import csv,sys,os
import matplotlib.pyplot as plt
filename = 'IEC6M01-#20-C03-Eng_Sweep_CgVg_hf_r1_220419_151711.csv'
csv_reader = csv.reader(open(filename))
### input the area
area = 2.64e-5
# print('The area is {}'.format(area))
n = 0
ls,tmp = [],[]
for row in csv_reader:
cv = [row[-2],row[-1]]
tmp.append(cv)
if n %241 == 0:
ls.append(tmp)
tmp = []
n += 1
fig_path = "figs"
if not os.path.exists(fig_path):
os.mkdir(fig_path)
index = 1
for i in ls[1:]:
Cg,Vg = [], []
f = open('figs/Die-{}_Cgs.dat'.format(index),'w')
f.write('Cg Vg\n')
for j in i:
Cg.append(float(j[0]))
Vg.append(float(j[1]))
f.write('{} {}\n'.format(float(j[0])/area,float(j[1])))
f.close()
plt.plot(Vg,Cg)
plt.title('Cg-Vg curve_{}'.format(index))
plt.xlabel('Vg')
plt.ylabel('Cg')
plt.savefig('figs/Die-{}_Cgs.jpg'.format(index))
plt.clf()
index += 1
with open('CV.csv','w',encoding='gbk',newline="") as f:
csv_writer = csv.writer(f)
for j in range(len(ls[1])):
tmp = []
for i in range(1,len(ls)):
tmp += [ls[i][j][1],float(ls[i][j][0])/area]
csv_writer.writerow(tmp)
f.close()
import csv,sys,os
import matplotlib.pyplot as plt
filename = 'IEC6M01-#20-T01-Eng_Sweep_IdVg_220331_091507.csv'
csv_reader = csv.reader(open(filename))
n = 0
ls,tmp = [],[]
ls1,tmp1 = [],[]
for row in csv_reader:
if n <= 65*(2*(n//130+1)-1) and n%130!=0:
tmp.append([row[-3],row[-1]])
else:
tmp1.append([row[-3]])
if n %130 == 0:
ls.append(tmp)
tmp = []
ls1.append(tmp1)
tmp1 = []
n += 1
fig_path = "figs"
if not os.path.exists(fig_path):
os.mkdir(fig_path)
for i in range(1,len(ls)):
Id, Id1, Vg = [], [], []
f = open('figs/Die-{}_IdVg.dat'.format(i),'w')
f.write('Id Id1 Vg\n')
for j in range(len(ls[1])):
Id.append(float(ls[i][j][0]))
Id1.append(float(ls1[i][j][0]))
Vg.append(float(ls[i][j][1]))
f.write('{} {} {}\n'.format(float(ls[i][j][0]),float(ls1[i][j][0]),float(ls[i][j][1])))
f.close()
# plt.rcParams.update({'figure.max_open_warning':0})
# plt.figure()
plt.plot(Vg,Id)
plt.yscale('log')
plt.plot(Vg,Id1)
plt.yscale('log')
plt.title('Id-Vg curve_{}'.format(i))
plt.xlabel('Vg')
plt.ylabel('Id')
plt.savefig('figs/Die-{}_IdVg.jpg'.format(i))
plt.clf()
import csv,sys,os
import matplotlib.pyplot as plt
from scipy import integrate
import numpy as np
# https://blog.csdn.net/github_15549139/article/details/47146279
def filter(filename1,filename2):
with open(filename1,'r') as f1:
content1 = f1.readlines()
with open(filename2,'r') as f2:
content2 = f2.readlines()
Id_raw, Vg_raw1 = [], []
for i in content1[1:]:
tmp = i.split()
Id_raw.append(float(tmp[0]))
Vg_raw1.append(float(tmp[-1]))
Cg_raw, Vg_raw2 = [], []
for j in content2[1:]:
tmp = j.split()
Cg_raw.append(float(tmp[0]))
Vg_raw2.append(float(tmp[1]))
return Id_raw,Vg_raw1,Cg_raw,Vg_raw2
def mobility_old(Id_raw,Vg_raw1,Cg_raw,Vg_raw2,dat_i):
f1 = np.polyfit(Vg_raw1,Id_raw,15)
yvals1 = np.polyval(f1,Vg_raw1)
f2 = np.polyfit(Vg_raw2,Cg_raw,15)
yvals2 = np.polyval(f2,Vg_raw2)
## Selected the Voltage windows
Vg_min = max(min(Vg_raw1),min(Vg_raw2))
Vg_max = min(max(Vg_raw1),max(Vg_raw2))
Vg = np.linspace(Vg_min,Vg_max,num=2000)
Id = np.polyval(f1, Vg)
Cg = np.polyval(f2, Vg)
plt.plot(Vg_raw1,Id_raw,'.',label='raw')
plt.plot(Vg,Id,label='fit')
plt.xlabel('$V_g$')
plt.ylabel('$I_d$')
plt.yscale('log')
plt.title('$I_d$-$V_g$_{}-curve'.format(dat_i))
plt.legend()
plt.savefig('mobs/Die-{}_IdVg_fit.jpg'.format(dat_i))
plt.clf()
plt.plot(Vg_raw2,Cg_raw,'.',label='raw')
plt.plot(Vg,Cg,label='fit')
plt.xlabel('$V_g$')
plt.ylabel('$C_g$')
plt.title('$C_g$-$V_g$_{}-curve'.format(dat_i))
plt.legend()
plt.savefig('mobs/Die-{}_Cgs_fit.jpg'.format(dat_i))
plt.clf()
minCg = min(Cg)
Cgc = [i-minCg for i in Cg]
## integrate.cumtrapz: integral function.
## Q is charge which capacitance to volatge integration.
Q = abs(integrate.cumtrapz(Cgc,Vg))
## mob: mobility. equal to (L/W)*(Id/Vd/Q)
mob = [(L/W)*(Id[i]/Vd/Q[i-1]) for i in range(1,len(Id))]
## Ns = Q/q
Ns = [i/e0 for i in Q]
plt.plot(Vg[1:],Ns,'b')
plt.xlabel('$V_g$')
plt.ylabel('$N$')
plt.title('$N$-$V_g$_{}-curve'.format(dat_i))
plt.savefig('mobs/Die-{}_NV.jpg'.format(dat_i))
plt.clf()
plt.plot(Ns[1000:],mob[1000:],'r')
plt.xlabel('$N$')
plt.ylabel('$\mu$')
plt.title('Mobility {}'.format(dat_i))
plt.savefig('mobs/Die-{}_mobility.jpg'.format(dat_i))
plt.clf()
def mobility(Id_raw,Vg_raw1,Cg_raw,Vg_raw2,dat_i,vfb):
## Id_raw, Vg_raw1 must be the same dimension
## Cg_raw, Vg_raw2 must be the same dimension
## 'np.polyfit' return a list of polynomial coefficient
poly1 = np.polyfit(Vg_raw1,Id_raw,15)
## yvals1: fitted data of Id-Vg curve
yvals1 = np.polyval(poly1,Vg_raw1)
## 'np.polyfit' return a list of polynomial coefficient
poly2 = np.polyfit(Vg_raw2,Cg_raw,15)
## yvals2: fitted data of Cg-Vg curve
yvals2 = np.polyval(poly2,Vg_raw2)
## Selected the Voltage windows
Vg_min = max(min(Vg_raw1),min(Vg_raw2))
Vg_max = min(max(Vg_raw1),max(Vg_raw2))
if vfb > Vg_max or vfb < Vg_min:
sys.exit()
if np.polyval(poly2,vfb) < np.polyval(poly2,Vg_max):
# print('This is n-type!')
## Voltage grid points 2000 (default)
Vg = np.linspace(vfb,Vg_max,num=2000)
Id = np.polyval(poly1, Vg)
Cg = np.polyval(poly2, Vg)
else:
# print('This is p-type!')
Vg = np.linspace(vfb,Vg_min,num=2000)
Id = np.polyval(poly1, Vg)
Cg = np.polyval(poly2, Vg)
plt.plot(Vg_raw1,Id_raw,'.',label='raw')
plt.plot(Vg,Id,label='fit')
plt.xlabel('$V_g$')
plt.ylabel('$I_d$')
plt.yscale('log')
plt.title('$I_d$-$V_g$_{}-curve'.format(dat_i))
plt.legend()
plt.savefig('mobs/Die-{}_IdVg_fit.jpg'.format(dat_i))
plt.clf()
plt.plot(Vg_raw2,Cg_raw,'.',label='raw')
plt.plot(Vg,Cg,label='fit')
plt.xlabel('$V_g$')
plt.ylabel('$C_g$')
plt.title('$C_g$-$V_g$_{}-curve'.format(dat_i))
plt.legend()
plt.savefig('mobs/Die-{}_Cgs_fit.jpg'.format(dat_i))
plt.clf()
## integrate.cumtrapz: integral function.
## Q is charge which capacitance to volatge integration.
Q = abs(integrate.cumtrapz(Cg,Vg))
## mob: mobility. equal to (L/W)*(Id/Vd/Q)
mob = [(L/W)*(Id[i]/Vd/Q[i-1]) for i in range(1,len(Id))]
## Ns = Q/q
Ns = [i/e0 for i in Q]
plt.plot(Vg[1:],Ns,'b')
plt.xlabel('$V_g$')
plt.ylabel('$N$')
plt.title('$N$-$V_g$_{}-curve'.format(dat_i))
plt.savefig('mobs/Die-{}_NV.jpg'.format(dat_i))
plt.clf()
plt.plot(Ns[1000:],mob[1000:],'r')
plt.xlabel('$N$')
plt.ylabel('$\mu$')
plt.title('Mobility_{}'.format(dat_i))
plt.savefig('mobs/Die-{}_mobility.jpg'.format(dat_i))
plt.clf()
def readVfb(filename):
with open(filename,'r') as f:
content = f.readlines()
res = content[0].split()
res = [float(i) for i in res]
return res
def main():
fig_path = "figs"
if not os.path.exists(fig_path):
print('No "figs" filefold!\n**No CV/IV data!**')
sys.exit()
mob_path = "mobs"
if not os.path.exists(mob_path):
os.mkdir(mob_path)
num = 0
for i in os.listdir(fig_path):
if i[-8:] == '_Cgs.dat':
num += 1
if num == 0:
print('Please check the name of "*_Cgs.dat')
sys.exit()
vfb_path = 'vfb.txt'
if not os.path.exists(vfb_path):
print('Warning! there is no "vfb.txt".\n***We will use the minimum of Voltage***')
flag = False
else:
Vfb = readVfb(vfb_path)
flag = True
if num != len(Vfb):
print('The numbers of CV.dat-{} and Vfb.txt-{} mismatch'.format(num,len(Vfb)))
sys.exit()
## Start,end denote the sequence of CV/IV.dat you want to do with.
start, end = 1, num
for dat_i in range(start,end+1):
filename1 = 'figs/Die-{}_IdVg.dat'.format(dat_i)
filename2 = 'figs/Die-{}_Cgs.dat'.format(dat_i)
Id_raw, Vg_raw1, Cg_raw, Vg_raw2 = filter(filename1,filename2)
if flag:
vfb = Vfb[dat_i-1]
mobility(Id_raw,Vg_raw1,Cg_raw,Vg_raw2,dat_i,vfb)
else:
mobility_old(Id_raw,Vg_raw1,Cg_raw,Vg_raw2,dat_i)
print('Die-{} is done.'.format(dat_i))
print('Congratulation!')
if __name__ == '__main__':
### constant Parameter
W=0.198*1e-4 #cm
L=0.5e-4 #cm
e0=1.602e-19
### Control Parameter
Vd = 0.9
main()
