ee5342 – semiconductor device modeling and characterization lecture 21 - spring 2005
DESCRIPTION
EE5342 – Semiconductor Device Modeling and Characterization Lecture 21 - Spring 2005. Professor Ronald L. Carter [email protected] http://www.uta.edu/ronc/. Gummel-Poon Static npn Circuit Model. Intrinsic Transistor. C. R C. I BR. B. R BB. I LC. I CC - I EC = {IS/Q B }* - PowerPoint PPT PresentationTRANSCRIPT
L21 April 7 1
EE5342 – Semiconductor Device Modeling and CharacterizationLecture 21 - Spring 2005
Professor Ronald L. [email protected]
http://www.uta.edu/ronc/
L21 April 7 2
Gummel-Poon Staticnpn Circuit Model
C
E
B
B’
ILC
ILEIBF
IBR ICC - IEC = {IS/QB}*
{exp(vBE/NFVt)-exp(vBC/NRVt)}
RC
RE
RBB
IntrinsicTransistor
L21 April 7 3
Gummel Poon npnModel Equations
IBF = IS expf(vBE/NFVt)/BF
ILE = ISE expf(vBE/NEVt)
IBR = IS expf(vBC/NRVt)/BR
ILC = ISC expf(vBC/NCVt)
ICC - IEC = IS(exp(vBE/NFVt - exp(vBC/NRVt)/QB
QB = {½ +¼ +(BF IBF/IKF + BR IBR/IKR)1/2} (1 - vBC/VAF - vBE/VAR )-1
L21 April 7 4
iE = - IEC =
(IS/QB)exp(vBC/NRVt),
where ICC = 0, and
QB-1
=
(1-vBC/VAF-vBE/VAR )
{IKR terms}-1,
so since vBE = vBC - vEC,
VAR ~ iE/[iE/vBE]vBC
VAR ParameterExtraction (rEarly)
+
-+
-
iE
iB
vECvBC
0.2 < vEC < 5.0
0.7 < vBC < 0.9
Reverse Active Operation
L21 April 7 5
0.0000
0.0002
0.0004
0.0006
0 1 2 3 4 5
iE(A) vs. vEC (V)
Reverse EarlyData for VAR• At a particular data
point, an effective VAR value can be calculated
VAReff = abs{iE/[iE/vBE]vBC}
• The most accurate is at vBE = 0 (why?)
vBC = 0.85 V
vBC = 0.75 V
L21 April 7 6
198
200
202
204
0 1 2 3 4
VAReff(V) vs. vEC (V)
Reverse EarlyVAR extraction
VAReff =
|iE/[iE/vBE]vBC|
• VAR was set at 200V for this data
• When vBE = 0
vBC = 0.75VAR=200.5
vBC = 0.85VAR=200.2
vBC = 0.85 V
vBC = 0.75 V
L21 April 7 7
+
-+
-
VAF ParameterExtraction (fEarly)
iC
iB
vCEvBE
0.2 < vCE < 5.0
0.7 < vBE < 0.9
Forward Active Operation
iC = ICC =
(IS/QB)exp(vBE/NFVt),
where ICE = 0, and
QB-1
=
(1-vBC/VAF-vBE/VAR )*
{IKF terms}-1,so since vBC = vBE -
vCE,
VAF ~|iC/[iC/vBC]vBE|
L21 April 7 8
0.000
0.001
0.002
0.003
0 1 2 3 4 5
iC(A) vs. vCE (V)
Forward EarlyData for VAF• At a particular
data point, an effective VAF value can be calculated
VAFeff =
abs{iC/[iC/vBC]vBE}
• The most accurate is at vBC = 0 (why?)
vBE = 0.85 V
vBE = 0.75 V
L21 April 7 9
99
101
103
105
0 1 2 3 4VAFeff(V) vs. vCE (V)
Forward EarlyVAf extraction
VAFeff =
|iC/[iC/vBC]vBE|
• VAF was set at 100V for this data
• When vBC = 0
vBE = 0.75VAF=101.2
vBE = 0.85VAF=101.0
vBE = 0.85 V
vBE = 0.75 V
L21 April 7 10
BJT CharacterizationReverse Gummel
+
-
iE
RC
iB
RE
RB
vBCxvBC
vBE
++
-
-
vBEx= 0 = vBE + iBRB - iERE
vBCx = vBC +iBRB +(iB+iE)RC
iB = IBR + ILC =
(IS/BR)expf(vBC/NRVt)
+ ISCexpf(vBC/NCVt)
iE = RIBR/QB =
ISexpf(vBC/NRVt)
(1-vBC/VAF-vBE/VAR )
{IKR terms}-1
L21 April 7 11
1.E-10
1.E-08
1.E-06
1.E-04
1.E-02
0.1 0.3 0.5 0.7 0.9
Sample rg data forparameter extraction
• IS=10f• Nr=1• Br=2• Isc=10p • Nc=2• Ikr=.1m• Vaf=100• Rc=5• Rb=100
iE, iB vs. vBCext
iB data
iE data
L21 April 7 12
1.E-10
1.E-08
1.E-06
1.E-04
1.E-02
0.1 0.3 0.5 0.7 0.9
Region a - IKRIS, RB, RC, NR, VAF
Region b - IS, NR, VAF, RB, RC
Region c - IS/BR, NR, RB, RC
Region d - IS/BR, NRRegion e - ISC, NC
Reverse GummelData Sensitivities
iE(A),iB(A) vs. vBC(V)
iE
vBCx = 0
iB
a
b
c
d
e
L21 April 7 13
1.E-10
1.E-08
1.E-06
1.E-04
1.E-02
0.1 0.3 0.5 0.7 0.9
Region a - IKRIS, RB, RC, NR, VAF
Region b - IS, NR, VAF, RB, RC
Region c - IS/BR, NR, RB, RC
Region d - IS/BR, NRRegion e - ISC, NC
Reverse GummelData Sensitivities
iE(A),iB(A) vs. vBC(V)
iE
vBCx = 0
iB
a
b
c
d
e
L21 April 7 14
Region (b) rgData SensitivitiesRegion b - IS, NR, VAF, RB, RCiE = RIBR/QB = ISexp(vBC/NRVt)
(1-vBC/VAF-vBE/VAR ){IKR terms}-1
L21 April 7 15
Region (a) rgData Sensitivities
Region a - IKRIS, RB, RC, NR, VAFiE=RIBR/QB~[ISIKR]1/2exp(vBC/2NRVt)
(1-vBC/VAF-vBE/VAR )
L21 April 7 16
Region (e) rgData SensitivitiesRegion e - ISC, NCiB = IBR + ILC = IS/BRexpf(vBC/NRVt)
+ ISCexpf(vBC/NCVt)
L21 April 7 17
Region (d) rgData SensitivitiesRegion d - BR, IS, NRiB = IBR + ILC = IS/BRexpf(vBC/NRVt)
+ ISCexpf(vBC/NCVt)
L21 April 7 18
Region (c) rgData SensitivitiesRegion c - BR, IS, NR, RB, RCiB = IBR + ILC = IS/BRexpf(vBC/NRVt)
+ ISCexpf(vBC/NCVt)
L21 April 7 19
0.9
1.1
1.3
1.5
1.7
1.9
2.1
0.1 0.3 0.5 0.7 0.9
Simple extraction of NR, NC from rg data
Data set used Nr = 1Nc = 2
Flat Neff region from iE data = 1.00 for 0.195 < vBC < 0.375
Max Neff value from iB data is 1.914 for 0.195 < vBC < 0.205
NEeff vs. vBCext
iB
data
iE data
L21 April 7 20
1.E-16
1.E-14
1.E-12
1.E-10
0.2 0.4 0.6
Simple extractionof IS, ISC from data
Data set used • IS = 10fA• ISC = 10pAMin ISeff for iE data =
9.96E-15 for vBC = 0.200
Max ISeff value for iB data is 8.44E-12 for vBC = 0.200ISeff vs. vBCext
iB data
iE data
L21 April 7 21
0.0
0.5
1.0
1.5
2.0
1.E-10 1.E-06 1.E-02
Simple extractionof BR from data
• Data set used Br = 2
• Extraction gives max iE/iB = 1.7 for 0.48 V < vBC < 0.55V 1.13A < iE < 14.4A
• Minimum value of Neff =1 for same range
iE/iB vs. iE
L21 April 7 22
Forward ActiveHybrid-pi Circuit model
Fig 9.33*
L21 April 7 23
Gummel PoonBase ResistanceIf IRB = 0, RBB = RBM+(RB-RBM)/QB
If IRB > 0
RB = RBM + 3(RB-RBM)(tan(z)-z)/(ztan2(z))
Regarding (i) RBB and (x) RTh on previous slide,
RBB = Rbmin + Rbmax/(1 + iB/IRB)RB
1
IRBi144
1i
IRB24
z 2B
B
2
L21 April 7 24
RB and RE from FG data
RE slope and , RERB intercept has
ii
vs. ,i
VNFi
v of plot a Thus,
REii
RERBi
VNFi
v
REii
RERBi
v
VNFi
1ii
ISE1VNF
REiRERBivexp
BFIS
i
B
C
BB
X,BE
B
C
BB
X,BE
B
C
B
X,BE
t
B
B
B
t
CBX,BEB
L21 April 7 25
RB and RE from FG data
• In this case, the data were generated with
• RB = 98.76 , compare to
77.4 - 32.3• RE = 1.432 ,
compare to 32.3
y = 32.3x + 77.4
120
130
140
150
1.4 1.6 1.8 2.0
B
C
BB
X,BE
ii
vs. ,i
VNFi
v
L21 April 7 26
h11_vs_ib
L21 April 7 27
h11_vs_frequency
L21 April 7 28
h11_vs_1/ib