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Entropy and the Second Law of Thermodynamics

Entropy and the Second Law of Thermodynamics

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...

The Second Law of Thermodynamics

The Second Law of Thermodynamics

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...

Entropy Change in Reversible Processes

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.

Second Law of Thermodynamics

Second Law of Thermodynamics

In the quest to identify a property that may reliably predict the spontaneity of a process, a promising candidate has been identified: entropy. Processes that involve an increase in entropy of the system (ΔS > 0) are very often spontaneous; however, examples to the contrary are plentiful. By expanding consideration of entropy changes to include the surroundings, a significant conclusion regarding the relation between this property and spontaneity may be reached. In thermodynamic...

Third Law of Thermodynamics

Third Law of Thermodynamics

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.

Standard Entropy Change for a Reaction

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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.

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Related Experiment Video

Updated: Oct 2, 2025

Bulk and Thin Film Synthesis of Compositionally Variant Entropy-stabilized Oxides

Bulk and Thin Film Synthesis of Compositionally Variant Entropy-stabilized Oxides

Published on: May 29, 2018

Entropy, Economics, and Criticality.

Michael S Harré¹

¹Complex Systems Research Group, Faculty of Engineering, The University of Sydney, Sydney 2006, Australia.

Entropy (Basel, Switzerland)

|February 25, 2022

Summary

Information theory, originating from Claude Shannon, offers tools for analyzing complex systems. This review explores its under-developed application in detecting non-linear phenomena within finance and economics.

Keywords:

criticality economics financial markets network theory non-linear dynamics non-stationary processes phase transitions tipping points

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Last Updated: Oct 2, 2025

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Area of Science:

Interdisciplinary science
Economics and Finance
Information Theory

Background:

Information theory, established over 70 years ago by Claude Shannon, has expanded beyond its initial scope.
It is now an interdisciplinary tool applied in neuroscience, AI, quantum mechanics, and astrophysics.

Purpose of the Study:

To provide a selective review of information theory's application in finance and economics.
To highlight its potential for understanding, modeling, and detecting non-linear phenomena in these fields.

Main Methods:

Selective review of existing literature.
Focus on information theory as a tool for non-linear phenomena analysis.

Main Results:

Information theory is under-utilized in finance and economics for non-linear phenomena.
Existing applications show promise but are not fully developed.

Conclusions:

The application of information theory in finance and economics has considerable scope for further development.
Further research is needed to fully leverage information theory for understanding non-linear financial and economic systems.