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Related Concept Videos

Entropy02:39

Entropy

30.1K
Salt particles that have dissolved in water never spontaneously come back together in solution to reform solid particles. Moreover, a gas that has expanded in a vacuum remains dispersed and never spontaneously reassembles. The unidirectional nature of these phenomena is the result of a thermodynamic state function called entropy (S). Entropy is the measure of the extent to which the energy is dispersed throughout a system, or in other words, it is proportional to the degree of disorder of a...
30.1K
Entropy and the Second Law of Thermodynamics01:20

Entropy and the Second Law of Thermodynamics

2.8K
The second law of thermodynamics can be stated quantitatively using the concept of entropy. Entropy is the measure of disorder of the system.
The relation  between entropy and disorder can be illustrated with the example of the phase change of ice to water. In ice, the molecules are located at specific sites giving a solid state, whereas, in a liquid form, these molecules are much freer to move. The molecular arrangement has therefore become more randomized. Although the change in average...
2.8K
The Second Law of Thermodynamics01:14

The Second Law of Thermodynamics

5.3K
In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Scientists refer to the measure of randomness or disorder within a system as entropy. High entropy means high disorder and low energy. To better understand entropy, think of a student’s bedroom. If no energy or work were put into it, the room would quickly become messy. It would exist in a very disordered state, one of high entropy. Energy must be...
5.3K
Standard Entropy Change for a Reaction03:00

Standard Entropy Change for a Reaction

20.3K
Entropy is a state function, so the standard entropy change for a chemical reaction (ΔS°rxn) can be calculated from the difference in standard entropy between the products and the reactants.
20.3K
Third Law of Thermodynamics02:38

Third Law of Thermodynamics

18.9K
A pure, perfectly crystalline solid possessing no kinetic energy (that is, at a temperature of absolute zero, 0 K) may be described by a single microstate, as its purity, perfect crystallinity,and complete lack of motion means there is but one possible location for each identical atom or molecule comprising the crystal (W = 1). According to the Boltzmann equation, the entropy of this system is zero.
18.9K
Entropy Change in Reversible Processes01:10

Entropy Change in Reversible Processes

2.5K
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.
2.5K

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A Simple, Low-cost, and Robust System to Measure the Volume of Hydrogen Evolved by Chemical Reactions with Aqueous Solutions
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Methods to Calculate Entropy Generation.

Jude A Osara1, Michael D Bryant2,3

  • 1Surface Technology and Tribology, Department of Mechanics of Solids, Surfaces and Systems, University of Twente, 7522 NB Enschede, The Netherlands.

Entropy (Basel, Switzerland)
|March 28, 2024
PubMed
Summary
This summary is machine-generated.

This study introduces a universal Phenomenological Entropy Generation (PEG) theorem, simplifying thermodynamic principles. The PEG theorem offers accurate system characterization for design, analysis, and optimization across diverse applications.

Keywords:
entropy generationnon-equilibrium thermodynamicsphenomenologysecond lawthermodynamic potentials

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Area of Science:

  • Thermodynamics
  • Physical Chemistry
  • Materials Science

Background:

  • Entropy generation is crucial for understanding irreversible processes.
  • Existing models often lack universality and convenience.
  • Combining the first and second laws of thermodynamics with potentials is key.

Purpose of the Study:

  • To introduce a universal theorem for entropy generation.
  • To simplify thermodynamic principles for accurate system modeling.
  • To provide a unified framework for analyzing diverse systems.

Main Methods:

  • Formulating entropy generation as the difference between phenomenological and reversible entropy functions.
  • Evaluating phenomenological entropy via real-time state measurements.
  • Calculating reversible entropy along ideal paths.
  • Developing models for various system classes using thermodynamic potentials.

Main Results:

  • Introduction of the universal Phenomenological Entropy Generation (PEG) theorem.
  • Development of convenient and accurate system governing equations and characterization models.
  • Demonstration of the method's applicability on frictional wear, grease degradation, battery cycling, metal fatigue, and pump flow.

Conclusions:

  • The PEG theorem provides a unified approach to entropy generation.
  • The presented methods enable accurate design, analysis, and diagnostic monitoring.
  • This framework supports optimization across a wide range of engineering systems.