool to study small systems: