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Related Concept Videos

Entropy02:39

Entropy

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...
Entropy01:18

Entropy

The first law of thermodynamics is quantitatively formulated via an equation relating the internal energy of a system, the heat exchanged by it, and the work done on it. A quantitative formulation of the second law of thermodynamics leads to defining a state function, the entropy.
When an ideal gas expands isothermally, the disorder in the gas increases. From the molecular perspective, the gas molecules have more volume to move around in.
Consider an infinitesimal step in the expansion, which...
Entropy and the Second Law of Thermodynamics01:20

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...
Entropy and the Second Law of Thermodynamics01:26

Entropy and the Second Law of Thermodynamics

Consider an isolated system in which a hot object is placed in contact with a cold one. This is an irreversible process that eventually leads both objects to reach the same equilibrium temperature. It is crucial to note that the constituents of any substance exhibit increased disorder at higher temperatures. As a cold substance absorbs heat, its constituents become more disordered. The energy transfer from a hotter object to a cooler one increases the system's disorder or randomness. This...
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.
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...

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An Analog Macroscopic Technique for Studying Molecular Hydrodynamic Processes in Dense Gases and Liquids
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Many faces of entropy or Bayesian statistical mechanics.

Evgeni B Starikov1

  • 1Institute for Materials Science and Max Bergmann Center of Biomaterials, Dresden University of Technology, 01062 Dresden, Germany. starikow@chemie.fu-berlin.de

Chemphyschem : a European Journal of Chemical Physics and Physical Chemistry
|September 25, 2010
PubMed
Summary

George Linhart derived a general formula for heat capacity versus temperature using a Bayesian approach to probability. His work, though forgotten, offers a fresh perspective on thermodynamics and statistical physics.

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Area of Science:

  • Thermodynamics
  • Statistical Physics
  • Physical Chemistry

Background:

  • George Linhart's 80-90 year old work on heat capacity is largely forgotten.
  • His formula predates and differs from approaches by Einstein, Debye, Planck, and Nernst.

Purpose of the Study:

  • To re-evaluate Linhart's forgotten thermodynamic formula.
  • To highlight its potential implications for academic and applied science.

Main Methods:

  • Derivation of a general mathematical formula for heat capacity versus temperature from fundamental thermodynamic principles.
  • Application of a "Bayesian approach to probability" (as termed now).

Main Results:

  • Successful fitting of experimental data for diverse solid-state substances over a broad temperature range.
  • A simple yet general formula for heat capacity.

Conclusions:

  • Linhart's work offers a valid and novel standpoint in thermodynamics and statistical physics.
  • The formula's potential significance for both theoretical and practical scientific applications warrants its revival.