Unraveling the Mystery of Entropy Production

In summary, entropy production is a measure of disorder or randomness in a system and is closely related to the second law of thermodynamics. It is directly related to the conversion of energy and is influenced by factors such as temperature gradient, energy transfer rate, and efficiency. While it is typically irreversible, there are exceptions in biological systems. Entropy production has important implications in various fields and helps us understand the behavior of natural and human-made systems.
  • #1
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Hello,

So one presumes that [itex]J_i = \sum_j L_{ij} X_j[/itex] where J_i is the current for a certain variable x_i and X_j are the different kind of thermodynamical "forces". In the case of heat conduction, the "force" is temperature difference [itex]\nabla T[/itex] and the current J_i is a current of heat (Fourier's law! [itex]J = - \kappa \nabla T[/itex]).

One also presumes that for the entropy production [itex]\sigma = \frac{\mathrm d}{\mathrm dt} S = \sum_i X_i J_i [/itex] (*), so that together with the previous one gets that [itex]\sigma = \sum_{i,j} L_{ij} X_i X_j[/itex].

But anyway, how can (*) possibly be correct? After all, we also know that by the chain rule [itex]\frac{\mathrm d}{\mathrm dt} S = \sum_i \frac{\partial S}{\partial x_i} \frac{\mathrm d x_i}{\mathrm dt}[/itex] or by definition of current [itex]\frac{\mathrm d}{\mathrm dt} S = \sum_i \frac{\partial S}{\partial x_i} J_i[/itex] (**).

Comparing (*) and (**) would suggest that [itex]\boxed{ X_i = \frac{\partial S}{\partial x_i} }[/itex].

However, take again the case of heat conduction: [itex]x_i = E[/itex] (energy), hence [itex]\frac{\partial S}{\partial x_i} = \frac{1}{T}[/itex], but on the other hand, as claimed in my first paragraph: [itex]X_i = \nabla T[/itex]
But obviously [itex]\boxed{ \frac{\partial S}{\partial x_i} = \frac{1}{T} \neq \nabla T = X_i }[/itex]

Where is my misunderstanding?
 
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Hello,

You are correct in your understanding that J_i = \sum_j L_{ij} X_j and that for entropy production \sigma = \frac{\mathrm d}{\mathrm dt} S = \sum_i X_i J_i. However, the issue here is that the variables x_i and X_i are not the same. In the case of heat conduction, x_i represents energy while X_i represents the temperature gradient. So while \frac{\partial S}{\partial x_i} = \frac{1}{T} as you correctly stated, X_i = \nabla T is not the same as \frac{\partial S}{\partial x_i}. In fact, X_i is related to \frac{\partial S}{\partial x_i} through the relationship X_i = \frac{\partial S}{\partial x_i} \frac{\mathrm d x_i}{\mathrm dt}. So there is no contradiction between your understanding and the equations provided.

I hope this helps clarify any misunderstandings. Keep up the good work in understanding thermodynamics!
 

FAQ: Unraveling the Mystery of Entropy Production

What is entropy production?

Entropy production is a measure of the amount of disorder or randomness in a system. It is a fundamental concept in thermodynamics and is closely related to the second law of thermodynamics, which states that the total entropy of a closed system will always tend to increase over time.

How is entropy production related to energy?

Entropy production is directly related to the conversion of energy from one form to another. Whenever energy is converted from a high-quality form (such as chemical or mechanical energy) to a low-quality form (such as heat), entropy is produced. This is because the low-quality form has a higher degree of disorder or randomness.

What factors affect entropy production?

Entropy production is influenced by several factors, including the temperature gradient within a system, the rate of energy transfer, and the efficiency of the energy conversion process. In general, any process that involves the transfer or conversion of energy will result in some level of entropy production.

Can entropy production be reversed?

In most cases, entropy production cannot be reversed. This is because the second law of thermodynamics states that the total entropy of a closed system will always increase over time. However, there are some exceptions, such as in biological systems where living organisms are able to decrease their own entropy by taking in energy from their surroundings.

How is entropy production relevant to real-world applications?

Entropy production has important implications in many fields, including engineering, biology, and climate science. It helps us understand the efficiency of energy conversion processes, the direction of chemical reactions, and the behavior of complex systems. By studying entropy production, we can better understand and predict the behavior of natural and human-made systems.

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