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Related Concept Videos

The Entropy as a State Function01:14

The Entropy as a State Function

Consider an arbitrary process that moves between two specific states (A and B) in a cyclic manner. This process is reversible and broken down into smaller parts that each follow a Carnot cycle. A Carnot cycle has two isothermal (constant temperature) processes. During these processes, the ratio of the amount of heat transferred to their respective temperature remains constant. The other two processes in the Carnot cycle are also reversible but adiabatic, which means they occur without any heat...
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

In the Carnot engine, which achieves the maximum efficiency between two reservoirs of fixed temperatures, the total change in entropy is zero. The observation can be generalized by considering any reversible cyclic process consisting of many Carnot cycles. Thus, it can be stated that the total entropy change of any ideal reversible cycle is zero.
The statement can be further generalized to prove that entropy is a state function. Take a cyclic process between any two points on a p-V diagram.
State Function, Exact and Inexact Differentials01:27

State Function, Exact and Inexact Differentials

A state function is a thermodynamic property that depends solely on the current state of a system, irrespective of its history or how it arrived at that state. These functions are represented by capital letters, such as U, H, and S, which stand for internal energy, enthalpy, and entropy, respectively.For instance, the value of internal energy depends on the system's state variables and remains unaffected by the process path. This means that whether the system underwent a linear process or a...
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Theories of Dissolution: The Danckwerts' Model and Interfacial Barrier Model

Various dissolution theories provide insight into the factors that influence the dissolution rate. Danckwerts' Model suggests that turbulence, rather than a stagnant layer, characterizes the dissolution medium at the solid-liquid interface. In this model, the agitated solvent contains macroscopic packets that move to the interface via eddy currents, facilitating the absorption and delivery of the drug to the bulk solution. The regular replenishment of solvent packets maintains the concentration...
Reynolds Transport Theorem01:24

Reynolds Transport Theorem

The Reynolds transport theorem provides a framework to relate the time rate of change of an extensive property within a system to that in a control volume, which is crucial for analyzing fluid dynamics. Extensive properties, such as mass, velocity, acceleration, temperature, and momentum, can be expressed in terms of the mass of a fluid portion. These properties are called extensive because they depend on the system's size, while intensive properties are their corresponding values per unit mass.
Carrier Transport01:21

Carrier Transport

The generation of electrical current in semiconductors is fundamentally driven by two mechanisms: drift and diffusion. These processes are essential for the functionality and performance of semiconductor-based devices.
Drift Current:
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An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
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The covariant dissipation function for transient nonequilibrium states.

Denis J Evans1, Debra J Searles, Stephen R Williams

  • 1Research School of Chemistry, Australian National University, Canberra, Australian Capital Territory 0200, Australia.

The Journal of Chemical Physics
|August 17, 2010
PubMed
Summary
This summary is machine-generated.

The covariant dissipation function, crucial in nonequilibrium statistical mechanics, relates simply to the initial dissipation function. Exact time-local fluctuation relations for deterministic systems do not exist, only asymptotic versions.

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Area of Science:

  • Statistical Mechanics
  • Physical Chemistry
  • Thermodynamics

Background:

  • The dissipation function is central to classical nonequilibrium statistical mechanics.
  • It underpins key theorems like the Evans-Searles fluctuation theorem.

Purpose of the Study:

  • To investigate how the dissipation function changes when defined with respect to a time-evolving distribution during relaxation.
  • To explore the relationship between this covariant dissipation function and the initial dissipation function.

Main Methods:

  • Theoretical analysis of the dissipation function in classical nonequilibrium statistical mechanics.
  • Mathematical derivation of relationships between different definitions of the dissipation function.

Main Results:

  • A simple, fixed relationship was found between the covariant dissipation function and the initial dissipation function.
  • Exact, time-local Evans-Searles fluctuation relations for deterministic systems were shown to be non-existent, with only asymptotic versions possible.

Conclusions:

  • The covariant dissipation function offers a simplified perspective on nonequilibrium statistical mechanics.
  • The findings clarify the limitations of exact fluctuation relations in deterministic systems.