Optimization of Non-linear Equation using Scipy Solver

Question

import numpy as np
import sys
import pandas as pd
from scipy.optimize import *
import matplotlib.pylab as plot

SigG = 162.4
M2 = 30
SigS = 111.7
Rmv = 26
kN2E6 = 6.13

func = lambda SigA : 1-(((SigA/SigG)**M2) + (((SigA/(kN2E6+(10.0**-23))) + SigS) / (Rmv + SigS))**2)
SigAinitial_guess = [0,162.4]
Solution = fsolve(func,SigAinitial_guess)
Solution[0]
print(repr(Solution[0]))

I have an issue with optimizing the above equation mentioned in the code. I need to find out SigA from the equation and the total equation must be equal to one.

I have already implemented the same using Excel solver and those are the exact output values of SigA and it satisfied with our experiment. Now, I'm trying to implement the same using Python.

The problem here is I have different kN2E6 values. From those values, if I take 4.608 I'm getting the exact output in Excel. If I take the values from 6.136 to the rest values I'm getting an error and I have mentioned it below for both kN2E6 values.

For kN2E6 = 6.136

For kN2E6 = 4.608

I have taken my SigAinitial_guess = [0,162.4], because my output of SigA should be in between (0,162.4).