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Semiconductor Device
Fabrication:
Doping
Arpan Deyasi
Dept of ECE, RCCIIT, Kolkata, India
1/15/2021 Arpan Deyasi, RCCIIT
1/15/2021 Arpan Deyasi, RCCIIT
Dopant induction in semiconductor
Diffusion
Boron is the most common p-type impurity in Silicon
Arsenic and Phosphorus are used as n-type dopants
Ion implantation
1/15/2021 Arpan Deyasi, RCCIIT
Dopant atoms are introduced from the gas phase of
by using doped-oxide sources
Doping concentration decreases monotonically from
the surface
In-depth distribution of the dopant is determined
mainly by the temperature and diffusion time
Used to form a deep junction
Feature of Diffusion
1/15/2021 Arpan Deyasi, RCCIIT
solid sources (BN , As2O3 , P2O5)
liquid sources (BBr3, AsCl3, and POCl3)
gaseous sources (B2H6, AsH3, and PH3)
Nature of Sources
1/15/2021 Arpan Deyasi, RCCIIT
Diffusion Mechanism
1/15/2021 Arpan Deyasi, RCCIIT
Mathematics of Diffusion
Let ‘F’ be the flux of dopant atoms traversing through a unit
area in a unit time
C
F D
z
∂
= −
∂
D: diffusion coefficient
C: dopant concentration
z: distance in one dimension
1/15/2021 Arpan Deyasi, RCCIIT
Mathematics of Diffusion
flux is proportional to the concentration gradient
dopant atoms will diffuse from a high-concentration region
toward a low-concentration region
negative sign states that matters flow in the direction
of decreasing dopant concentration
1/15/2021 Arpan Deyasi, RCCIIT
According to the law of conservation of matter, the change of
the dopant concentration with time must be equivalent to
the local decrease of the diffusion flux, in the absence of a
source or a sink
Mathematics of Diffusion
C F
t z
∂ ∂
= −
∂ ∂
C C
D
t z z
∂ ∂ ∂ 
=− − 
∂ ∂ ∂ 
1/15/2021 Arpan Deyasi, RCCIIT
Mathematics of Diffusion
2
2
C C
D
t z
∂ ∂
=
∂ ∂
this is applicable for lower dopant concentration, so
the diffusion constant at a given temperature can be
considered as a constant
1/15/2021 Arpan Deyasi, RCCIIT
Mathematics of Diffusion
C
F D
z
∂
= −
∂
Fick’s 1st law of diffusion
2
2
C C
D
t z
∂ ∂
=
∂ ∂
Fick’s 2nd law of diffusion
1/15/2021 Arpan Deyasi, RCCIIT
Solution of Diffusion Equation
Boundary condition
at t=0, C(z,0)=0
dopant concentration in the host semiconductor is initially zero
at z=0, C(0,t)=CS
at z=∞, C(∞,t)=0
at large distances from the surface, there are no impurity atoms
at the surface level, CS is the doping concentration
1/15/2021 Arpan Deyasi, RCCIIT
Solution of Diffusion Equation
( , )
2
S
z
C z t C erfc
Dt
 
=  
 
Constant-Surface-Concentration Diffusion
The total number of dopants per unit area of the semiconductor
0 0
( , )
2
S
z z
z
C z t dz C erfc dz
Dt
∝ ∝
=
 
=  
 
∫ ∫
1/15/2021 Arpan Deyasi, RCCIIT
Solution of Diffusion Equation
2
( ) SQ t C Dt
π
=
( ) 1.13 SQ t C Dt=
1/15/2021 Arpan Deyasi, RCCIIT
Diffusion Profile
C(z)
z
1/15/2021 Arpan Deyasi, RCCIIT
Solution of Diffusion Equation
If fixed (or constant) amount of dopant is deposited onto
the semiconductor surface in a thin layer, and the dopant is
subsequently diffused into the semiconductor
0
( , )
z
C z t dz S
∝
=
=∫
‘S’ is the total amount of dopant per unit area
1/15/2021 Arpan Deyasi, RCCIIT
Solution of Diffusion Equation
Boundary condition
at t=0, C(z,0)=0
at z=∞, C(∞,t)=0
2
( , ) exp
4
S z
C z t
DtDtπ
 
= − 
 
1/15/2021 Arpan Deyasi, RCCIIT
Solution of Diffusion Equation
at z=0, C(0,t)=CS
S
S
C
Dtπ
=
2
( , ) exp
4
S
z
C z t C
Dt
 
= − 
 
Constant-Total-Dopant Diffusion
1/15/2021 Arpan Deyasi, RCCIIT
Diffusion Profile
C(z)
z
1/15/2021
Arpan Deyasi, RCCIIT
Experimental set-up
of Diffusion
1/15/2021 Arpan Deyasi, RCCIIT
Experimental set-up
of Diffusion
1/15/2021 Arpan Deyasi, RCCIIT
Two-step Diffusion process
Pre-deposition is also known as constant source diffusion
pre-deposition diffused layer is first formed under the
constant surface concentration condition
Here surface concentration of dopant is always constant
I. Pre-deposition
( , )
2
S
z
C z t C erfc
Dt
 
=  
 
1/15/2021 Arpan Deyasi, RCCIIT
Two-step Diffusion process
II. Drive-in
Drive-in process is also known as limited source diffusion
Here finite quantity of diffusing matter is first placed on the
wafer
Diffusion proceeds from this limited source & it is assumed
that all of this matter is consumed during process
As drive in progresses surface concentration decreases and
dopants move further
2
( , ) exp
4
S z
C z t
DtDtπ
 
= − 
 
1/15/2021 Arpan Deyasi, RCCIIT
C(z)
z
Two-step Diffusion process
1/15/2021 Arpan Deyasi, RCCIIT
Ion Implantation
A low-temperature process
Ions of one element are accelerated into a solid target, thereby
changing the physical, chemical, or electrical properties of the
target
1/15/2021 Arpan Deyasi, RCCIIT
Ion Implantation
Process
[i] Dopant atoms are volatilized, ionized, accelerated,
separated by the mass-to-charge ratios, and directed at a
target
[ii] The atoms enter the crystal lattice, collide with the
host atoms, lose energy, and finally come to rest at some
depth within the solid
[iii] The average penetration depth is determined by the
dopant, substrate materials, and acceleration energy
1/15/2021 Arpan Deyasi, RCCIIT
Ion Implantation Unit
1/15/2021 Arpan Deyasi, RCCIIT
Ion Implantation
1/15/2021 Arpan Deyasi, RCCIIT
Ion Implantation: Range Distributions
Each implanted ion traverses a random path as it penetrates
the target, losing energy by nuclear and electronic stopping
The average total path length is called
the range ‘R’, which is composed of
both lateral and vertical motions
The average depth of the implanted
ions is called the projected range ‘Rp’
1/15/2021 Arpan Deyasi, RCCIIT
distribution of the implanted ions
about that depth can be
approximated as Gaussian with a
standard deviation ‘σp’
Ion Implantation: Range Distributions
lateral motion of the ions leads to a lateral Gaussian
distribution with a standard deviation ‘σ⏊’
1/15/2021 Arpan Deyasi, RCCIIT
ion concentration at depth ‘x’
Ion Implantation: Range Distributions
( )
2
0 2
( ) exp
2
p
p
x R
n x n
σ
 −
 = −
 
 
peak concentration
1/15/2021 Arpan Deyasi, RCCIIT
Ion Implantation: Range Distributions
0
0.4
2 pp
n
φ φ
σπ σ
= ≅
total implanted dose

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Doping processes in device Fabrication

  • 1. Semiconductor Device Fabrication: Doping Arpan Deyasi Dept of ECE, RCCIIT, Kolkata, India 1/15/2021 Arpan Deyasi, RCCIIT
  • 2. 1/15/2021 Arpan Deyasi, RCCIIT Dopant induction in semiconductor Diffusion Boron is the most common p-type impurity in Silicon Arsenic and Phosphorus are used as n-type dopants Ion implantation
  • 3. 1/15/2021 Arpan Deyasi, RCCIIT Dopant atoms are introduced from the gas phase of by using doped-oxide sources Doping concentration decreases monotonically from the surface In-depth distribution of the dopant is determined mainly by the temperature and diffusion time Used to form a deep junction Feature of Diffusion
  • 4. 1/15/2021 Arpan Deyasi, RCCIIT solid sources (BN , As2O3 , P2O5) liquid sources (BBr3, AsCl3, and POCl3) gaseous sources (B2H6, AsH3, and PH3) Nature of Sources
  • 5. 1/15/2021 Arpan Deyasi, RCCIIT Diffusion Mechanism
  • 6. 1/15/2021 Arpan Deyasi, RCCIIT Mathematics of Diffusion Let ‘F’ be the flux of dopant atoms traversing through a unit area in a unit time C F D z ∂ = − ∂ D: diffusion coefficient C: dopant concentration z: distance in one dimension
  • 7. 1/15/2021 Arpan Deyasi, RCCIIT Mathematics of Diffusion flux is proportional to the concentration gradient dopant atoms will diffuse from a high-concentration region toward a low-concentration region negative sign states that matters flow in the direction of decreasing dopant concentration
  • 8. 1/15/2021 Arpan Deyasi, RCCIIT According to the law of conservation of matter, the change of the dopant concentration with time must be equivalent to the local decrease of the diffusion flux, in the absence of a source or a sink Mathematics of Diffusion C F t z ∂ ∂ = − ∂ ∂ C C D t z z ∂ ∂ ∂  =− −  ∂ ∂ ∂ 
  • 9. 1/15/2021 Arpan Deyasi, RCCIIT Mathematics of Diffusion 2 2 C C D t z ∂ ∂ = ∂ ∂ this is applicable for lower dopant concentration, so the diffusion constant at a given temperature can be considered as a constant
  • 10. 1/15/2021 Arpan Deyasi, RCCIIT Mathematics of Diffusion C F D z ∂ = − ∂ Fick’s 1st law of diffusion 2 2 C C D t z ∂ ∂ = ∂ ∂ Fick’s 2nd law of diffusion
  • 11. 1/15/2021 Arpan Deyasi, RCCIIT Solution of Diffusion Equation Boundary condition at t=0, C(z,0)=0 dopant concentration in the host semiconductor is initially zero at z=0, C(0,t)=CS at z=∞, C(∞,t)=0 at large distances from the surface, there are no impurity atoms at the surface level, CS is the doping concentration
  • 12. 1/15/2021 Arpan Deyasi, RCCIIT Solution of Diffusion Equation ( , ) 2 S z C z t C erfc Dt   =     Constant-Surface-Concentration Diffusion The total number of dopants per unit area of the semiconductor 0 0 ( , ) 2 S z z z C z t dz C erfc dz Dt ∝ ∝ =   =     ∫ ∫
  • 13. 1/15/2021 Arpan Deyasi, RCCIIT Solution of Diffusion Equation 2 ( ) SQ t C Dt π = ( ) 1.13 SQ t C Dt=
  • 14. 1/15/2021 Arpan Deyasi, RCCIIT Diffusion Profile C(z) z
  • 15. 1/15/2021 Arpan Deyasi, RCCIIT Solution of Diffusion Equation If fixed (or constant) amount of dopant is deposited onto the semiconductor surface in a thin layer, and the dopant is subsequently diffused into the semiconductor 0 ( , ) z C z t dz S ∝ = =∫ ‘S’ is the total amount of dopant per unit area
  • 16. 1/15/2021 Arpan Deyasi, RCCIIT Solution of Diffusion Equation Boundary condition at t=0, C(z,0)=0 at z=∞, C(∞,t)=0 2 ( , ) exp 4 S z C z t DtDtπ   = −   
  • 17. 1/15/2021 Arpan Deyasi, RCCIIT Solution of Diffusion Equation at z=0, C(0,t)=CS S S C Dtπ = 2 ( , ) exp 4 S z C z t C Dt   = −    Constant-Total-Dopant Diffusion
  • 18. 1/15/2021 Arpan Deyasi, RCCIIT Diffusion Profile C(z) z
  • 20. 1/15/2021 Arpan Deyasi, RCCIIT Experimental set-up of Diffusion
  • 21. 1/15/2021 Arpan Deyasi, RCCIIT Two-step Diffusion process Pre-deposition is also known as constant source diffusion pre-deposition diffused layer is first formed under the constant surface concentration condition Here surface concentration of dopant is always constant I. Pre-deposition ( , ) 2 S z C z t C erfc Dt   =    
  • 22. 1/15/2021 Arpan Deyasi, RCCIIT Two-step Diffusion process II. Drive-in Drive-in process is also known as limited source diffusion Here finite quantity of diffusing matter is first placed on the wafer Diffusion proceeds from this limited source & it is assumed that all of this matter is consumed during process As drive in progresses surface concentration decreases and dopants move further 2 ( , ) exp 4 S z C z t DtDtπ   = −   
  • 23. 1/15/2021 Arpan Deyasi, RCCIIT C(z) z Two-step Diffusion process
  • 24. 1/15/2021 Arpan Deyasi, RCCIIT Ion Implantation A low-temperature process Ions of one element are accelerated into a solid target, thereby changing the physical, chemical, or electrical properties of the target
  • 25. 1/15/2021 Arpan Deyasi, RCCIIT Ion Implantation Process [i] Dopant atoms are volatilized, ionized, accelerated, separated by the mass-to-charge ratios, and directed at a target [ii] The atoms enter the crystal lattice, collide with the host atoms, lose energy, and finally come to rest at some depth within the solid [iii] The average penetration depth is determined by the dopant, substrate materials, and acceleration energy
  • 26. 1/15/2021 Arpan Deyasi, RCCIIT Ion Implantation Unit
  • 27. 1/15/2021 Arpan Deyasi, RCCIIT Ion Implantation
  • 28. 1/15/2021 Arpan Deyasi, RCCIIT Ion Implantation: Range Distributions Each implanted ion traverses a random path as it penetrates the target, losing energy by nuclear and electronic stopping The average total path length is called the range ‘R’, which is composed of both lateral and vertical motions The average depth of the implanted ions is called the projected range ‘Rp’
  • 29. 1/15/2021 Arpan Deyasi, RCCIIT distribution of the implanted ions about that depth can be approximated as Gaussian with a standard deviation ‘σp’ Ion Implantation: Range Distributions lateral motion of the ions leads to a lateral Gaussian distribution with a standard deviation ‘σ⏊’
  • 30. 1/15/2021 Arpan Deyasi, RCCIIT ion concentration at depth ‘x’ Ion Implantation: Range Distributions ( ) 2 0 2 ( ) exp 2 p p x R n x n σ  −  = −     peak concentration
  • 31. 1/15/2021 Arpan Deyasi, RCCIIT Ion Implantation: Range Distributions 0 0.4 2 pp n φ φ σπ σ = ≅ total implanted dose