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Entropy is one of the few quantities in the physical sciences that require a particular direction for time, sometimes called an arrow of time. As one goes "forward" in time, the second law of thermodynamics says, the entropy of an isolated system can increase, but not decrease. Thus, entropy measurement is a way of distinguishing the past from ...
The T-V diagram of the rubber band experiment. The decrease in the temperature of the rubber band in a spontaneous process at ambient temperature can be explained using the Helmholtz free energy = where dF is the change in free energy, dL is the change in length, τ is the tension, dT is the change in temperature and S is the entropy.
The relationship between entropy, order, and disorder in the Boltzmann equation is so clear among physicists that according to the views of thermodynamic ecologists Sven Jorgensen and Yuri Svirezhev, "it is obvious that entropy is a measure of order or, most likely, disorder in the system."
For example, in the Carnot cycle, while the heat flow from a hot reservoir to a cold reservoir represents the increase in the entropy in a cold reservoir, the work output, if reversibly and perfectly stored, represents the decrease in the entropy which could be used to operate the heat engine in reverse, returning to the initial state; thus the ...
The maximum entropy principle: For a closed system with fixed internal energy (i.e. an isolated system), the entropy is maximized at equilibrium. The minimum energy principle: For a closed system with fixed entropy, the total energy is minimized at equilibrium.
Mathematically, the absolute entropy of any system at zero temperature is the natural log of the number of ground states times the Boltzmann constant k B = 1.38 × 10 −23 J K −1. The entropy of a perfect crystal lattice as defined by Nernst's theorem is zero provided that its ground state is unique, because ln(1) = 0.
Roughly, the fluctuation theorem relates to the probability distribution of the time-averaged irreversible entropy production, denoted ¯.The theorem states that, in systems away from equilibrium over a finite time t, the ratio between the probability that ¯ takes on a value A and the probability that it takes the opposite value, −A, will be exponential in At.
An example of such an exchange would be an isentropic expansion or compression that entails work done on or by the flow. For an isentropic flow, entropy density can vary between different streamlines. If the entropy density is the same everywhere, then the flow is said to be homentropic.