Lecture 3
OUTLINE
• Semiconductor Fundamentals (cont’d)
– Thermal equilibrium
– Fermi-Dirac distribution
• Boltzmann approximation
– Relationship between EF and n, p
– Degenerately doped semiconductor
Reading: Pierret 2.4-2.5; Hu 1.7-1.10
Fluid Analogy
Conduction
Band
Valence
Band
EE130/230A Fall 2013
Lecture 3, Slide 2
Thermal Equilibrium
• No external forces are applied:
– electric field = 0, magnetic field = 0
– mechanical stress = 0
– no light
• Dynamic situation in which every process is balanced by
its inverse process
Electron-hole pair (EHP) generation rate = EHP recombination rate
• Thermal agitation  electrons and holes exchange
energy with the crystal lattice and each other
 Every energy state in the conduction band and valence band
has a certain probability of being occupied by an electron
EE130/230A Fall 2013
Lecture 3, Slide 3
Analogy for Thermal Equilibrium
Sand particles
C. C. Hu, Modern Semiconductor Devices for Integrated Circuits, Figure 1-17
• There is a certain probability for the electrons in the
conduction band to occupy high-energy states under
the agitation of thermal energy (vibrating atoms).
EE130/230A Fall 2013
Lecture 3, Slide 4
Fermi Function
• Probability that an available state at energy E is occupied:
f (E) 
1
1 e
( E  E F ) / kT
• EF is called the Fermi energy or the Fermi level
There is only one Fermi level in a system at equilibrium.
If E >> EF :
If E << EF :
If E = EF :
EE130/230A Fall 2013
Lecture 3, Slide 5
Effect of Temperature on f(E)
R. F. Pierret, Semiconductor Device Fundamentals, p. 46
EE130/230A Fall 2013
Lecture 3, Slide 6
Boltzmann Approximation
If E  EF  3kT , f ( E )  e
 ( E  EF ) / kT
If EF  E  3kT , f ( E )  1  e
( E  EF ) / kT
Probability that a state is empty (i.e. occupied by a hole):
1  f (E)  e
EE130/230A Fall 2013
( E  EF ) / kT
Lecture 3, Slide 7
e
 ( EF  E ) / kT
Equilibrium Distribution of Carriers
• Obtain n(E) by multiplying gc(E) and f(E)
Energy band
diagram
EE130/230A Fall 2013
Density of
States, gc(E)
×
Probability of
occupancy, f(E)
Lecture 3, Slide 8
cnx.org/content/m13458/latest
=
Carrier
distribution, n(E)
R. F. Pierret, Semiconductor Device Fundamentals, Figure 2.16
• Obtain p(E) by multiplying gv(E) and 1-f(E)
Energy band
diagram
EE130/230A Fall 2013
Density of
States, gv(E)
×
Probability of
occupancy, 1-f(E)
Lecture 3, Slide 9
=
cnx.org/content/m13458/latest
Carrier
distribution, p(E)
R. F. Pierret, Semiconductor Device Fundamentals, Figure 2.16
Equilibrium Carrier Concentrations
• Integrate n(E) over all the energies in the conduction
band to obtain n:
n
top of conductionband
Ec
g c(E)f(E)dE
• By using the Boltzmann approximation, and
extending the integration limit to , we obtain
3/ 2
*
 2mn , DOS kT 
 ( Ec  E F ) / kT

n  Nce
where N c  2
2

h


EE130/230A Fall 2013
Lecture 3, Slide 10
• Integrate p(E) over all the energies in the valence
band to obtain p:
p
Ev
bottomof valence band
gv(E)1  f(E)dE
• By using the Boltzmann approximation, and
extending the integration limit to -, we obtain
p  Nve
EE130/230A Fall 2013
 ( E F  Ev ) / kT
 2m
where N v  2

h

*
p , DOS
2
Lecture 3, Slide 11
kT 



3/ 2
Intrinsic Carrier Concentration

np  N c e
 ( Ec  EF ) / kT
N e
 ( EF  Ev ) / kT
v
 Nc Nve
( Ec  Ev ) / kT
 Nc Nve
ni  N c N v e

 EG / kT
n
 EG / 2 kT
Effective Densities of States at the Band Edges (@ 300K)
Si
Ge
GaAs
Nc (cm-3)
2.82 × 1019
1.05 × 1019
4.37 × 1017
Nv (cm-3)
1.83 × 1019
3.92 × 1018
8.12 × 1018
EE130/230A Fall 2013
Lecture 3, Slide 12
2
i
n(ni, Ei) and p(ni, Ei)
• In an intrinsic semiconductor, n = p = ni and EF = Ei
n  ni  N c e
 ( Ec  Ei ) / kT
 N c  ni e( Ec  Ei ) / kT
n  ni e
EE130/230A Fall 2013
p  ni  N v e
 ( Ei  Ev ) / kT
 N v  ni e( Ei  Ev ) / kT
( E F  Ei ) / kT
Lecture 3, Slide 13
p  ni e
( Ei  E F ) / kT
Intrinsic Fermi Level, Ei
• To find EF for an intrinsic semiconductor, use the fact that n = p:
Nce
 ( Ec  E F ) / kT
 Nve
 ( E F  Ev ) / kT
Ec  Ev kT  N v 
EF 
 ln    Ei
2
2  Nc 
Ec  Ev 3kT  m
Ei 

ln
2
4  m
*
p , DOS
*
n , DOS
EE130/230A Fall 2013
 Ec  Ev


2

Lecture 3, Slide 14
n-type Material
R. F. Pierret, Semiconductor Device Fundamentals, Figure 2.16
Energy band
diagram
EE130/230A Fall 2013
Density of
States
Probability
of occupancy
Lecture 3, Slide 15
Carrier
distributions
Example: Energy-band diagram
Question: Where is EF for n = 1017 cm-3 (at 300 K) ?
EE130/230A Fall 2013
Lecture 3, Slide 16
Example: Dopant Ionization
Consider a phosphorus-doped Si sample at 300K with ND = 1017 cm-3.
What fraction of the donors are not ionized?
Hint: Suppose at first that all of the donor atoms are ionized.
 Nc 
EF  Ec  kT ln 
  Ec  147 meV
 n 
Probability of non-ionization 
1
1  e ( ED  EF ) / kT
1

 0.02
(147meV  45meV ) / 26 meV
1 e
EE130/230A Fall 2013
Lecture 3, Slide 17
p-type Material
R. F. Pierret, Semiconductor Device Fundamentals, Figure 2.16
Energy band
diagram
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Density of
States
Probability
of occupancy
Lecture 3, Slide 18
Carrier
distributions
Non-degenerately Doped Semiconductor
• Recall that the expressions for n and p were derived using
the Boltzmann approximation, i.e. we assumed
Ev  3kT  EF  Ec  3kT
Ec
3kT
EF in this range
3kT
Ev
The semiconductor is said to be non-degenerately doped in this case.
EE130/230A Fall 2013
Lecture 3, Slide 19
Degenerately Doped Semiconductor
• If a semiconductor is very heavily doped, the Boltzmann
approximation is not valid.
In Si at T=300K: Ec-EF < 3kBT if ND > 1.6x1018 cm-3
EF-Ev < 3kBT if NA > 9.1x1017 cm-3
The semiconductor is said to be degenerately doped in this case.
• Terminology:
“n+”  degenerately n-type doped. EF  Ec
“p+”  degenerately p-type doped. EF  Ev
EE130/230A Fall 2013
Lecture 3, Slide 20
Band Gap Narrowing
• If the dopant concentration is a significant fraction of
the silicon atomic density, the energy-band structure
is perturbed  the band gap is reduced by DEG :
R. J. Van Overstraeten and R. P. Mertens,
Solid State Electronics vol. 30, 1987
8
DEG  3.5 10 N
1/ 3
300
T
N = 1018 cm-3: DEG = 35 meV
N = 1019 cm-3: DEG = 75 meV
EE130/230A Fall 2013
Lecture 3, Slide 21
Dependence of EF on Temperature
C. C. Hu, Modern Semiconductor Devices for Integrated Circuits, Figure 1-21
n  N c e  ( Ec  EF ) / kT
 EF  Ec  kT ln N c n 
Net Dopant Concentration (cm-3)
EE130/230A Fall 2013
Lecture 3, Slide 22
Summary
• Thermal equilibrium:
– Balance between internal processes with no external
stimulus (no electric field, no light, etc.)
– Fermi function
f (E) 
1
1  e ( E  EF ) / kT
• Probability that a state at energy E is filled with an
electron, under equilibrium conditions.
• Boltzmann approximation:
For high E, i.e. E – EF > 3kT: f ( E )  e  ( E  EF ) / kT
For low E, i.e. EF – E > 3kT:
EE130/230A Fall 2013
Lecture 3, Slide 23
1  f ( E )  e ( EF  E ) / kT
Summary (cont’d)
• Relationship between EF and n, p :
n  Nce
 ( Ec  E F ) / kT
p  Nve
 ( E F  Ev ) / kT
 ni e
( E F  Ei ) / kT
 ni e
( Ei  E F ) / kT
• Intrinsic carrier concentration :
ni  N c N v e
 EG / 2 kT
• The intrinsic Fermi level, Ei, is located near midgap.
EE130/230A Fall 2013
Lecture 3, Slide 24
Summary (cont’d)
• If the dopant concentration exceeds 1018 cm-3,
silicon is said to be degenerately doped.
– The simple formulas relating n and p exponentially to EF
are not valid in this case.
For degenerately doped n-type (n+) Si: EF  Ec
For degenerately doped p-type (p+) Si: EF  Ev
EE130/230A Fall 2013
Lecture 3, Slide 25