The red dot gives the half wave potential
$E_{1/2}=E^\circ + \dfrac{RT}{nF}\ln\left(\dfrac{m_R}{m_O}\\right)$
The blue dot gives the Nernst potential to help differentiate the effect of both parameters on the curve.
Here, 1 electron exchanged and the standard potential is equal to 0.77 V/ESH. The electrode area is supposed to be equal to 1 m$^2$."""
#===========================================================
# --- Initial parameters ---------------------
#===========================================================
parameters = {
'ratm':
widgets.FloatSlider(value=1.,
description='ratio -- $\dfrac{m_R}{m_O}$',
min=0.00001,
max=10),
'ratC':
widgets.FloatSlider(value=1,
description='$\dfrac{C_R}{C_O}$',
min=0.00001,
max=10),
}
#default parameter for the potential of the couple considered : E0, temperature T, number of exchanged electrons n
E0 = 0.77
T = 298.15
n = 1.
F = constants.physical_constants['Faraday constant'][0]
R = constants.R
lines['dewr'].set_data([0., 1.], Temps[0])
#Plotting horizontal lines for the ebullition point
lines['ebl'].set_data([0., 1.], Temps[1])
lines['ebr'].set_data([0., 1.], Temps[1])
#Plotting an horizontal line for the value of x0
lines['x'].set_data([x, x], [min(TempRange), max(TempRange)])
ax4.set_title('Cooling curve for x = {:3.2f}'.format(x))
fig.canvas.draw_idle()
if __name__ == "__main__":
parameters = {
'x':
widgets.FloatSlider(value=0.5,
description='x_B',
min=0.0001,
max=0.999999),
}
#Save the data as a csv file
saveCsv = True
fileCsv = "diagbin.csv"
Teb = np.array([353.3, 383.8]) #Benzene, Toluene
Hvap = np.array([30.72e3, 33.18e3])
Cpl = np.array([135.6, 157.])
Cpg = np.array([
82.44,
103.7,
])
Hl = np.array([49.e3, 12.e3])
Hg = Hl + Hvap
description = """This program simulates the i-E curves when the current is limited by the electronic transfer.
$I=I_0\left( \exp\left( \dfrac{\\alpha n F \eta}{RT} \\right) - \exp\left( -\dfrac{\left( 1-\\alpha \\right) n F \eta}{RT} \\right)\\right)$
$\eta=E-E^0$, $\\alpha$ is the transfer coefficient for the oxydation
Here, 1 electron exchanged and the standard potential is equal to 0.77 V/ESH. The electrode area is supposed to be equal to 1 m$^2$."""
#===========================================================
# --- Initial parameters ---------------------
#===========================================================
parameters = {
'alpha':
widgets.FloatSlider(value=0.5,
description='transfer coefficient -- $\\alpha$',
min=0,
max=1),
'logI':
widgets.FloatSlider(value=-1.35, description='$\log(I_0)$', min=-5, max=5),
}
#default parameter for the potential of the couple considered : E0, temperature T, number of exchanged electrons n
E0 = 0.77
T = 298.15
n = 1
F = constants.physical_constants['Faraday constant'][0]
R = constants.R
#===========================================================
# --- Functions to plot-------------------------------------
#===========================================================
fig.canvas.draw_idle()
# Main program
if __name__ == "__main__":
#kinetic constants
k1 = 100 #s^-1
k2 = 1 #s^-1
k3 = 100 #s^-1
#Initial conditions : only A is present
C0 = [1., 0., 0., 0.]
parameters = {
'ratio':
widgets.FloatSlider(value=-2,
description='$\log(k_2/k_1)$',
min=-3,
max=3),
}
fig, axes = plt.subplots(2, 2)
ax1 = plt.subplot(2, 2, 1)
ax2 = plt.subplot(2, 2, 2)
ax3 = plt.subplot(2, 2, 3)
ax4 = plt.subplot(2, 2, 4)
ax1.set_title('Concentrations versus time')
ax2.set_title('Concentrations versus time')
#ax2.set_title('B')
ax3.set_title('$v_d(\mathrm{B})$ and $v_a(\mathrm{D})$ versus time')
ax4.set_title('$v_a(\mathrm{D})=f(v_d(\mathrm{B}))$')
#ax4.set_title('D')
lines = {}
def plot_data(lambdaa):
energies = Eg(lambdaa,cutR)
lines2['Eg'].set_data(cutR,energies)
lines2['Eu'].set_data(cutR,Eu(lambdaa,cutR))
lines2['min'].set_data(cutR[np.argmin(energies)],np.min(energies))
energies2= Eg(lambdaa,cutR)
energies2[energies2>0]=0.
lines['plane'].set_data(lambdaa*np.ones_like(cutR),cutR)
lines['plane'].set_3d_properties(energies2)
# Main program
if __name__ == "__main__":
parameters = {
'lambdaa' : widgets.FloatSlider(value=1., description='$\lambda$', min=0.0001, max=2),
}
#figure
fig = plt.figure(figsize=(8,8))
gs = fig.add_gridspec(2, 1, left=0.08, right=0.95, bottom=0.05, top=0.95, wspace=0.18, hspace=0.3)
ax1 = fig.add_subplot(gs[0,0])
ax2 = fig.add_subplot(gs[1,0],projection='3d', proj_type='ortho')
#ax3 = fig.add_subplot(gs[1,0])
#ax4 = fig.add_subplot(gs[1,1])
xs = np.linspace(0.0001,4,500)
ax1.set_xlim(0.,4.)
ax1.set_ylim(-0.7,0.5)
grid, delta = createGrid(0, 2, 250,0.0001, 4, 250)
zetas,Rs = grid
Z = Eg(zetas,Rs)
Z[Z>0]=0
lines['ref'].set_data([omega_0, omega_0], [0, 0.25 * maxi])
ax1.set_xlim(2886. + 300, 2886. - 300)
ax1.set_ylim(0, maxi * 1.1)
for x in xs:
textsR[int(x)].set_position(
(BrancheR(x + 1, omega_0, B, a) - 4, pop(x + 1, omega_0, B, a, T)))
textsP[int(x)].set_position(
(BrancheP(x, omega_0, B, a) + 10, pop(x, omega_0, B, a, T)))
# Main program
if __name__ == "__main__":
parameters = {
'omega_0':
widgets.FloatSlider(value=2886.,
description='$\omega_0$',
min=2700,
max=3000),
'B':
widgets.FloatSlider(value=10.75, description='$B$', min=0, max=20),
'a':
widgets.FloatSlider(value=0., description='$a$', min=0, max=0.25),
'T':
widgets.FloatSlider(value=300., description='$T$', min=100, max=500),
}
fig = plt.figure(figsize=(8, 8))
gs = fig.add_gridspec(1,
1,
left=0.08,
right=0.95,
bottom=0.05,
rects['SCN'].set_width(nSCN / nmax * 0.12)
rects['FeSCN'].set_width(nFeSCN / nmax * 0.12)
rects['Feeq'].set_x(0.48 + nFeeq / nmax * 0.12)
rects['SCNeq'].set_x(0.68 + nSCNeq / nmax * 0.12)
rects['FeSCNeq'].set_x(0.88 + nFeSCNeq / nmax * 0.12)
fig.canvas.draw_idle()
if __name__ == "__main__":
nmax = 1e-2
parameters = {
'nFe0':
widgets.FloatSlider(value=0.05,
description='$n^0_{\\mathrm{Fe^{3+}}}$',
min=0.0,
max=nmax),
'nSCN0':
widgets.FloatSlider(value=0.05,
description='$n^0_{\\mathrm{SCN^{-}}}$',
min=0.0,
max=nmax),
'nFeSCN0':
widgets.FloatSlider(value=0,
description='$n^0_{\\mathrm{FeSCN^{2+}}}$',
min=0.0,
max=nmax),
'xi':
widgets.FloatSlider(value=0.00000001,
description='$x$',
min=-0.01,