Entropy | Wikipedia audio article
Channel: wikipedia tts
Date: 2018-12-24

This is an audio version of the Wikipedia Article:
https://en.wikipedia.org/wiki/Entropy


00:02:55 1 History
00:06:00 2 Definitions and descriptions
00:07:34 2.1 Function of state
00:08:43 2.2 Reversible process
00:09:50 2.3 Carnot cycle
00:14:54 2.4 Classical thermodynamics
00:19:03 2.5 Statistical mechanics
00:25:39 2.6 Entropy of a system
00:29:50 3 Second law of thermodynamics
00:32:37 4 Applications
00:32:47 4.1 The fundamental thermodynamic relation
00:34:22 4.2 Entropy in chemical thermodynamics
00:36:34 4.3 Entropy balance equation for open systems
00:37:03 5 Entropy change formulas for simple processes
00:41:52 5.1 Isothermal expansion or compression of an ideal gas
00:42:12 5.2 Cooling and heating
00:43:55 5.3 Phase transitions
00:47:07 6 Approaches to understanding entropy
00:48:26 6.1 Standard textbook definitions
00:48:45 6.2 Order and disorder
00:49:36 6.3 Energy dispersal
00:51:39 6.4 Relating entropy to energy iusefulness/i
00:53:06 6.5 Entropy and adiabatic accessibility
00:53:59 6.6 Entropy in quantum mechanics
00:56:07 6.7 Information theory
00:57:58 6.8 Experimental measurement of entropy
01:01:26 7 Interdisciplinary applications of entropy
01:03:24 7.1 Thermodynamic and statistical mechanics concepts
01:03:58 7.2 The arrow of time
01:06:02 7.3 Cosmology
01:06:35 7.4 Economics
01:08:40 8 See also
01:09:41 9 Notes



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SUMMARY
=======
In statistical mechanics, entropy is an extensive property of a thermodynamic system. It is closely related to the number Ω of microscopic configurations (known as microstates) that are consistent with the macroscopic quantities that characterize the system (such as its volume, pressure and temperature). Under the assumption that each microstate is equally probable, the entropy 
  
    
      
        S
      
    
    {\displaystyle S}
   is the natural logarithm of the number of microstates, multiplied by the Boltzmann constant kB. Formally,

  
    
      
        S
        =
        
          k
          
            
              B
            
          
        
        ln
        ⁡
        Ω
        
           (assuming equiprobable microstates)
        
        .
      
    
    {\displaystyle S=k_{\mathrm {B} }\ln \Omega {\text{ (assuming equiprobable microstates)}}.}
  Macroscopic systems typically have a very large number Ω of possible microscopic configurations.  For example, the entropy of an ideal gas is proportional to the number of gas molecules N.  Roughly twenty liters of gas at room temperature and atmospheric pressure has N ≈ 6×1023 (Avogadro's number).  At equilibrium, each of the Ω ≈ eN configurations can be regarded as random and equally likely. 
The second law of thermodynamics states that the entropy of an isolated system never decreases. Such systems spontaneously evolve towards thermodynamic equilibrium, the state with maximum entropy. Non-isolated systems may lose entropy, provided  their environment's entropy increases by at least that amount so that the total entropy increases. Entropy is a function of the state of the system, so the change in entropy of a system is determined by its initial and final states. In the idealization that a process is reversible, the entropy does not change, while irreversible processes always increase the total entropy.
Because it is determined by the number of random microstates, entropy is related to the amount of additional information needed to specify the exact physical state of a system, given its macroscopic specification. For this reason, it is often said that entropy is an expression of the disorder, or randomness of a system, or of the lack of information about it. The concept of entropy plays a central role in information theory.
Boltzmann's constant, and therefore entropy, have dimensions of energy divided by temperature, which has a unit of joules per kelvin (J K−1) in the International System of Units (or kg m ...