The charge retention behaviour of MNOS structures with embedded Si or Ge nanocrystals are studied by computer simulation. It is obtained that the oxide thickness and the location of nanocrystlas affect the retention behaviour very strongly. The retention time changes from a few ms to several years.
When you are citing the document, use the following link http://essuir.sumdu.edu.ua/handle/123456789/3538

Horváth, Zsolt József

Kovács, B.

Molnár, K. Z.

Turmezei, P. J.

English

Molnár, K.Z.

Turmezei, P.

Horváth, Zs.J.

Electronic Sumy State University Institutional Repository

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE  NANOMATERIALS: APPLICATIONS AND PROPERTIES Vol. 2 No 4, 04NAESP14(3pp) (2013)   2304-1862/2013/2(4)04NAESP14(3) 04NAESP14-1  2013 Sumy State University Retention Behaviour of MNOS Memory Devices with Embedded Si or Ge Nanocrystals –  Computer Simulation  K.Z. Molnár1,*, P. Turmezei1,†, Zs.J. Horváth1,2,‡, B. Kovács1,§  1 Óbuda University, Kandó Kálmán Faculty of Electrical Engineering, Institute of Microelectronics and Technology, Budapest, Tavaszmező u. 15-17, H-1084 Hungary 2 Hungarian Academy of Sciences, Research Centre for Natural Sciences, Institute for Technical Physics and Mate-rials Science, Budapest, P.O. Box 49, H-1525 Hungary  (Received 05 June 2013; published online 31 August 2013)  The charge retention behaviour of MNOS structures with embedded Si or Ge nanocrystals are studied by computer simulation. It is obtained that the oxide thickness and the location of nanocrystlas affect the retention behaviour very strongly. The retention time changes from a few ms to several years.  Keywords: Non-volatile memory, MNOS, Tunneling, Retention.   PACS numbers: 73.40.Gk, 73.40.Qv, 73.63.Kv                                                             * molnar.karoly@kvk.uni-obuda.hu † turmezei@uni-obuda.hu ‡ horvath.zsolt@kvk.uni-obuda.hu § kovacs.balazs@kvk.uni-obuda.hu 1. INTRODUCTION  The two basic types of memory elements used in non-volatile (EEPROM and flash) memories are the floating gate and the SONOS (silicon-oxide-nitride-oxide-silicon) field effect transistors (FETs). Floating gate memory arrays face difficulties with technology scale-down. The main problem is that through defects or weak points of tunnel oxide with reduced thickness the whole amount of stored charge carrying the infor-mation can be lost. One of the possible solutions is to replace floating gate with separated semiconductor nanocrystals (NCs), which are electrically isolated [1]. But, in SONOS and MNOS (metal-nitride-oxide-silicon) devices (the latter were the first realized memory structures [2]) the charge is stored in traps located in the Si3N4 layer close to the Si3N4 / SiO2 interface. In these structures traps are isolated a'priori. However, formation of semiconductor NCs in silicon nitride based structures can enhance their charging and / or retention behaviour, as it was demonstrated first in SONOS structures by Rao and co-workers [3]. Nevertheless, only very few works are devoted to silicon nitride based memory structures with embedded NCs, although it seems obvious to merge the advantages of nanocrystal and silicon nitride based memory devices. We have studied both MNS (metal-nitride-silicon) and MNOS structures with Si NCs, and compared their memory behaviour with similar reference memory structures without NCs. MNOS structures with em-bedded Ge NCs has also been studied. For proper loca-tions of NCs in MNOS structures enhanced charge in-jection and retention properties were obtained [4, 5]. But, in the case of MNS structures the effect of NCs on charge injection properties was just opposite, than it was expected: the memory window shrinked with increasing duration of NC deposition [4, 5]. For the optimization of the memory properties of MNOS structures, an additional thin nitride layer was grown between the oxide layer and the sheet of embedded Ge or Si nanocrytals [5]. Indeed, for these SiO2 / Si3N4 / NC / Si3N4 structures much wider memory window was obtained than for the SiO2 / NC / Si3N4 struc-tures with NCs grown at the oxide / nitride interface, pre-pared by similar way. However, the retention behaviour changed in opposite way. For structures with embedded Si NCs a very short retention time (few seconds) was ob-tained, while for those with Ge NCs the retention time was close to 4000 years [5]. To understand the origin of these opposite behav-iour the charge injection and retention behaviour of SiO2 / Si3N4 / NC / Si3N4 and SiO2 / NC / Si3N4 struc-tures were studied by calculation of tunneling probabil-ity of electrons and holes to the structure for the case of charge injection (charging voltage pulse applied) [6, 7], and for the case of retention (no bias applied). The re-sults of these simple calculations are in cotradiction with most of the experimental results: both the injec-tion probability and the probability of escape of cap-tured electrons or holes decreases, if NCs are deeper in the nitride layer. In this paper the results of simulation of retention behaviour are presented.  2. RESULTS AND DISCUSSION  The band structure used for simualtions is presented in Fig. 1. The probability of electron (or hole) escape from nanocrystals equals the tunneling probability via the potential barrier determined by the actual electric field, to the substrate or to the nitride conduction (or valence) band. The tunneling probabilities have been calculated by WKB approximation [6, 7].  The probabilities were calculated to both directions, namely towards the metal and towards the silicon sub-strate. These tunneling probabilities are different due to different electric fields and different potential barriers.   K.Z. MOLNA L, P. TURMEZEI, ZS.J. HORVA TH, ET AL. PROC. NAP 2, 04NAESP14 (2013)   04NAESP14-2  Si 5.1 eV Si3N4 Al 3.1 eV 1.05 eV NC 8.0 eV SiO2  q·Voxide q·Vnitride 0 xoxide xnitride x 1.1 eV nanocrystal gap   Fig. 1 – Band diagram of MNOS structures with semiconduc-tor nanocrystals used for the calculations  -2.5E+04-2.3E+04-2.0E+04-1.8E+04-1.5E+04-1.3E+04-1.0E+04-7.5E+03-5.0E+03-2.5E+030.0E+000 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32Depth of nanocrystals, nmLogarithm of tunneling probabilityOptimal depth of nanocrystals  Fig. 2 – The logarithm of electron tunneling probability towards the substrate (dashed line) and towards the metal (solid line) during the escape of electrons from Si nanocrystals as a function of depth of nanocrystals from the oxide / nitride interface. The oxide thickness is 2.5 nm, the nitride thickness is 48 nm  If nanocrystals are close to the oxide / nitride interface, the tunneling probability is much higher towards the substrate, than towards the metal. However, getting nanocrystals deeper into the nitride layer, the probabil-ity towards the substrate decreases, while that towards the metal increases, as it can be seen in Fig. 2 for MNOS structures containing Si nanocrystals (the oxide thickness is 2.5 nm, the nitride thickness is 48 nm). The optimal depth of nanocrystals for retention behav-iour can be considered as the depth where the tunnel-ing probabilities towards the two directions equal.  But, it was obtained by our earlier calculations that the optimal location of nanocrystals for charge injection is at the oxide / nitride interface. The effect of injected charge on the threshold voltage is decreasing either with deeper location of nanocrystals. So, a compromise has to be made between these two opposite require-ments.  10-710-510-310-110110310510710910110123456710 years521 3 4Flat-band voltage (V)Time (s) Fig. 3 – The change of flat-band voltage (absolute value) due to charge escape from the nanocrystals. The initial charge is  1013 q/cm2 (  1.6  10 – 6 C/cm2) for holes and electrons, re-spectively. 1 – nanocrystals located at the oxide / nitride inter-face, oxide thickness 2 nm, electron escape from Si or Ge, hole escape from Si (three dependences very close to each other),  2 – nanocrystals located at the oxide / nitride interface, oxide thickness 2 nm, hole escape from Ge, 3 and 4 – nanocrystals located at the oxide / nitride interface, oxide thickness 3 nm or 4 nm, respectively, electron escape from Si, 5 – nanocrystals located at a depth of 3 nm from the oxide / nitride interface, oxide thickness 2 nm, electron escape from Si  The representative results of simulation of reten-tion behaviour are presented in Fig. 3. The depth of potential well, i.e. the material of nanocrystal (Si vs. Ge) does not influence the retention time very much, but the oxide thickness and location of nanocrystals exhibit a great effect. The retention time for electron escape varies about 10 orders of magnitude from sever-al hundred microseconds to several months, while the oxide thickness changes from 2 nm to 4 nm, if nano-crystals are located at the nitride/oxide interface. Even higher effect is obtained for the same oxide thickness, but different depth of nanocrystals in the nitride layer (compare curves 1 and 5). So, there is a very sharp de-pendence of retention behaviour on the oxide thickness and location of nanocrystals.  Another issue is the escape of charge carriers dur-ing reading of the information. As the electric fields are higher during reading, the tunneling probabilities are much higher yielding much faster loss of charge hold-ing the information. Therefore, the reading process has to be as short as possible.  3. RESULTS AND DISCUSSION  The retention behaviour of MNOS structures with embedded Si or Ge nanocrystals have been studied by computer simulation. It has been obtained that the oxide thickness and the location of nanocrystals affect the retention behaviour very strongly. The retention time changes from a few ms to several years. The deep-er the location of nanocrystals the longer the retention time.      RETENTION BEHAVIOUR OF MNOS MEMORY DEVICES… PROC. NAP 2, 04NAESP14 (2013)   04NAESP14-3 REFERENCES  1. Zs.J. Horváth, P. Basa, T. Jászi, A.E. Pap, L. Dobos, B. Pécz, L. Tóth, P. Szöllősi, K. Nagy, J. Nanosci. Nano-technol. 8, 812 (2008). 2. D. Frohman-Bentchkowsky, M. Lenzlinger, J. Appl. Phys. 40, 3307 (1969). 3. R.A. Rao , R.F. Steimle, M. Sadd, C.T. Swift, B. Hradsky, S. Straub, T. Merchant, M. Stoker, S.G.H. Anderson, M. Rossow, J. Yater, B. Acred, K. Harber, E.J. Prinz, B.E. White Jr., R. Muralidhar, Solid-State Electron. 48, 1463 (2004). 4. Zs.J. Horváth, P. Basa, Mater. Sci. Forum 609, 1 (2009). 5. Zs.J. Horváth, P. Basa, Nanocrystals and Quantum Dots of Group IV Semiconductors, (Eds. T.V. Torchynska, Yu.V. Vorobiev), (American Scientific Publishers: 2010). 6. Zs.J. Horváth, K.Z. Molnár, Gy. Molnár, P. Basa, T. Jászi, A.E. Pap, R. Lovassy, P. Turmezei, phys. status solidi c 9, 1370 (2012). 7. Zs.J. Horváth, P. Basa, T. Jászi, K.Z. Molnár, A.E. Pap, Gy. Molnár, Appl. Surf. Sci. 269, 23 (2013).  

Retention Behaviour of MNOS Memory Devices with Embedded Si or Ge Nanocrystals – Computer Simulation

SocioEconomic Challenges Journal (Sumy State University)

PROCEEDINGS OF THE INTERNATIONAL CONFERENCE  
NANOMATERIALS: APPLICATIONS AND PROPERTIES 
Vol. 2 No 4, 04NAESP14(3pp) (2013) 
 
 
2304-1862/2013/2(4)04NAESP14(3) 04NAESP14-1  2013 Sumy State University 
Retention Behaviour of MNOS Memory Devices with Embedded Si or Ge Nanocrystals –  
Computer Simulation 
 
K.Z. Molnár1,*, P. Turmezei1,†, Zs.J. Horváth1,2,‡, B. Kovács1,§ 
 
1 Óbuda University, Kandó Kálmán Faculty of Electrical Engineering, Institute of Microelectronics and Technology, 
Budapest, Tavaszmező u. 15-17, H-1084 Hungary 
2 Hungarian Academy of Sciences, Research Centre for Natural Sciences, Institute for Technical Physics and Mate-
rials Science, Budapest, P.O. Box 49, H-1525 Hungary 
 
(Received 05 June 2013; published online 31 August 2013) 
 
The charge retention behaviour of MNOS structures with embedded Si or Ge nanocrystals are studied 
by computer simulation. It is obtained that the oxide thickness and the location of nanocrystlas affect the 
retention behaviour very strongly. The retention time changes from a few ms to several years. 
 
Keywords: Non-volatile memory, MNOS, Tunneling, Retention. 
 
 PACS numbers: 73.40.Gk, 73.40.Qv, 73.63.Kv 
 
 
                                                          
* molnar.karoly@kvk.uni-obuda.hu 
† turmezei@uni-obuda.hu 
‡ horvath.zsolt@kvk.uni-obuda.hu 
§ kovacs.balazs@kvk.uni-obuda.hu 
1. INTRODUCTION 
 
The two basic types of memory elements used in 
non-volatile (EEPROM and flash) memories are the 
floating gate and the SONOS (silicon-oxide-nitride-
oxide-silicon) field effect transistors (FETs). Floating 
gate memory arrays face difficulties with technology 
scale-down. The main problem is that through defects 
or weak points of tunnel oxide with reduced thickness 
the whole amount of stored charge carrying the infor-
mation can be lost. One of the possible solutions is to 
replace floating gate with separated semiconductor 
nanocrystals (NCs), which are electrically isolated [1]. 
But, in SONOS and MNOS (metal-nitride-oxide-
silicon) devices (the latter were the first realized memory 
structures [2]) the charge is stored in traps located in the 
Si3N4 layer close to the Si3N4 / SiO2 interface. In these 
structures traps are isolated a'priori. However, formation 
of semiconductor NCs in silicon nitride based structures 
can enhance their charging and / or retention behaviour, 
as it was demonstrated first in SONOS structures by Rao 
and co-workers [3]. Nevertheless, only very few works are 
devoted to silicon nitride based memory structures with 
embedded NCs, although it seems obvious to merge the 
advantages of nanocrystal and silicon nitride based 
memory devices. 
We have studied both MNS (metal-nitride-silicon) 
and MNOS structures with Si NCs, and compared their 
memory behaviour with similar reference memory 
structures without NCs. MNOS structures with em-
bedded Ge NCs has also been studied. For proper loca-
tions of NCs in MNOS structures enhanced charge in-
jection and retention properties were obtained [4, 5]. 
But, in the case of MNS structures the effect of NCs on 
charge injection properties was just opposite, than it 
was expected: the memory window shrinked with 
increasing duration of NC deposition [4, 5]. 
For the optimization of the memory properties of 
MNOS structures, an additional thin nitride layer was 
grown between the oxide layer and the sheet of embedded 
Ge or Si nanocrytals [5]. Indeed, for these 
SiO2 / Si3N4 / NC / Si3N4 structures much wider memory 
window was obtained than for the SiO2 / NC / Si3N4 struc-
tures with NCs grown at the oxide / nitride interface, pre-
pared by similar way. However, the retention behaviour 
changed in opposite way. For structures with embedded 
Si NCs a very short retention time (few seconds) was ob-
tained, while for those with Ge NCs the retention time 
was close to 4000 years [5]. 
To understand the origin of these opposite behav-
iour the charge injection and retention behaviour of 
SiO2 / Si3N4 / NC / Si3N4 and SiO2 / NC / Si3N4 struc-
tures were studied by calculation of tunneling probabil-
ity of electrons and holes to the structure for the case of 
charge injection (charging voltage pulse applied) [6, 7], 
and for the case of retention (no bias applied). The re-
sults of these simple calculations are in cotradiction 
with most of the experimental results: both the injec-
tion probability and the probability of escape of cap-
tured electrons or holes decreases, if NCs are deeper in 
the nitride layer. In this paper the results of simulation 
of retention behaviour are presented. 
 
2. RESULTS AND DISCUSSION 
 
The band structure used for simualtions is presented 
in Fig. 1. The probability of electron (or hole) escape 
from nanocrystals equals the tunneling probability via 
the potential barrier determined by the actual electric 
field, to the substrate or to the nitride conduction (or 
valence) band. The tunneling probabilities have been 
calculated by WKB approximation [6, 7].  
The probabilities were calculated to both directions, 
namely towards the metal and towards the silicon sub-
strate. These tunneling probabilities are different due 
to different electric fields and different potential barriers.  
 K.Z. MOLNA L, P. TURMEZEI, ZS.J. HORVA TH, ET AL. PROC. NAP 2, 04NAESP14 (2013) 
 
 
04NAESP14-2 
 
Si 
5.1 eV 
Si3N4 Al 
3.1 eV 
1.05 eV 
NC 
8.0 eV 
SiO2  
q·Voxide 
q·Vnitride 
0 xoxide xnitride 
x 
1.1 eV 
nanocrystal gap 
 
 
Fig. 1 – Band diagram of MNOS structures with semiconduc-
tor nanocrystals used for the calculations 
 
-2.5E+04
-2.3E+04
-2.0E+04
-1.8E+04
-1.5E+04
-1.3E+04
-1.0E+04
-7.5E+03
-5.0E+03
-2.5E+03
0.0E+00
0 2 4 6 8 10 12 14 16 18 20 22 24 26 28 30 32
Depth of nanocrystals, nm
L
o
g
a
ri
th
m
 o
f 
tu
n
n
e
li
n
g
 
p
ro
b
a
b
il
it
y
Optimal depth of 
nanocrystals
 
 
Fig. 2 – The logarithm of electron tunneling probability towards 
the substrate (dashed line) and towards the metal (solid line) 
during the escape of electrons from Si nanocrystals as a function 
of depth of nanocrystals from the oxide / nitride interface. The 
oxide thickness is 2.5 nm, the nitride thickness is 48 nm 
 
If nanocrystals are close to the oxide / nitride interface, 
the tunneling probability is much higher towards the 
substrate, than towards the metal. However, getting 
nanocrystals deeper into the nitride layer, the probabil-
ity towards the substrate decreases, while that towards 
the metal increases, as it can be seen in Fig. 2 for 
MNOS structures containing Si nanocrystals (the oxide 
thickness is 2.5 nm, the nitride thickness is 48 nm). 
The optimal depth of nanocrystals for retention behav-
iour can be considered as the depth where the tunnel-
ing probabilities towards the two directions equal.  
But, it was obtained by our earlier calculations that 
the optimal location of nanocrystals for charge injection 
is at the oxide / nitride interface. The effect of injected 
charge on the threshold voltage is decreasing either 
with deeper location of nanocrystals. So, a compromise 
has to be made between these two opposite require-
ments. 
 
10
-7
10
-5
10
-3
10
-1
10
1
10
3
10
5
10
7
10
9
10
11
0
1
2
3
4
5
6
7
10 years
521 3 4
F
la
t-
b
a
n
d
 v
o
lt
a
g
e
 (
V
)
Time (s)
 
Fig. 3 – The change of flat-band voltage (absolute value) due 
to charge escape from the nanocrystals. The initial charge is 
 1013 q/cm2 (  1.6  10 – 6 C/cm2) for holes and electrons, re-
spectively. 1 – nanocrystals located at the oxide / nitride inter-
face, oxide thickness 2 nm, electron escape from Si or Ge, hole 
escape from Si (three dependences very close to each other),  
2 – nanocrystals located at the oxide / nitride interface, oxide 
thickness 2 nm, hole escape from Ge, 3 and 4 – nanocrystals 
located at the oxide / nitride interface, oxide thickness 3 nm or 
4 nm, respectively, electron escape from Si, 5 – nanocrystals 
located at a depth of 3 nm from the oxide / nitride interface, 
oxide thickness 2 nm, electron escape from Si 
 
The representative results of simulation of reten-
tion behaviour are presented in Fig. 3. The depth of 
potential well, i.e. the material of nanocrystal (Si vs. 
Ge) does not influence the retention time very much, 
but the oxide thickness and location of nanocrystals 
exhibit a great effect. The retention time for electron 
escape varies about 10 orders of magnitude from sever-
al hundred microseconds to several months, while the 
oxide thickness changes from 2 nm to 4 nm, if nano-
crystals are located at the nitride/oxide interface. Even 
higher effect is obtained for the same oxide thickness, 
but different depth of nanocrystals in the nitride layer 
(compare curves 1 and 5). So, there is a very sharp de-
pendence of retention behaviour on the oxide thickness 
and location of nanocrystals.  
Another issue is the escape of charge carriers dur-
ing reading of the information. As the electric fields are 
higher during reading, the tunneling probabilities are 
much higher yielding much faster loss of charge hold-
ing the information. Therefore, the reading process has 
to be as short as possible. 
 
3. RESULTS AND DISCUSSION 
 
The retention behaviour of MNOS structures with 
embedded Si or Ge nanocrystals have been studied by 
computer simulation. It has been obtained that the 
oxide thickness and the location of nanocrystals affect 
the retention behaviour very strongly. The retention 
time changes from a few ms to several years. The deep-
er the location of nanocrystals the longer the retention 
time. 
 
 
 
 
 RETENTION BEHAVIOUR OF MNOS MEMORY DEVICES… PROC. NAP 2, 04NAESP14 (2013) 
 
 
04NAESP14-3 
REFERENCES 
 
1. Zs.J. Horváth, P. Basa, T. Jászi, A.E. Pap, L. Dobos, 
B. Pécz, L. Tóth, P. Szöllősi, K. Nagy, J. Nanosci. Nano-
technol. 8, 812 (2008). 
2. D. Frohman-Bentchkowsky, M. Lenzlinger, J. Appl. Phys. 
40, 3307 (1969). 
3. R.A. Rao , R.F. Steimle, M. Sadd, C.T. Swift, B. Hradsky, 
S. Straub, T. Merchant, M. Stoker, S.G.H. Anderson, 
M. Rossow, J. Yater, B. Acred, K. Harber, E.J. Prinz, 
B.E. White Jr., R. Muralidhar, Solid-State Electron. 48, 
1463 (2004). 
4. Zs.J. Horváth, P. Basa, Mater. Sci. Forum 609, 1 (2009). 
5. Zs.J. Horváth, P. Basa, Nanocrystals and Quantum Dots 
of Group IV Semiconductors, (Eds. T.V. Torchynska, 
Yu.V. Vorobiev), (American Scientific Publishers: 2010). 
6. Zs.J. Horváth, K.Z. Molnár, Gy. Molnár, P. Basa, T. Jászi, 
A.E. Pap, R. Lovassy, P. Turmezei, phys. status solidi c 9, 
1370 (2012). 
7. Zs.J. Horváth, P. Basa, T. Jászi, K.Z. Molnár, A.E. Pap, 
Gy. Molnár, Appl. Surf. Sci. 269, 23 (2013). 
 


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Retention Behaviour of MNOS Memory Devices with Embedded Si or Ge Nanocrystals – Computer Simulation

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