-
Notifications
You must be signed in to change notification settings - Fork 1
/
Copy pathSLME.py
195 lines (162 loc) · 6.01 KB
/
SLME.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
from numpy import *
import matplotlib.pyplot as plt
from io import BytesIO
data_am15 = open("AM15G.dat",'r', encoding='utf-8') # solar spectrum
data_alpha = open("absorption.dat", 'r',encoding='utf-8') #光吸收系数
Eg = 1.40 #带隙，单位eV
L = 3 #输入厚度，单位为μm
f = 1 #f，直接带隙为1，间接带隙需要修改
L_max = 3 #厚度最大值，单位微米
T = 300 #温度，单位K
e = ev = 1.60217648740E-19
h = 6.626068E-34
c = 299792458
h_ev = h / ev
c_nm = c * 1E9
Pi = 3.1415926
k = 1.3806505E-23 #单位J/K
k_ev = k / ev
Pin = 1000 #太阳光输入效率
#将太阳光谱数据转换成二维列表
am15 = []
for line in data_am15:
s = line.strip().split('\t')
s1 = ' '.join(s) + '\n'
s2 = s1.split()
if s2 != []:
am15.append([s2[0],s2[1]])
data_am15.close()
#将光吸收系数变为二维列表
alpha = []
for line in data_alpha:
s = line.strip().split('\t')
s1 = ' '.join(s) + '\n'
s2 = s1.split()
if s2 != []:
alpha.append([float(s2[0]), float(s2[1])])
# preparing the data for calculating slme
# 差值过程，思路就是将光吸收与SLME的横坐标对标
data_in = []
for l in range(1, len(am15)) : #am15为太阳光谱
# x = am15[l].split()
hv = float(am15[l][0]) #波长，nm
nhv = float(am15[l][1]) #入射能量
for ll in range(len(alpha)-1) :
if alpha[ll][0] <= hv and alpha[ll+1][0] >= hv :
fact = (hv - alpha[ll][0])/(alpha[ll+1][0] - alpha[ll][0])
tmp1 = alpha[ll][1]*(1-fact) + fact*alpha[ll+1][1]
data_in.append([hv, nhv, tmp1])
#数据内容分别为波长，太阳光入射能量，tmp1为光吸收系数
break
dat = open('data_in_1.dat','w',encoding='utf-8')
for i in range(len(data_in)):
string = str(data_in[i][0]) + '\t' + str(data_in[i][1]) + '\t' + str(data_in[i][2]) +'\n'
# print(string)
dat.write(string)
dat.close()
def get_I(l,f=1,data_in=data_in):
#产生短路电流和暗电流的函数，需要修改的参数有：l，厚度，单位微米；f，直接带隙为1，间接带隙需要修改
Isc = 0.0
I0 = 0.0
L = l * 1E-4 # 厚度，单位微米
for l in range(len(data_in) - 1):
hv0 = data_in[l][0] # 积分单元矩阵左横坐标
hv1 = data_in[l + 1][0] # 积分单元矩阵右横坐标
#
des1 = hv1 - hv0
#
aE0 = 1.0 - exp(-2.0 * L * data_in[l][2])
aE1 = 1.0 - exp(-2.0 * L * data_in[l + 1][2])
is0 = data_in[l][1] * (hv0 / h / c_nm) * aE0
is1 = data_in[l + 1][1] * (hv1 / h / c_nm) * aE1
Isc = Isc + e * (is0 + is1) * des1 / 2.0
hv_0 = 1240 / hv0
hv_1 = 1240 / hv1
des2 = hv_0 - hv_1
irb0 = 2 * Pi * hv_0 ** 2 / h_ev ** 3 / c ** 2 * (exp(-1 * hv_0 / k_ev / T)) * aE0
irb1 = 2 * Pi * hv_1 ** 2 / h_ev ** 3 / c ** 2 * (exp(-1 * hv_1 / k_ev / T)) * aE1
I0 = I0 + e * Pi / f * (irb0 + irb1) * des2 / 2.0
return Isc, I0
def get_JVcurve(Isc, I0, Eg):
#产生JV曲线的函数，需要用到get_I输出的参数，Eg为带隙，单位为eV
I = []
V = []
npts = int(Eg / 0.001)
for ll in range(npts):
Vap = ll * 0.001
i = Isc - I0 * (exp(Vap / k_ev / T) - 1)
# print(I)
I.append(i)
V.append(Vap)
if i <= 0:
break
plt.plot(V,I,'r', label='J-V curve')
plt.ylim(0,Isc+50) # xlim、ylim：分别设置X、Y轴的显示范围
plt.xlim(0,Vap+0.05)
plt.title("JV curve") # title：设置子图的标题
plt.savefig('JV-curve.png')
plt.show()
dat = open('JV-curve.dat', 'w', encoding='utf-8')
for i in range(len(I)):
string = str(V[i]) + '\t' + str(I[i]) + '\t' + str(I[i]*V[i]) +'\n'
# print(string)
dat.write(string)
dat.close()
print('JV-curve中的信息：')
print('开路电压 = ', Vap)
print('短路电流 = ', Isc)
print('SLME =' + str(get_slme(Isc,I0)) + '\t' + '厚度 = ' + str(L) + 'μm')
return 0
def get_slme(Isc,I0):
#计算SLME的函数，会同时打印出短路电流，开路电压和SLME数据，需要用到get_I的输出参数
npts = int(Eg / 0.001)
maxIV = 0
IVtmp = 0
for ll in range(npts):
Vap = ll * 0.001
I = Isc - I0 * (exp(Vap / k_ev / T) - 1)
IVtmp = Vap * I
# print(I)
if IVtmp >= maxIV:
maxIV = IVtmp
elif I <= 0:
break
# print("短路电流 = ", Isc, "A/m2")
# print("开路电压 = ", Vap, "V")
slme = maxIV / Pin
# print("SLME = ", slme)
return slme
#主函数部分
#第一部分是画给定厚度的JV曲线，同时给出开路电压，短路电流和SLME
Isc,I0 = get_I(l=L, f=f)
#print(I0)
get_JVcurve(Isc, I0, Eg)
get_slme(Isc,I0)
#第二部分是画SLME随厚度变化曲线，需要输入曲线中厚度最大值和曲线撒点数
n = 100 #曲线撒的点
npts = int(L_max*n)
Y = []
X = []
dat = open('SLME-curve.dat', 'w', encoding='utf-8')
slme = 0
slme_max = 0
for i in range(npts+1):
l = i / n
Isc, I0 = get_I(l=l)
# print("厚度 =", l,"μm")
slme = get_slme(Isc, I0)
Y.append(slme)
X.append(l)
dat.write(str(l) + '\t' + str(slme) + '\n')
if slme >= slme_max:
slme_max = slme
l_max = l
dat.close()
print('SLME-curve内信息：')
print('SLME_max = ' + str(slme_max) + '\t' + '厚度 = ' + str(l_max) + 'μm')
plt.plot(X,Y)
plt.ylim(0,Y[-1]+0.025) # xlim、ylim：分别设置X、Y轴的显示范围
plt.xlim(0,L_max)
plt.title("SLME curve") # title：设置子图的标题
plt.savefig('SLME-curve.png')
plt.show()