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#Librerias necesarias para ejecutar el cdigo
import numpy as num
import matplotlib
matplotlib.use('TkAgg')
import matplotlib.pyplot as plot
from matplotlib.figure import Figure
from matplotlib.backends.backend_tkagg import FigureCanvasTkAgg, NavigationToolbar2TkAgg
from matplotlib.backend_bases import key_press_handler
import scipy.constants as sc
import matplotlib.patches as mpatches
import sys
if sys.version_info[0] < 3:
import Tkinter as Tk
else:
import tkinter as Tk
home = Tk.Tk()
home.wm_title("pag20")
#Declaracion de limites
f = Figure()
plota = f.add_subplot(111)
#Declaracion de Variables
a = num.linspace(0.5,4,1000)#Temperatura desde 50 hasta 400 kelvin
#Definicion de las funciones
mnSi=1.08*sc.m_e
mnGaAs=0.068*sc.m_e
mnGe=0.55*sc.m_e
mnGaN=0.19*sc.m_e
mnGaP=0.9*sc.m_e
mnInP=0.07*sc.m_e
mpSi=1.1*sc.m_e
mpGaAs=0.5*sc.m_e
mpGe=0.39*sc.m_e
mpGaN=0.8*sc.m_e
mpGaP=0.9*sc.m_e
mpInP=0.4*sc.m_e
#GaN
nc=2*((2*num.pi*mnGaN*sc.k*(1000/a))/(sc.h**2))**(3/2)/1e+6
nv=2*((2*num.pi*mpGaN*sc.k*(1000/a))/(sc.h**2))**(3/2)/1e+6
Eg=3.470-((7.70*10**(-4))*(1000/a)**2/((1000/a)+600)) #GaN
b=num.sqrt(nc*nv)*num.exp(-Eg*sc.e/(2*((1000/a))*sc.k))
#GaP
nc=2*((2*num.pi*mnGaP*sc.k*(1000/a))/(sc.h**2))**(3/2)/1e+6
nv=2*((2*num.pi*mpGaP*sc.k*(1000/a))/(sc.h**2))**(3/2)/1e+6
Eg=2.340-((6.20*10**(-4))*(1000/a)**2/((1000/a)+460)) #GaP
c=num.sqrt(nc*nv)*num.exp(-Eg*sc.e/(2*((1000/a))*sc.k))
#GaAs
nc=2*((2*num.pi*mnGaAs*sc.k*(1000/a))/(sc.h**2))**(3/2)/1e+6
nv=2*((2*num.pi*mpGaAs*sc.k*(1000/a))/(sc.h**2))**(3/2)/1e+6
Eg=1.519-((5.41*10**(-4))*(1000/a)**2/((1000/a)+204)) #GaAS
d=num.sqrt(nc*nv)*num.exp(-Eg*sc.e/(2*((1000/a))*sc.k))
#InP
nc=2*((2*num.pi*mnInP*sc.k*(1000/a))/(sc.h**2))**(3/2)/1e+6
nv=2*((2*num.pi*mpInP*sc.k*(1000/a))/(sc.h**2))**(3/2)/1e+6
Eg=1.425-((4.50*10**(-4))*(1000/a)**2/((1000/a)+327)) #InP
e=num.sqrt(nc*nv)*num.exp(-Eg*sc.e/(2*((1000/a))*sc.k))
#Si
nc=2*((2*num.pi*mnSi*sc.k*(1000/a))/(sc.h**2))**(3/2)/1e+6
nv=2*((2*num.pi*mpSi*sc.k*(1000/a))/(sc.h**2))**(3/2)/1e+6
Eg=1.170-((4.73*10**(-4))*(1000/a)**2/((1000/a)+636)) #Si
g=num.sqrt(nc*nv)*num.exp(-Eg*sc.e/(2*((1000/a))*sc.k))
#Ge
nc=2*((2*num.pi*mnGe*sc.k*(1000/a))/(sc.h**2))**(3/2)/1e+6
nv=2*((2*num.pi*mpGe*sc.k*(1000/a))/(sc.h**2))**(3/2)/1e+6
Eg=0.744-((4.77*10**(-4))*(1000/a)**2/((1000/a)+235)) #Ge
h=num.sqrt(nc*nv)*num.exp(-Eg*sc.e/(2*((1000/a))*sc.k))
#Se les asigna el label correspondiente a cada eje
plota.semilogy(a,b,color='y',label='GaN')
plota.semilogy(a,c,color='b',label='GaP')
plota.semilogy(a,d,color='g',label='GaAS')
plota.semilogy(a,e,color='black',label='InP')
plota.semilogy(a,g,color='r',label='Si')
plota.semilogy(a,h,color='cyan',label='Ge')
plota.set_xlabel("$1000/T \ (1/K)$")
plota.set_ylabel("$ni \ (cm-3)$",rotation='vertical')
plota.legend(loc=1)
# Muestra la grafica-------------------------------------------------
plota.set_title('Concentracion de portadores intrinsecos')
f.tight_layout()
plota.grid(True)
canvas = FigureCanvasTkAgg(f,master=home)
canvas.show()
canvas.get_tk_widget().pack(side=Tk.TOP, fill=Tk.BOTH, expand=1)
toolbar = NavigationToolbar2TkAgg(canvas, home)
toolbar.update()
canvas._tkcanvas.pack(side=Tk.TOP, fill=Tk.BOTH, expand=1)
#Proceso de seleccion del teclado
R = "right"
L = "left"
U = "up"
D = "down"
x = 3
state=0
var = Tk.StringVar()
label = Tk.Label(home, textvariable=var, fg="black", bg="white", font = "Helvetica 14 bold italic")
var.set("Utilice las flechas del teclado para desplazarce por la grafica")
def graficar(x):
if state==0:
#Ge
nc=2*((2*num.pi*mnGe*sc.k*(1000/x))/(sc.h**2))**(3/2)/1e+6
nv=2*((2*num.pi*mpGe*sc.k*(1000/x))/(sc.h**2))**(3/2)/1e+6
Eg=0.744-((4.77*10**(-4))*(1000/x)**2/((1000/x)+235)) #Ge
y=num.sqrt(nc*nv)*num.exp(-Eg*sc.e/(2*((1000/x))*sc.k))
elif state==1:
#Si
nc=2*((2*num.pi*mnSi*sc.k*(1000/x))/(sc.h**2))**(3/2)/1e+6
nv=2*((2*num.pi*mpSi*sc.k*(1000/x))/(sc.h**2))**(3/2)/1e+6
Eg=1.170-((4.73*10**(-4))*(1000/x)**2/((1000/x)+636)) #Si
y=num.sqrt(nc*nv)*num.exp(-Eg*sc.e/(2*((1000/x))*sc.k))
elif state==2:
#InP
nc=2*((2*num.pi*mnInP*sc.k*(1000/x))/(sc.h**2))**(3/2)/1e+6
nv=2*((2*num.pi*mpInP*sc.k*(1000/x))/(sc.h**2))**(3/2)/1e+6
Eg=1.425-((4.50*10**(-4))*(1000/x)**2/((1000/x)+327)) #InP
y=num.sqrt(nc*nv)*num.exp(-Eg*sc.e/(2*((1000/x))*sc.k))
elif state==3:
#GaAs
nc=2*((2*num.pi*mnGaAs*sc.k*(1000/x))/(sc.h**2))**(3/2)/1e+6
nv=2*((2*num.pi*mpGaAs*sc.k*(1000/x))/(sc.h**2))**(3/2)/1e+6
Eg=1.519-((5.41*10**(-4))*(1000/x)**2/((1000/x)+204)) #GaAS
y=num.sqrt(nc*nv)*num.exp(-Eg*sc.e/(2*((1000/x))*sc.k))
elif state==4:
#GaP
nc=2*((2*num.pi*mnGaP*sc.k*(1000/x))/(sc.h**2))**(3/2)/1e+6
nv=2*((2*num.pi*mpGaP*sc.k*(1000/x))/(sc.h**2))**(3/2)/1e+6
Eg=2.340-((6.20*10**(-4))*(1000/x)**2/((1000/x)+460)) #GaP
y=num.sqrt(nc*nv)*num.exp(-Eg*sc.e/(2*((1000/x))*sc.k))
else:
#GaN
nc=2*((2*num.pi*mnGaN*sc.k*(1000/x))/(sc.h**2))**(3/2)/1e+6
nv=2*((2*num.pi*mpGaN*sc.k*(1000/x))/(sc.h**2))**(3/2)/1e+6
Eg=3.470-((7.70*10**(-4))*(1000/x)**2/((1000/x)+600)) #GaN
y=num.sqrt(nc*nv)*num.exp(-Eg*sc.e/(2*((1000/x))*sc.k))
n = num.linspace(x,x,2)
plota.cla()
plota.semilogy(a,b,color='y',label='GaN')
plota.semilogy(a,c,color='b',label='GaP')
plota.semilogy(a,d,color='g',label='GaAS')
plota.semilogy(a,e,color='black',label='InP')
plota.semilogy(a,g,color='r',label='Si')
plota.semilogy(a,h,color='cyan',label='Ge')
plota.set_xlabel("$1000/T \ (1/K)$")
plota.set_ylabel("$ni \ (cm-3)$",rotation='vertical')
plota.legend(loc=1)
# Muestra la grafica-------------------------------------------------
plota.set_title('Concentracion de portadores intrinsecos')
f.tight_layout()
plota.grid(True)
plota.scatter([x, ], [y, ], 50, color='red')
canvas.draw()
var.set("Valores sobre la curva\t ni= "+str(y)+" con 1000/T= "+str(x))
def on_key_event(event):
#Flecha de abajo
if event.key==D:
global state
global a
global b
global x
x = x
if state==5:
state=0
else:
state=state+1
graficar(x)
#Flecha de arriba
elif event.key==U:
global state
global a
global b
global x
x = x
if state==0:
state=5
else:
state=state-1
graficar(x)
#Flecha derecha
elif event.key==R:
global a
global b
global x
if x>=4:
x=4
else:
x = x + 0.1
graficar(x)
#Flecha Izquierda
elif event.key==L:
global a
global b
global x
if x<=0.5:
x=0.5
else:
x = x - 0.1
graficar(x)
else:
pass
key_press_handler(event, canvas, toolbar)
plot.text(4*10**(-6),1*10**(6) , r'$\ Area $')
canvas.mpl_connect('key_press_event', on_key_event)
label.pack(side="bottom", ipady=20)
#Continue el proceso
Tk.mainloop()
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