檢視 $adddiffusivedope 的原始碼

$adddiffusivedope is the command that puts diffusive dopant distribution in the device. The doping density decay can be either exponential decay or Gaussian distribution. The command is 

 $adddiffusivedope
 N_region
 type  regionID Ndope  activation_energy  x_left  y_bottom  x_right y_top <math>L_x</math> <math>L_y</math>  
 type  regionID Ndope  activation_energy  x_left  y_bottom  x_right y_top <math>L_x</math> <math>L_y</math>  
 ...
 ...
 Nth_type ....  

 type: Can be 1, 11, 111, 101. Please see below
 regionID:  The region No to use the diffusive doping
 Ndope: Na pr Nd  Posive is for n-type, negative is for p-type
 <math>L_{x}</math> and <math>L_{y}</math> is the diffusion length in x and y direction. The unit is <math>\mu m </math>

 For type = 1, inside regionID
  <math>x_{left} < x < x_{right} ~~ y_{bottom} < y < y_{top} :    N_{d,a} =N_{d,a}+ Ndope </math>
  <math>x < x_{left}    :  N_{d,a} = N_{d,a}+ Ndope * exp(-1/L_{x}*(|x-x_{left}|)) </math> 
  <math>x > x_{right}   :  N_{d,a} = N_{d,a}+ Ndope * exp(-1/L_{x}*(|x-x_{right}|)) </math> 
  <math>y < y_{bottom}  :   N_{d,a} = N_{d,a}+ Ndope * exp(-1/L_{y}*(|y-y_{bottom}|)) </math> 
  <math>y > y_{top}     :   N_{d,a} = N_{d,a}+ Ndope * exp(-1/L_{y}*(|y-y_{top}|)) </math>
<br><br>
 For type = 11, inside regionID
 <math>x_{left} < x < x_{right} ~~ y_{bottom} < y < y_{top} :    N_{d,a} = Ndope </math>
  <math>x < x_{left}    :  N_{d,a} =  Ndope * exp(-1/L_{x}*(|x-x_{left}|)) </math> 
  <math>x > x_{right}   :  N_{d,a} =  Ndope * exp(-1/L_{x}*(|x-x_{right}|)) </math> 
  <math>y < y_{bottom}  :   N_{d,a} = Ndope * exp(-1/L_{y}*(|y-y_{bottom}|)) </math> 
  <math>y > y_{top}     :   N_{d,a} = Ndope * exp(-1/L_{y}*(|y-y_{top}|)) </math>

 As shown in the above equation, the difference between 11 and 1 is that the diffusive dopant is additional to the region. For example, in parameters, you already set the doping density to be -1.0e19. If you use 1, Ndope = 2.0e19. Then, the final doping density in this region is 2e19-1e19 = 1.0e19. If you use 11, the doping density becomes 2e19

For 101 and 111, it is applied in impurity. The difference between N_impuriy and N_{d,a} is that  N_impuriy is 100% activated. 

 For type = 101, inside regionID
  <math>x_{left} < x < x_{right} ~~ y_{bottom} < y < y_{top} :   N_{impurity} =N_{impurity}+ Ndope </math>
 <math>x < x_{left}    :  N_{impurity} = N_{impurity}+ Ndope * exp(-1/L_{x}*(|x-x_{left}|)) </math> 
 <math>x > x_{right}   :  N_{impurity} = N_{impurity}+ Ndope * exp(-1/L_{x}*(|x-x_{right}|)) </math> 
 <math>y < y_{bottom}  :  N_{impurity} = N_{impurity}+ Ndope * exp(-1/L_{y}*(|y-y_{bottom}|)) </math> 
 <math>y > y_{top}     :  N_{impurity} = N_{impurity}+ Ndope * exp(-1/L_{y}*(|y-y_{top}|)) </math>
 For type = 111, inside regionID
  <math>x_{left} < x < x_{right} ~~ y_{bottom} < y < y_{top} :   N_{impurity} = Ndope </math>
 <math>x < x_{left}    :  N_{impurity} = Ndope * exp(-1/L_{x}*(|x-x_{left}|)) </math> 
 <math>x > x_{right}   :  N_{impurity} = Ndope * exp(-1/L_{x}*(|x-x_{right}|)) </math> 
 <math>y < y_{bottom}  :  N_{impurity} = Ndope * exp(-1/L_{y}*(|y-y_{bottom}|)) </math> 
 <math>y > y_{top}     :  N_{impurity} = Ndope * exp(-1/L_{y}*(|y-y_{top}|)) </math>



 type: Can be 2, 12, 112, 102. with is decay like Gaussian broadening. Please see below
 regionID:  The region No to use the diffusive doping
 Ndope: Na pr Nd  Posive is for n-type, negative is for p-type
 <math>L_{x}</math> and <math>L_{y}</math> is the Gaussian broading width in x and y direction. The unit is <math>\mu m </math>

 For type = 2, inside regionID
  <math>x_{left} < x < x_{right} ~~ y_{bottom} < y < y_{top} :  N_{d,a} = N_{d,a}+Ndope </math>
 <math>x < x_{left}    :  N_{d,a} = N_{d,a}+ Ndope * exp(-0.5/L_{x}^{2}*(|x-x_{left}|)^{2}) </math> 
 <math>x > x_{right}   :  N_{d,a} = N_{d,a}+ Ndope * exp(-0.5/L_{x}^{2}*(|x-x_{right}|)^{2}) </math> 
 <math>y < y_{bottom}  :  N_{d,a} = N_{d,a}+ Ndope * exp(-0.5/L_{y}^{2}*(|y-y_{bottom}|)^{2}) </math> 
 <math>y > y_{top}     :  N_{d,a} = N_{d,a}+ Ndope * exp(-0.5/L_{y}^{2}*(|y-y_{top}|)^{2}) </math>

 For type = 12, inside regionID
  <math>x_{left} < x < x_{right} ~~ y_{bottom} < y < y_{top} :   N_{d,a} = Ndope </math>
 <math>x < x_{left}    :  N_{d,a} = Ndope * exp(-0.5/L_{x}^{2}*(|x-x_{left}|)^{2}) </math> 
 <math>x > x_{right}   :  N_{d,a} = Ndope * exp(-0.5/L_{x}^{2}*(|x-x_{right}|)^{2}) </math> 
 <math>y < y_{bottom}  :  N_{d,a} = Ndope * exp(-0.5/L_{y}^{2}*(|y-y_{bottom}|)^{2}) </math> 
 <math>y > y_{top}     :  N_{d,a} = Ndope * exp(-0.5/L_{y}^{2}*(|y-y_{top}|)^{2}) </math>

 As shown in the above equation, the difference between 11 and 1 is that the diffusive dopant is additional to the region. For example, in parameters, you already set the doping density to be -1.0e19. If you use 1, Ndope = 2.0e19. Then, the final doping density in this region is 2e19-1e19 = 1.0e19. If you use 11, the doping density becomes 2e19

For 102 and 112, it is applied in impurity. The difference between N_impuriy and N_{d,a} is that  N_impuriy is 100% activated. 

 For type = 102, inside regionID
  <math>x_{left} < x < x_{right} ~~ y_{bottom} < y < y_{top} :   N_{impurity} =  N_{impurity} +Ndope </math>
 <math>x < x_{left}    :  N_{impurity} = N_{impurity}+ Ndope * exp(-0.5/L_{x}^{2}*(|x-x_{left}|)^{2}) </math> 
 <math>x > x_{right}   :  N_{impurity} = N_{impurity}+ Ndope * exp(-0.5/L_{x}^{2}*(|x-x_{right}|)^{2}) </math> 
 <math>y < y_{bottom}  :  N_{impurity} = N_{impurity}+ Ndope * exp(-0.5/L_{y}^{2}*(|y-y_{bottom}|)^{2}) </math> 
 <math>y > y_{top}     :  N_{impurity} = N_{impurity}+ Ndope * exp(-0.5/L_{y}^{2}*(|y-y_{top}|)^{2}) </math>
 For type = 112, inside regionID
  <math>x_{left} < x < x_{right} ~~ y_{bottom} < y < y_{top} :   N_{impurity} = Ndope </math>
 <math>x < x_{left}    :  N_{impurity} = Ndope * exp(-0.5/L_{x}^{2}*(|x-x_{left}|)^{2}) </math> 
 <math>x > x_{right}   :  N_{impurity} = Ndope * exp(-0.5/L_{x}^{2}*(|x-x_{right}|)^{2}) </math> 
 <math>y < y_{bottom}  :  N_{impurity} = Ndope * exp(-0.5/L_{y}^{2}*(|y-y_{bottom}|)^{2}) </math> 
 <math>y > y_{top}     :  N_{impurity} = Ndope * exp(-0.5/L_{y}^{2}*(|y-y_{top}|)^{2}) </math>

<br>'''<big><big>The $adddiffusivedope setting in GUI interface is here</big></big>''' <br>
Press '''Additional Function''', check the box for '''Functional Dope''' and fill in these fields as needed!<br>
[[檔案:2D_adddiffusivedope_fig1.jpg|1200px]]