Temperature Scales

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					                              Physics 334
                             Modern Physics




Credits: Material for this PowerPoint was adopted from Rick Trebino’s lectures from Georgia Tech which were based on
the textbook “Modern Physics” by Thornton and Rex. Many of the images have been used also from “Modern Physics” by
Tipler and Llewellyn, others from a variety of sources (PowerPoint clip art, Wikipedia encyclopedia etc), and contributions
are noted wherever possible in the PowerPoint file. The PDF handouts are intended for my Modern Physics class, as a
study aid only.
Chapter 2 Statistics and Thermodynamics

•   Why Statistics
•   Probability Distribution
•   Gaussian Distribution Functions
•   Temperature and Ideal Gas
•   The Maxwell-Boltzmann Distribution
•   Density of States
What has Statistics to do with Modern Physics

In physics and engineering courses we talk about motion of
baseballs, airplanes, rigid bodies etc. These descriptions are from a
macroscopic point of view

In Kinetic theory of gases, the macroscopic properties of gases for
example, pressure, volume and temperature are based on
microscopic motion of molecules and atoms that make up the gas.

All matter is made of atoms and molecules, so it make sense to talk
about macroscopic quantities in light of microscopic quantities.
Therefore it is necessary to combine mechanics (classical or
quantum) with statistics. This is called Statistical Mechanics.

The main concept that will be used is the concept of probabilities,
since in quantum mechanics the interest is in measuring the
probabilities of a physical quantity (position, momentum, energy etc.)
        Probability Distribution Function
A distribution function f(x) or Ф(x) is a function that gives
the probability of the particle found in a certain range of
allowed values of an event.

An event is an act of making a measurement of an
observable. Say if our measurement is of position x than
the probability function of finding the particle in the range
x and x+dx is
                             P( xi )
                     ( x)           , for discrete variable xi
                               xi
                              dP( x )
                      ( x)          , for continuous variable x
                               dx
                              dP( x )            P( xi ) 
                     where              lim              
                               dx        xi 0
                                                  xi 
               Probability Calculations
The probability of finding the particle is given by
                  f              f
P( x1  x  x2 )=   ( xk )x   P ( xi ) for discrete variable xi
                 k i           k i
                 xf
P( x1  x  x2 )=   ( x )dx, for continuous variable x
                 xi

where the region is defined between x i and x f
                          Normalization
The particle has to be some where. Normalization
means that the sum or integral should be equal to 1.

                    
P(  x  )=  P( xi )=1 for discrete variable xi
                  k 
                  +
P(  x  )=   ( x)dx  1, for continuous variable x
                   -

un normalized distribution functions can always be normalized
For a 1-D function of x, the normalization condition is

  * ( x) ( x)dx  1
                           Normalization
Example: Find the normalizing constant A for the
function
                             x 
               ( x)  A sin  
                              a 

  * ( x) ( x)dx  1
          x 
a
                    2 1
   A sin   dx  A a  1
     2    2

0          a        2
   2
A
   a
                Expectation (Average) Value
Average value of a physical quantity is called expectation
value. If several measurements are made, the value that
is expected on the average is the expectation value even
though no single measurement may be the expectation
value. This is also the mean value.
           
 x =x =  xi P( xi )=1 for discrete variable xi
          i 
           +
 x =x =     
          i - 
                   x ( x)dx  1, for continuous variable x
                        Expectation Value
Example: Find the expectation value of the function


         2 x 
 ( x)  sin  
         a  a 

      
 x    * ( x) x ( x)dx
      

            2 x 
      a
       2              a
 x   x sin   dx 
     0
       a       a    2
                                    Standard Deviation
Standard deviation (σ) tells us how much deviation to
expect from the average value. Variance (σ2) also gives
us the spread.
                                   
                                                  Pi
    xi  x                    ( xi  x )2
                  2
                                                      = for discrete variable xi
                                  i            xi
                                  
                                          dP
    xi  x              dx( x  x )
                  2                           2
                                             , for continuous variable x
                            
                                          dx
  (x  x )  x  x
 2           2                2           2



             x  x
      2               2             2
              Gaussian Distribution
Binomial distribution, Gaussian
distribution and Poisson
distribution are the most
common distributions               Star
encountered in physics.            t




We will discuss only the                  x

Gaussian distribution as it
occurs widely and is used in
many different fields. Gaussian
distribution is also called Bell
curve or standard distribution.

Consider a drunk undergoing a
random walk.
               Gaussian Distribution
Displacement is the sum of several random steps. The
probability of small steps to cancel each other out is
greater than the probability of large steps which might be
in the same direction.

The distribution function is given as


                    1
      ( x)                 e    ( x  a )2
                                                (2 )
                                                   2

                  2    2
                           Bell Curve
The solid green line shows that
1. The “most probable” value (peak) is at x=25
2. The median (50% level) is at x=25
3. The mean is at x=25
σ=6
Red dash line                                           Gaussian Distribution


x- σ<x<x+σ                         0.07



The probability of                 0.06



the particle to be in              0.05



this region is 68.3%
                     Probability




                                   0.04



Purple dash line                   0.03



x- 2σ<x<x+2σ                       0.02



The probability of                 0.01



the particle to be in                0
                                          0   5   10   15    20     25    30    35   40   45   50

this region is 95%                                                  x
Thermal Physics
Thermal physics is the study of
  •   Temperature
  •   Heat
  •   How these affect matter
  •   How heat is transferred between systems and to the
      environment
Heat
It is a process in which energy is exchanged because of
temperature differences.

Thermal Contact
Objects are said to be in thermal contact if energy can be
exchanged between them.

Thermal Equilibrium
Energy cease to exchange between objects
 Zeroth Law of Thermodynamics




If objects A and B are separately in thermal equilibrium
with a third object, C, then A and B are in thermal
equilibrium with each other.
Allows a definition of temperature

Temperature is the property that determines whether or not an
object is in thermal equilibrium with other objects
Thermometers


Used to measure the temperature of an object or a
 system
Make use of physical properties that change with
 temperature
Many physical properties can be used
  volume of a liquid
  length of a solid
  pressure of a gas held at constant volume
  volume of a gas held at constant pressure
  electric resistance of a conductor
  color of a very hot object
Thermometers, cont


A mercury thermometer is
an example of a common
thermometer
The level of the mercury
rises due to thermal
expansion
Temperature can be
defined by the height of the
mercury column
Temperature Scales

 Thermometers can be calibrated by placing them in thermal
 contact with an environment that remains at constant
 temperature
   Environment could be mixture of ice and water in thermal
   equilibrium
   Also commonly used is water and steam in thermal equilibrium
Celsius Scale


Temperature of an ice-water mixture is defined as
  0º C
  This is the freezing point of water
Temperature of a water-steam mixture is defined
  as 100º C
  This is the boiling point of water
Distance between these points is divided into 100
  segments or degrees
Fahrenheit Scales

Most common scale used in the US
Temperature of the freezing point is 32º
Temperature of the boiling point is 212º
180 divisions between the points
Kelvin Scale


When the pressure of a gas goes to zero, its
  temperature is –273.15º C
This temperature is called absolute zero
This is the zero point of the Kelvin scale
  –273.15º C = 0 K
To convert: TC = TK – 273.15
  The size of the degree in the Kelvin scale is the same as
    the size of a Celsius degree
 Pressure-Temperature Graph


All gases extrapolate to
the same temperature at
zero pressure
This temperature is
absolute zero
Modern Definition of Kelvin Scale


Defined in terms of two points
  Agreed upon by International Committee on Weights and
    Measures in 1954
First point is absolute zero
Second point is the triple point of water
  Triple point is the single point where water can exist as
     solid, liquid, and gas
  Single temperature and pressure
  Occurs at 0.01º C and P = 4.58 mm Hg
Modern Definition of Kelvin Scale, cont

The temperature of the triple point on the Kelvin scale is 273.16
  K
Therefore, the current definition of the Kelvin is defined as
  1/273.16 of the temperature of the triple point of water
Some Kelvin
Temperatures

Some representative
Kelvin temperatures
Note, this scale is
logarithmic
Absolute zero has
never been reached
Comparing Temperature Scales
Converting Among Temperature Scales



       TC  TK  273.15
           9
       TF  TC  32
           5
           5
       TC  TF  32 
            9
              9
       TF  TC
              5
Temperature and Kinetic Energy
The average kinetic energy of a molecule in thermal equilibrium
with its surrounding is given by
     3
 Ek  kT , where k is the Boltzmann constant = 8.617 10-5eV / K
     2

Example
Calculate the average kinetic energy of a gas molecule at room
temperature T=20 degree Celsius
T  20  273  293K
        3     3
 Ek      kT  (8.62 105 eV / K )(293K )  0.038eV
        2     2
It is useful to remember that at room temperature of 300 K the
value of kT is
                      1
kT  0.02585eV          eV
                      40
Ideal Gas
A gas does not have a fixed volume or pressure
In a container, the gas expands to fill the container
Most gases at room temperature and pressure behave
approximately as an ideal gas.

Exercise: Consider a container of gas that has a volume V in
thermal equilibrium at a temperature T. Show that the pressure P
is given by PV=NkT, where N is the Avogadro's number and k is
the Boltzmann constant.

Example: Calculate the volume occupied by one mole of
molecules at a pressure of one atmosphere (1.01x105N/m2) and
a temperature of 273 K. This condition is called Standard
Temperature and Pressure (STP)
Ideal Gas
Example: Calculate the volume occupied by one mole of
molecules at a pressure of one atmosphere (1.01x105N/m2) and
a temperature of 273 K. This condition is called Standard
Temperature and Pressure (STP).
    N A kT
V
      P
At T=273, the value of kT is
               273K 
kT  (0.0585)          0.0235 K
               300 K 
     (6.02 1023 )(0.0235eV )           19
V                             (1.60 10 J / eV )  0.0224m
                                                              3

         1.01105 N / m 2     
V  22.4 liters

				
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posted:11/27/2012
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