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{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Chapter7 - Optoelectronic sources"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Example 7.1: Page 153"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Intrinsic carrier concentration ,ni = 2.2e+12 m**-3\n"
]
}
],
"source": [
"from __future__ import division\n",
"from math import sqrt, pi, exp\n",
"#Intrinsic carrier\n",
"#given data :\n",
"m=9.11*10**-31## in kg\n",
"k=1.38*10**-23## in JK**-1\n",
"h=6.626*10**-34## in Js\n",
"ev=1.6*10**-19## in J\n",
"T=300## in K\n",
"me=0.07*m## in kg\n",
"mh=0.56*m## in kg\n",
"Eg=1.43*ev## in J\n",
"ni=2*((2*pi*k*T)/h**2)**(3/2)*(me*mh)**(3/4)*exp(-Eg/(2*k*T))#\n",
"print \"Intrinsic carrier concentration ,ni = %0.1e m**-3\"%ni"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Example 7.2: Page 155"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Diffusion potential, Vd = 1.234 V\n"
]
}
],
"source": [
"#Diffusion potential\n",
"from math import log\n",
"#given data :\n",
"Na=5*10**23## in m**-3\n",
"Nd=5*10**21## in m**-3\n",
"T=300## in K\n",
"e=1.6*10**-19## in J\n",
"k=1.38*10**-23## in JK**-1\n",
"V=(k*T)/e#\n",
"ni=2.2*10**12## in m**-3\n",
"Vd=V*log((Na*Nd)/ni**2)#\n",
"print \"Diffusion potential, Vd = %0.3f V\"%Vd"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Example 7.3: Page 161"
]
},
{
"cell_type": "code",
"execution_count": 6,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Injection efficiency, eta_inj = 0.8247\n"
]
}
],
"source": [
"#Injection efficiency\n",
"#given data :\n",
"Na=10**23## in m**-3\n",
"Nd=10**21## in m**-3\n",
"T=300## in K\n",
"e=1.6*10**-19## in J\n",
"k=1.38*10**-23## in JK**-1\n",
"mue=0.85## in m**2V**-1s**-1\n",
"muh=0.04## in m**2V**-1s**-1\n",
"De=(mue*k*T)/e## in m**2s**-1\n",
"Dh=(muh*k*T)/e## in m**2s**-1\n",
"Le=1#\n",
"Lh=Le#\n",
"eta_inj=1/(1+((De/Dh)*(Lh/Le)*(Nd/Na)))#\n",
"print \"Injection efficiency, eta_inj = %0.4f\"%eta_inj"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Example 7.4: Page 171"
]
},
{
"cell_type": "code",
"execution_count": 8,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"part (a)\n",
"Internal quantum efficiency = 0.50\n",
"part (b)\n",
"External quantum efficiency = 0.0337\n"
]
}
],
"source": [
"#Internal and quantum efficiency\n",
"#given data :\n",
"print \"part (a)\"\n",
"tau_rr=1#\n",
"tau_nr=tau_rr#\n",
"eta_int=1/(1+(tau_rr/tau_nr))#\n",
"print \"Internal quantum efficiency = %0.2f\"%eta_int\n",
"print \"part (b)\"\n",
"ns=3.7#\n",
"na=1.5#\n",
"As=0#\n",
"eta_ext=eta_int*(1-As)*((2*na**3)/(ns*(ns+na)**2))#\n",
"print \"External quantum efficiency = %0.4f\"%eta_ext"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Example 7.5: Page 180"
]
},
{
"cell_type": "code",
"execution_count": 10,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"The number of longitudinal modes excited = 1.001e-03 nm\n"
]
}
],
"source": [
"#The number of longitudinal modes excited\n",
"#given data :\n",
"lamda=632.8*10**-9## in m\n",
"n=1#\n",
"L=20*10**-2## in m\n",
"del_lamda=((lamda)**2/(2*n*L))*10**9#\n",
"print \"The number of longitudinal modes excited = %0.3e nm\"%del_lamda"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Example 7.6: Page 183"
]
},
{
"cell_type": "code",
"execution_count": 11,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"part (a)\n",
"The reduction in threshold gain = 1.31 mm**-1\n",
"part (b)\n",
"Differential quantum efficiency = 0.42\n"
]
}
],
"source": [
"#The reduction and Differential quantum efficiency\n",
"#given data :\n",
"print \"part (a)\"\n",
"alfa_eff=1.5## in mm**-1\n",
"gama=0.8#\n",
"L=0.5## in mm\n",
"R1=0.35#\n",
"R2=R1#\n",
"R2a=1.0#\n",
"g_th1=(1/gama)*(alfa_eff+(1/(2*L))*log(1/(R1*R2)))#\n",
"g_th2=(1/gama)*(alfa_eff+(1/(2*L))*log(1/(R1*R2a)))#\n",
"del_gth=g_th1-g_th2#\n",
"print \"The reduction in threshold gain = %0.2f mm**-1\"%del_gth\n",
"print \"part (b)\"\n",
"eta_D=(gama*(g_th2-alfa_eff))/(g_th2)#\n",
"print \"Differential quantum efficiency = %0.2f\"%eta_D"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Example 7.7: Page 192"
]
},
{
"cell_type": "code",
"execution_count": 13,
"metadata": {
"collapsed": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"part (a)\n",
"The internal power efficiency = 0.48\n",
"part (b)\n",
"The external power efficiency = 0.012\n",
"part (c)\n",
"The overall source fiber power coupling efficiency = 8.51e-04\n",
"The optical loss = 30.70 dB\n"
]
}
],
"source": [
"from math import log10\n",
"#Internal and external power efficiency\n",
"#given data :\n",
"print \"part (a)\"\n",
"As=0##\n",
"ns=3.7## assuming that the example 7.4\n",
"eta_int=0.50## internal efficiency\n",
"V=1.5## in V\n",
"I=120*10**-3## in A\n",
"IBYe=120*10**-3## \n",
"Eph=1.43## in eV\n",
"eta_int=0.50## internal efficiency\n",
"fi_int=eta_int*IBYe*Eph#\n",
"t_power=I*V#\n",
"P_int=fi_int/t_power#\n",
"print \"The internal power efficiency = %0.2f\"%P_int\n",
"print \"part (b)\"\n",
"eta_ext=eta_int*(1-As)*2/(ns*(ns+1)**2)#\n",
"fi_ext=eta_ext*IBYe*Eph#\n",
"t_power=I*V#\n",
"P_ext=fi_ext/t_power#\n",
"print \"The external power efficiency = %0.3f\"%P_ext\n",
"print \"part (c)\"\n",
"V=1.5## in V\n",
"I=120*10**-3## in A\n",
"IBYe=120*10**-3## \n",
"Eph=1.43## in eV\n",
"n1=1.5#\n",
"n2=1.48#\n",
"na=n1#\n",
"eta_ext=0.0337#\n",
"eta_T=eta_ext*((n1**2-n2**2)/na**2)#\n",
"fi_T=eta_T*IBYe*Eph#\n",
"t_power=I*V#\n",
"sfpc=fi_T/t_power#\n",
"O_loss=-10*log10(sfpc)#\n",
"print \"The overall source fiber power coupling efficiency = %0.2e\"%sfpc\n",
"print \"The optical loss = %0.2f dB\"%O_loss"
]
}
],
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"kernelspec": {
"display_name": "Python 2",
"language": "python",
"name": "python2"
},
"language_info": {
"codemirror_mode": {
"name": "ipython",
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"file_extension": ".py",
"mimetype": "text/x-python",
"name": "python",
"nbconvert_exporter": "python",
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"version": "2.7.9"
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|