Analytical Macrospin Modeling of the Stochastic Switching Time of Spin-Transfer Torque Devices
Owing to their nonvolatility, outstanding endurance, high write and read speeds, and CMOS process compatibility, spin-transfer torque magnetoresistive memories (MRAMs) are prime candidates for innovative memory applications. However, the switching delay of their core components-the magnetic tunnel j...
Ausführliche Beschreibung
Autor*in: |
Vincent, Adrien F [verfasserIn] |
---|
Format: |
Artikel |
---|---|
Sprache: |
Englisch |
Erschienen: |
2015 |
---|
Schlagwörter: |
spin-transfer torque magnetoresistive memories physical macrospin simulations Distribution (Probability theory) |
---|
Übergeordnetes Werk: |
Enthalten in: IEEE transactions on electron devices - New York, NY : IEEE, 1963, 62(2015), 1, Seite 164-170 |
---|---|
Übergeordnetes Werk: |
volume:62 ; year:2015 ; number:1 ; pages:164-170 |
Links: |
---|
DOI / URN: |
10.1109/TED.2014.2372475 |
---|
Katalog-ID: |
OLC1967766029 |
---|
LEADER | 01000caa a2200265 4500 | ||
---|---|---|---|
001 | OLC1967766029 | ||
003 | DE-627 | ||
005 | 20210716042055.0 | ||
007 | tu | ||
008 | 160206s2015 xx ||||| 00| ||eng c | ||
024 | 7 | |a 10.1109/TED.2014.2372475 |2 doi | |
028 | 5 | 2 | |a PQ20160617 |
035 | |a (DE-627)OLC1967766029 | ||
035 | |a (DE-599)GBVOLC1967766029 | ||
035 | |a (PRQ)c2574-c32dbd5c0078f165ffbc2eb01262c23a945176fb4219fe51c786a432ea81282c0 | ||
035 | |a (KEY)0079428720150000062000100164analyticalmacrospinmodelingofthestochasticswitchin | ||
040 | |a DE-627 |b ger |c DE-627 |e rakwb | ||
041 | |a eng | ||
082 | 0 | 4 | |a 620 |q DNB |
100 | 1 | |a Vincent, Adrien F |e verfasserin |4 aut | |
245 | 1 | 0 | |a Analytical Macrospin Modeling of the Stochastic Switching Time of Spin-Transfer Torque Devices |
264 | 1 | |c 2015 | |
336 | |a Text |b txt |2 rdacontent | ||
337 | |a ohne Hilfsmittel zu benutzen |b n |2 rdamedia | ||
338 | |a Band |b nc |2 rdacarrier | ||
520 | |a Owing to their nonvolatility, outstanding endurance, high write and read speeds, and CMOS process compatibility, spin-transfer torque magnetoresistive memories (MRAMs) are prime candidates for innovative memory applications. However, the switching delay of their core components-the magnetic tunnel junctions (MTJs)-is a stochastic quantity. To account for this in electronic design, only partial models (working in extreme regimes) are available. In this paper, we propose an analytical model for the stochastic switching delay of a current-driven MTJ, with in-plane magnetization, that agrees with physical simulations, from low- to high-current regimes through intermediate regime. We performed physical macrospin simulations of MTJs for a wide range of current. We developed an analytical model for the mean switching delay that fits those simulations results, and smoothly connects well-accepted models for the extreme low and extreme high currents limits. In addition, a probability distribution in agreement with our simulations results is proposed, leading to a full model of the stochastic switching delay. An example for the application of the model is proposed. Our analytical model can help to evaluate the error rate in MRAM designs, and allow designing innovative electronic circuits that exploit the intrinsic stochastic behavior of MTJs as a beneficial feature. | ||
650 | 4 | |a MRAM | |
650 | 4 | |a simulation | |
650 | 4 | |a Stochastic processes | |
650 | 4 | |a spin-transfer torque magnetoresistive memories | |
650 | 4 | |a magnetic tunnel junctions | |
650 | 4 | |a in-plane magnetization | |
650 | 4 | |a MRAM devices | |
650 | 4 | |a probability | |
650 | 4 | |a physical macrospin simulations | |
650 | 4 | |a magnetic memories | |
650 | 4 | |a Switches | |
650 | 4 | |a stochastic switching delay | |
650 | 4 | |a CMOS process compatibility | |
650 | 4 | |a Mathematical model | |
650 | 4 | |a Delays | |
650 | 4 | |a current-driven MTJ | |
650 | 4 | |a intrinsic stochastic behavior | |
650 | 4 | |a mean switching | |
650 | 4 | |a magnetisation | |
650 | 4 | |a Current density | |
650 | 4 | |a partial models | |
650 | 4 | |a modeling | |
650 | 4 | |a Magnetic devices | |
650 | 4 | |a error rate | |
650 | 4 | |a Analytical models | |
650 | 4 | |a magnetic tunnelling | |
650 | 4 | |a Magnetic tunneling | |
650 | 4 | |a probability distribution | |
650 | 4 | |a Computer memory | |
650 | 4 | |a Random access memory | |
650 | 4 | |a Design | |
650 | 4 | |a Models | |
650 | 4 | |a Magnetoresistance | |
650 | 4 | |a Analysis | |
650 | 4 | |a Magnetic tunnel junctions | |
650 | 4 | |a Distribution (Probability theory) | |
650 | 4 | |a Stochastic analysis | |
650 | 4 | |a Complementary metal oxide semiconductors | |
650 | 4 | |a Design and construction | |
650 | 4 | |a Usage | |
700 | 1 | |a Locatelli, Nicolas |4 oth | |
700 | 1 | |a Klein, Jacques-Olivier |4 oth | |
700 | 1 | |a Zhao, Weisheng S |4 oth | |
700 | 1 | |a Galdin-Retailleau, Sylvie |4 oth | |
700 | 1 | |a Querlioz, Damien |4 oth | |
773 | 0 | 8 | |i Enthalten in |t IEEE transactions on electron devices |d New York, NY : IEEE, 1963 |g 62(2015), 1, Seite 164-170 |w (DE-627)129602922 |w (DE-600)241634-7 |w (DE-576)015096734 |x 0018-9383 |7 nnns |
773 | 1 | 8 | |g volume:62 |g year:2015 |g number:1 |g pages:164-170 |
856 | 4 | 1 | |u http://dx.doi.org/10.1109/TED.2014.2372475 |3 Volltext |
856 | 4 | 2 | |u http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6981938 |
856 | 4 | 2 | |u http://search.proquest.com/docview/1640794838 |
912 | |a GBV_USEFLAG_A | ||
912 | |a SYSFLAG_A | ||
912 | |a GBV_OLC | ||
912 | |a SSG-OLC-TEC | ||
912 | |a SSG-OLC-MAT | ||
912 | |a GBV_ILN_70 | ||
912 | |a GBV_ILN_170 | ||
912 | |a GBV_ILN_2004 | ||
912 | |a GBV_ILN_4313 | ||
912 | |a GBV_ILN_4314 | ||
951 | |a AR | ||
952 | |d 62 |j 2015 |e 1 |h 164-170 |
author_variant |
a f v af afv |
---|---|
matchkey_str |
article:00189383:2015----::nltclarsimdlnotetcatcwthntmosi |
hierarchy_sort_str |
2015 |
publishDate |
2015 |
allfields |
10.1109/TED.2014.2372475 doi PQ20160617 (DE-627)OLC1967766029 (DE-599)GBVOLC1967766029 (PRQ)c2574-c32dbd5c0078f165ffbc2eb01262c23a945176fb4219fe51c786a432ea81282c0 (KEY)0079428720150000062000100164analyticalmacrospinmodelingofthestochasticswitchin DE-627 ger DE-627 rakwb eng 620 DNB Vincent, Adrien F verfasserin aut Analytical Macrospin Modeling of the Stochastic Switching Time of Spin-Transfer Torque Devices 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Owing to their nonvolatility, outstanding endurance, high write and read speeds, and CMOS process compatibility, spin-transfer torque magnetoresistive memories (MRAMs) are prime candidates for innovative memory applications. However, the switching delay of their core components-the magnetic tunnel junctions (MTJs)-is a stochastic quantity. To account for this in electronic design, only partial models (working in extreme regimes) are available. In this paper, we propose an analytical model for the stochastic switching delay of a current-driven MTJ, with in-plane magnetization, that agrees with physical simulations, from low- to high-current regimes through intermediate regime. We performed physical macrospin simulations of MTJs for a wide range of current. We developed an analytical model for the mean switching delay that fits those simulations results, and smoothly connects well-accepted models for the extreme low and extreme high currents limits. In addition, a probability distribution in agreement with our simulations results is proposed, leading to a full model of the stochastic switching delay. An example for the application of the model is proposed. Our analytical model can help to evaluate the error rate in MRAM designs, and allow designing innovative electronic circuits that exploit the intrinsic stochastic behavior of MTJs as a beneficial feature. MRAM simulation Stochastic processes spin-transfer torque magnetoresistive memories magnetic tunnel junctions in-plane magnetization MRAM devices probability physical macrospin simulations magnetic memories Switches stochastic switching delay CMOS process compatibility Mathematical model Delays current-driven MTJ intrinsic stochastic behavior mean switching magnetisation Current density partial models modeling Magnetic devices error rate Analytical models magnetic tunnelling Magnetic tunneling probability distribution Computer memory Random access memory Design Models Magnetoresistance Analysis Magnetic tunnel junctions Distribution (Probability theory) Stochastic analysis Complementary metal oxide semiconductors Design and construction Usage Locatelli, Nicolas oth Klein, Jacques-Olivier oth Zhao, Weisheng S oth Galdin-Retailleau, Sylvie oth Querlioz, Damien oth Enthalten in IEEE transactions on electron devices New York, NY : IEEE, 1963 62(2015), 1, Seite 164-170 (DE-627)129602922 (DE-600)241634-7 (DE-576)015096734 0018-9383 nnns volume:62 year:2015 number:1 pages:164-170 http://dx.doi.org/10.1109/TED.2014.2372475 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6981938 http://search.proquest.com/docview/1640794838 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_170 GBV_ILN_2004 GBV_ILN_4313 GBV_ILN_4314 AR 62 2015 1 164-170 |
spelling |
10.1109/TED.2014.2372475 doi PQ20160617 (DE-627)OLC1967766029 (DE-599)GBVOLC1967766029 (PRQ)c2574-c32dbd5c0078f165ffbc2eb01262c23a945176fb4219fe51c786a432ea81282c0 (KEY)0079428720150000062000100164analyticalmacrospinmodelingofthestochasticswitchin DE-627 ger DE-627 rakwb eng 620 DNB Vincent, Adrien F verfasserin aut Analytical Macrospin Modeling of the Stochastic Switching Time of Spin-Transfer Torque Devices 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Owing to their nonvolatility, outstanding endurance, high write and read speeds, and CMOS process compatibility, spin-transfer torque magnetoresistive memories (MRAMs) are prime candidates for innovative memory applications. However, the switching delay of their core components-the magnetic tunnel junctions (MTJs)-is a stochastic quantity. To account for this in electronic design, only partial models (working in extreme regimes) are available. In this paper, we propose an analytical model for the stochastic switching delay of a current-driven MTJ, with in-plane magnetization, that agrees with physical simulations, from low- to high-current regimes through intermediate regime. We performed physical macrospin simulations of MTJs for a wide range of current. We developed an analytical model for the mean switching delay that fits those simulations results, and smoothly connects well-accepted models for the extreme low and extreme high currents limits. In addition, a probability distribution in agreement with our simulations results is proposed, leading to a full model of the stochastic switching delay. An example for the application of the model is proposed. Our analytical model can help to evaluate the error rate in MRAM designs, and allow designing innovative electronic circuits that exploit the intrinsic stochastic behavior of MTJs as a beneficial feature. MRAM simulation Stochastic processes spin-transfer torque magnetoresistive memories magnetic tunnel junctions in-plane magnetization MRAM devices probability physical macrospin simulations magnetic memories Switches stochastic switching delay CMOS process compatibility Mathematical model Delays current-driven MTJ intrinsic stochastic behavior mean switching magnetisation Current density partial models modeling Magnetic devices error rate Analytical models magnetic tunnelling Magnetic tunneling probability distribution Computer memory Random access memory Design Models Magnetoresistance Analysis Magnetic tunnel junctions Distribution (Probability theory) Stochastic analysis Complementary metal oxide semiconductors Design and construction Usage Locatelli, Nicolas oth Klein, Jacques-Olivier oth Zhao, Weisheng S oth Galdin-Retailleau, Sylvie oth Querlioz, Damien oth Enthalten in IEEE transactions on electron devices New York, NY : IEEE, 1963 62(2015), 1, Seite 164-170 (DE-627)129602922 (DE-600)241634-7 (DE-576)015096734 0018-9383 nnns volume:62 year:2015 number:1 pages:164-170 http://dx.doi.org/10.1109/TED.2014.2372475 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6981938 http://search.proquest.com/docview/1640794838 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_170 GBV_ILN_2004 GBV_ILN_4313 GBV_ILN_4314 AR 62 2015 1 164-170 |
allfields_unstemmed |
10.1109/TED.2014.2372475 doi PQ20160617 (DE-627)OLC1967766029 (DE-599)GBVOLC1967766029 (PRQ)c2574-c32dbd5c0078f165ffbc2eb01262c23a945176fb4219fe51c786a432ea81282c0 (KEY)0079428720150000062000100164analyticalmacrospinmodelingofthestochasticswitchin DE-627 ger DE-627 rakwb eng 620 DNB Vincent, Adrien F verfasserin aut Analytical Macrospin Modeling of the Stochastic Switching Time of Spin-Transfer Torque Devices 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Owing to their nonvolatility, outstanding endurance, high write and read speeds, and CMOS process compatibility, spin-transfer torque magnetoresistive memories (MRAMs) are prime candidates for innovative memory applications. However, the switching delay of their core components-the magnetic tunnel junctions (MTJs)-is a stochastic quantity. To account for this in electronic design, only partial models (working in extreme regimes) are available. In this paper, we propose an analytical model for the stochastic switching delay of a current-driven MTJ, with in-plane magnetization, that agrees with physical simulations, from low- to high-current regimes through intermediate regime. We performed physical macrospin simulations of MTJs for a wide range of current. We developed an analytical model for the mean switching delay that fits those simulations results, and smoothly connects well-accepted models for the extreme low and extreme high currents limits. In addition, a probability distribution in agreement with our simulations results is proposed, leading to a full model of the stochastic switching delay. An example for the application of the model is proposed. Our analytical model can help to evaluate the error rate in MRAM designs, and allow designing innovative electronic circuits that exploit the intrinsic stochastic behavior of MTJs as a beneficial feature. MRAM simulation Stochastic processes spin-transfer torque magnetoresistive memories magnetic tunnel junctions in-plane magnetization MRAM devices probability physical macrospin simulations magnetic memories Switches stochastic switching delay CMOS process compatibility Mathematical model Delays current-driven MTJ intrinsic stochastic behavior mean switching magnetisation Current density partial models modeling Magnetic devices error rate Analytical models magnetic tunnelling Magnetic tunneling probability distribution Computer memory Random access memory Design Models Magnetoresistance Analysis Magnetic tunnel junctions Distribution (Probability theory) Stochastic analysis Complementary metal oxide semiconductors Design and construction Usage Locatelli, Nicolas oth Klein, Jacques-Olivier oth Zhao, Weisheng S oth Galdin-Retailleau, Sylvie oth Querlioz, Damien oth Enthalten in IEEE transactions on electron devices New York, NY : IEEE, 1963 62(2015), 1, Seite 164-170 (DE-627)129602922 (DE-600)241634-7 (DE-576)015096734 0018-9383 nnns volume:62 year:2015 number:1 pages:164-170 http://dx.doi.org/10.1109/TED.2014.2372475 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6981938 http://search.proquest.com/docview/1640794838 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_170 GBV_ILN_2004 GBV_ILN_4313 GBV_ILN_4314 AR 62 2015 1 164-170 |
allfieldsGer |
10.1109/TED.2014.2372475 doi PQ20160617 (DE-627)OLC1967766029 (DE-599)GBVOLC1967766029 (PRQ)c2574-c32dbd5c0078f165ffbc2eb01262c23a945176fb4219fe51c786a432ea81282c0 (KEY)0079428720150000062000100164analyticalmacrospinmodelingofthestochasticswitchin DE-627 ger DE-627 rakwb eng 620 DNB Vincent, Adrien F verfasserin aut Analytical Macrospin Modeling of the Stochastic Switching Time of Spin-Transfer Torque Devices 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Owing to their nonvolatility, outstanding endurance, high write and read speeds, and CMOS process compatibility, spin-transfer torque magnetoresistive memories (MRAMs) are prime candidates for innovative memory applications. However, the switching delay of their core components-the magnetic tunnel junctions (MTJs)-is a stochastic quantity. To account for this in electronic design, only partial models (working in extreme regimes) are available. In this paper, we propose an analytical model for the stochastic switching delay of a current-driven MTJ, with in-plane magnetization, that agrees with physical simulations, from low- to high-current regimes through intermediate regime. We performed physical macrospin simulations of MTJs for a wide range of current. We developed an analytical model for the mean switching delay that fits those simulations results, and smoothly connects well-accepted models for the extreme low and extreme high currents limits. In addition, a probability distribution in agreement with our simulations results is proposed, leading to a full model of the stochastic switching delay. An example for the application of the model is proposed. Our analytical model can help to evaluate the error rate in MRAM designs, and allow designing innovative electronic circuits that exploit the intrinsic stochastic behavior of MTJs as a beneficial feature. MRAM simulation Stochastic processes spin-transfer torque magnetoresistive memories magnetic tunnel junctions in-plane magnetization MRAM devices probability physical macrospin simulations magnetic memories Switches stochastic switching delay CMOS process compatibility Mathematical model Delays current-driven MTJ intrinsic stochastic behavior mean switching magnetisation Current density partial models modeling Magnetic devices error rate Analytical models magnetic tunnelling Magnetic tunneling probability distribution Computer memory Random access memory Design Models Magnetoresistance Analysis Magnetic tunnel junctions Distribution (Probability theory) Stochastic analysis Complementary metal oxide semiconductors Design and construction Usage Locatelli, Nicolas oth Klein, Jacques-Olivier oth Zhao, Weisheng S oth Galdin-Retailleau, Sylvie oth Querlioz, Damien oth Enthalten in IEEE transactions on electron devices New York, NY : IEEE, 1963 62(2015), 1, Seite 164-170 (DE-627)129602922 (DE-600)241634-7 (DE-576)015096734 0018-9383 nnns volume:62 year:2015 number:1 pages:164-170 http://dx.doi.org/10.1109/TED.2014.2372475 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6981938 http://search.proquest.com/docview/1640794838 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_170 GBV_ILN_2004 GBV_ILN_4313 GBV_ILN_4314 AR 62 2015 1 164-170 |
allfieldsSound |
10.1109/TED.2014.2372475 doi PQ20160617 (DE-627)OLC1967766029 (DE-599)GBVOLC1967766029 (PRQ)c2574-c32dbd5c0078f165ffbc2eb01262c23a945176fb4219fe51c786a432ea81282c0 (KEY)0079428720150000062000100164analyticalmacrospinmodelingofthestochasticswitchin DE-627 ger DE-627 rakwb eng 620 DNB Vincent, Adrien F verfasserin aut Analytical Macrospin Modeling of the Stochastic Switching Time of Spin-Transfer Torque Devices 2015 Text txt rdacontent ohne Hilfsmittel zu benutzen n rdamedia Band nc rdacarrier Owing to their nonvolatility, outstanding endurance, high write and read speeds, and CMOS process compatibility, spin-transfer torque magnetoresistive memories (MRAMs) are prime candidates for innovative memory applications. However, the switching delay of their core components-the magnetic tunnel junctions (MTJs)-is a stochastic quantity. To account for this in electronic design, only partial models (working in extreme regimes) are available. In this paper, we propose an analytical model for the stochastic switching delay of a current-driven MTJ, with in-plane magnetization, that agrees with physical simulations, from low- to high-current regimes through intermediate regime. We performed physical macrospin simulations of MTJs for a wide range of current. We developed an analytical model for the mean switching delay that fits those simulations results, and smoothly connects well-accepted models for the extreme low and extreme high currents limits. In addition, a probability distribution in agreement with our simulations results is proposed, leading to a full model of the stochastic switching delay. An example for the application of the model is proposed. Our analytical model can help to evaluate the error rate in MRAM designs, and allow designing innovative electronic circuits that exploit the intrinsic stochastic behavior of MTJs as a beneficial feature. MRAM simulation Stochastic processes spin-transfer torque magnetoresistive memories magnetic tunnel junctions in-plane magnetization MRAM devices probability physical macrospin simulations magnetic memories Switches stochastic switching delay CMOS process compatibility Mathematical model Delays current-driven MTJ intrinsic stochastic behavior mean switching magnetisation Current density partial models modeling Magnetic devices error rate Analytical models magnetic tunnelling Magnetic tunneling probability distribution Computer memory Random access memory Design Models Magnetoresistance Analysis Magnetic tunnel junctions Distribution (Probability theory) Stochastic analysis Complementary metal oxide semiconductors Design and construction Usage Locatelli, Nicolas oth Klein, Jacques-Olivier oth Zhao, Weisheng S oth Galdin-Retailleau, Sylvie oth Querlioz, Damien oth Enthalten in IEEE transactions on electron devices New York, NY : IEEE, 1963 62(2015), 1, Seite 164-170 (DE-627)129602922 (DE-600)241634-7 (DE-576)015096734 0018-9383 nnns volume:62 year:2015 number:1 pages:164-170 http://dx.doi.org/10.1109/TED.2014.2372475 Volltext http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6981938 http://search.proquest.com/docview/1640794838 GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_170 GBV_ILN_2004 GBV_ILN_4313 GBV_ILN_4314 AR 62 2015 1 164-170 |
language |
English |
source |
Enthalten in IEEE transactions on electron devices 62(2015), 1, Seite 164-170 volume:62 year:2015 number:1 pages:164-170 |
sourceStr |
Enthalten in IEEE transactions on electron devices 62(2015), 1, Seite 164-170 volume:62 year:2015 number:1 pages:164-170 |
format_phy_str_mv |
Article |
institution |
findex.gbv.de |
topic_facet |
MRAM simulation Stochastic processes spin-transfer torque magnetoresistive memories magnetic tunnel junctions in-plane magnetization MRAM devices probability physical macrospin simulations magnetic memories Switches stochastic switching delay CMOS process compatibility Mathematical model Delays current-driven MTJ intrinsic stochastic behavior mean switching magnetisation Current density partial models modeling Magnetic devices error rate Analytical models magnetic tunnelling Magnetic tunneling probability distribution Computer memory Random access memory Design Models Magnetoresistance Analysis Magnetic tunnel junctions Distribution (Probability theory) Stochastic analysis Complementary metal oxide semiconductors Design and construction Usage |
dewey-raw |
620 |
isfreeaccess_bool |
false |
container_title |
IEEE transactions on electron devices |
authorswithroles_txt_mv |
Vincent, Adrien F @@aut@@ Locatelli, Nicolas @@oth@@ Klein, Jacques-Olivier @@oth@@ Zhao, Weisheng S @@oth@@ Galdin-Retailleau, Sylvie @@oth@@ Querlioz, Damien @@oth@@ |
publishDateDaySort_date |
2015-01-01T00:00:00Z |
hierarchy_top_id |
129602922 |
dewey-sort |
3620 |
id |
OLC1967766029 |
language_de |
englisch |
fullrecord |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1967766029</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20210716042055.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">160206s2015 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1109/TED.2014.2372475</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20160617</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1967766029</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1967766029</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)c2574-c32dbd5c0078f165ffbc2eb01262c23a945176fb4219fe51c786a432ea81282c0</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0079428720150000062000100164analyticalmacrospinmodelingofthestochasticswitchin</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">620</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Vincent, Adrien F</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Analytical Macrospin Modeling of the Stochastic Switching Time of Spin-Transfer Torque Devices</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Owing to their nonvolatility, outstanding endurance, high write and read speeds, and CMOS process compatibility, spin-transfer torque magnetoresistive memories (MRAMs) are prime candidates for innovative memory applications. However, the switching delay of their core components-the magnetic tunnel junctions (MTJs)-is a stochastic quantity. To account for this in electronic design, only partial models (working in extreme regimes) are available. In this paper, we propose an analytical model for the stochastic switching delay of a current-driven MTJ, with in-plane magnetization, that agrees with physical simulations, from low- to high-current regimes through intermediate regime. We performed physical macrospin simulations of MTJs for a wide range of current. We developed an analytical model for the mean switching delay that fits those simulations results, and smoothly connects well-accepted models for the extreme low and extreme high currents limits. In addition, a probability distribution in agreement with our simulations results is proposed, leading to a full model of the stochastic switching delay. An example for the application of the model is proposed. Our analytical model can help to evaluate the error rate in MRAM designs, and allow designing innovative electronic circuits that exploit the intrinsic stochastic behavior of MTJs as a beneficial feature.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">MRAM</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">simulation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Stochastic processes</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">spin-transfer torque magnetoresistive memories</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">magnetic tunnel junctions</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">in-plane magnetization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">MRAM devices</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">probability</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">physical macrospin simulations</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">magnetic memories</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Switches</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">stochastic switching delay</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">CMOS process compatibility</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematical model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Delays</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">current-driven MTJ</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">intrinsic stochastic behavior</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">mean switching</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">magnetisation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Current density</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">partial models</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">modeling</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Magnetic devices</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">error rate</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Analytical models</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">magnetic tunnelling</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Magnetic tunneling</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">probability distribution</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer memory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Random access memory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Design</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Models</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Magnetoresistance</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Analysis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Magnetic tunnel junctions</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Distribution (Probability theory)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Stochastic analysis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Complementary metal oxide semiconductors</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Design and construction</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Usage</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Locatelli, Nicolas</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Klein, Jacques-Olivier</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhao, Weisheng S</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Galdin-Retailleau, Sylvie</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Querlioz, Damien</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">IEEE transactions on electron devices</subfield><subfield code="d">New York, NY : IEEE, 1963</subfield><subfield code="g">62(2015), 1, Seite 164-170</subfield><subfield code="w">(DE-627)129602922</subfield><subfield code="w">(DE-600)241634-7</subfield><subfield code="w">(DE-576)015096734</subfield><subfield code="x">0018-9383</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:62</subfield><subfield code="g">year:2015</subfield><subfield code="g">number:1</subfield><subfield code="g">pages:164-170</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1109/TED.2014.2372475</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6981938</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://search.proquest.com/docview/1640794838</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4314</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">62</subfield><subfield code="j">2015</subfield><subfield code="e">1</subfield><subfield code="h">164-170</subfield></datafield></record></collection>
|
author |
Vincent, Adrien F |
spellingShingle |
Vincent, Adrien F ddc 620 misc MRAM misc simulation misc Stochastic processes misc spin-transfer torque magnetoresistive memories misc magnetic tunnel junctions misc in-plane magnetization misc MRAM devices misc probability misc physical macrospin simulations misc magnetic memories misc Switches misc stochastic switching delay misc CMOS process compatibility misc Mathematical model misc Delays misc current-driven MTJ misc intrinsic stochastic behavior misc mean switching misc magnetisation misc Current density misc partial models misc modeling misc Magnetic devices misc error rate misc Analytical models misc magnetic tunnelling misc Magnetic tunneling misc probability distribution misc Computer memory misc Random access memory misc Design misc Models misc Magnetoresistance misc Analysis misc Magnetic tunnel junctions misc Distribution (Probability theory) misc Stochastic analysis misc Complementary metal oxide semiconductors misc Design and construction misc Usage Analytical Macrospin Modeling of the Stochastic Switching Time of Spin-Transfer Torque Devices |
authorStr |
Vincent, Adrien F |
ppnlink_with_tag_str_mv |
@@773@@(DE-627)129602922 |
format |
Article |
dewey-ones |
620 - Engineering & allied operations |
delete_txt_mv |
keep |
author_role |
aut |
collection |
OLC |
remote_str |
false |
illustrated |
Not Illustrated |
issn |
0018-9383 |
topic_title |
620 DNB Analytical Macrospin Modeling of the Stochastic Switching Time of Spin-Transfer Torque Devices MRAM simulation Stochastic processes spin-transfer torque magnetoresistive memories magnetic tunnel junctions in-plane magnetization MRAM devices probability physical macrospin simulations magnetic memories Switches stochastic switching delay CMOS process compatibility Mathematical model Delays current-driven MTJ intrinsic stochastic behavior mean switching magnetisation Current density partial models modeling Magnetic devices error rate Analytical models magnetic tunnelling Magnetic tunneling probability distribution Computer memory Random access memory Design Models Magnetoresistance Analysis Magnetic tunnel junctions Distribution (Probability theory) Stochastic analysis Complementary metal oxide semiconductors Design and construction Usage |
topic |
ddc 620 misc MRAM misc simulation misc Stochastic processes misc spin-transfer torque magnetoresistive memories misc magnetic tunnel junctions misc in-plane magnetization misc MRAM devices misc probability misc physical macrospin simulations misc magnetic memories misc Switches misc stochastic switching delay misc CMOS process compatibility misc Mathematical model misc Delays misc current-driven MTJ misc intrinsic stochastic behavior misc mean switching misc magnetisation misc Current density misc partial models misc modeling misc Magnetic devices misc error rate misc Analytical models misc magnetic tunnelling misc Magnetic tunneling misc probability distribution misc Computer memory misc Random access memory misc Design misc Models misc Magnetoresistance misc Analysis misc Magnetic tunnel junctions misc Distribution (Probability theory) misc Stochastic analysis misc Complementary metal oxide semiconductors misc Design and construction misc Usage |
topic_unstemmed |
ddc 620 misc MRAM misc simulation misc Stochastic processes misc spin-transfer torque magnetoresistive memories misc magnetic tunnel junctions misc in-plane magnetization misc MRAM devices misc probability misc physical macrospin simulations misc magnetic memories misc Switches misc stochastic switching delay misc CMOS process compatibility misc Mathematical model misc Delays misc current-driven MTJ misc intrinsic stochastic behavior misc mean switching misc magnetisation misc Current density misc partial models misc modeling misc Magnetic devices misc error rate misc Analytical models misc magnetic tunnelling misc Magnetic tunneling misc probability distribution misc Computer memory misc Random access memory misc Design misc Models misc Magnetoresistance misc Analysis misc Magnetic tunnel junctions misc Distribution (Probability theory) misc Stochastic analysis misc Complementary metal oxide semiconductors misc Design and construction misc Usage |
topic_browse |
ddc 620 misc MRAM misc simulation misc Stochastic processes misc spin-transfer torque magnetoresistive memories misc magnetic tunnel junctions misc in-plane magnetization misc MRAM devices misc probability misc physical macrospin simulations misc magnetic memories misc Switches misc stochastic switching delay misc CMOS process compatibility misc Mathematical model misc Delays misc current-driven MTJ misc intrinsic stochastic behavior misc mean switching misc magnetisation misc Current density misc partial models misc modeling misc Magnetic devices misc error rate misc Analytical models misc magnetic tunnelling misc Magnetic tunneling misc probability distribution misc Computer memory misc Random access memory misc Design misc Models misc Magnetoresistance misc Analysis misc Magnetic tunnel junctions misc Distribution (Probability theory) misc Stochastic analysis misc Complementary metal oxide semiconductors misc Design and construction misc Usage |
format_facet |
Aufsätze Gedruckte Aufsätze |
format_main_str_mv |
Text Zeitschrift/Artikel |
carriertype_str_mv |
nc |
author2_variant |
n l nl j o k jok w s z ws wsz s g r sgr d q dq |
hierarchy_parent_title |
IEEE transactions on electron devices |
hierarchy_parent_id |
129602922 |
dewey-tens |
620 - Engineering |
hierarchy_top_title |
IEEE transactions on electron devices |
isfreeaccess_txt |
false |
familylinks_str_mv |
(DE-627)129602922 (DE-600)241634-7 (DE-576)015096734 |
title |
Analytical Macrospin Modeling of the Stochastic Switching Time of Spin-Transfer Torque Devices |
ctrlnum |
(DE-627)OLC1967766029 (DE-599)GBVOLC1967766029 (PRQ)c2574-c32dbd5c0078f165ffbc2eb01262c23a945176fb4219fe51c786a432ea81282c0 (KEY)0079428720150000062000100164analyticalmacrospinmodelingofthestochasticswitchin |
title_full |
Analytical Macrospin Modeling of the Stochastic Switching Time of Spin-Transfer Torque Devices |
author_sort |
Vincent, Adrien F |
journal |
IEEE transactions on electron devices |
journalStr |
IEEE transactions on electron devices |
lang_code |
eng |
isOA_bool |
false |
dewey-hundreds |
600 - Technology |
recordtype |
marc |
publishDateSort |
2015 |
contenttype_str_mv |
txt |
container_start_page |
164 |
author_browse |
Vincent, Adrien F |
container_volume |
62 |
class |
620 DNB |
format_se |
Aufsätze |
author-letter |
Vincent, Adrien F |
doi_str_mv |
10.1109/TED.2014.2372475 |
dewey-full |
620 |
title_sort |
analytical macrospin modeling of the stochastic switching time of spin-transfer torque devices |
title_auth |
Analytical Macrospin Modeling of the Stochastic Switching Time of Spin-Transfer Torque Devices |
abstract |
Owing to their nonvolatility, outstanding endurance, high write and read speeds, and CMOS process compatibility, spin-transfer torque magnetoresistive memories (MRAMs) are prime candidates for innovative memory applications. However, the switching delay of their core components-the magnetic tunnel junctions (MTJs)-is a stochastic quantity. To account for this in electronic design, only partial models (working in extreme regimes) are available. In this paper, we propose an analytical model for the stochastic switching delay of a current-driven MTJ, with in-plane magnetization, that agrees with physical simulations, from low- to high-current regimes through intermediate regime. We performed physical macrospin simulations of MTJs for a wide range of current. We developed an analytical model for the mean switching delay that fits those simulations results, and smoothly connects well-accepted models for the extreme low and extreme high currents limits. In addition, a probability distribution in agreement with our simulations results is proposed, leading to a full model of the stochastic switching delay. An example for the application of the model is proposed. Our analytical model can help to evaluate the error rate in MRAM designs, and allow designing innovative electronic circuits that exploit the intrinsic stochastic behavior of MTJs as a beneficial feature. |
abstractGer |
Owing to their nonvolatility, outstanding endurance, high write and read speeds, and CMOS process compatibility, spin-transfer torque magnetoresistive memories (MRAMs) are prime candidates for innovative memory applications. However, the switching delay of their core components-the magnetic tunnel junctions (MTJs)-is a stochastic quantity. To account for this in electronic design, only partial models (working in extreme regimes) are available. In this paper, we propose an analytical model for the stochastic switching delay of a current-driven MTJ, with in-plane magnetization, that agrees with physical simulations, from low- to high-current regimes through intermediate regime. We performed physical macrospin simulations of MTJs for a wide range of current. We developed an analytical model for the mean switching delay that fits those simulations results, and smoothly connects well-accepted models for the extreme low and extreme high currents limits. In addition, a probability distribution in agreement with our simulations results is proposed, leading to a full model of the stochastic switching delay. An example for the application of the model is proposed. Our analytical model can help to evaluate the error rate in MRAM designs, and allow designing innovative electronic circuits that exploit the intrinsic stochastic behavior of MTJs as a beneficial feature. |
abstract_unstemmed |
Owing to their nonvolatility, outstanding endurance, high write and read speeds, and CMOS process compatibility, spin-transfer torque magnetoresistive memories (MRAMs) are prime candidates for innovative memory applications. However, the switching delay of their core components-the magnetic tunnel junctions (MTJs)-is a stochastic quantity. To account for this in electronic design, only partial models (working in extreme regimes) are available. In this paper, we propose an analytical model for the stochastic switching delay of a current-driven MTJ, with in-plane magnetization, that agrees with physical simulations, from low- to high-current regimes through intermediate regime. We performed physical macrospin simulations of MTJs for a wide range of current. We developed an analytical model for the mean switching delay that fits those simulations results, and smoothly connects well-accepted models for the extreme low and extreme high currents limits. In addition, a probability distribution in agreement with our simulations results is proposed, leading to a full model of the stochastic switching delay. An example for the application of the model is proposed. Our analytical model can help to evaluate the error rate in MRAM designs, and allow designing innovative electronic circuits that exploit the intrinsic stochastic behavior of MTJs as a beneficial feature. |
collection_details |
GBV_USEFLAG_A SYSFLAG_A GBV_OLC SSG-OLC-TEC SSG-OLC-MAT GBV_ILN_70 GBV_ILN_170 GBV_ILN_2004 GBV_ILN_4313 GBV_ILN_4314 |
container_issue |
1 |
title_short |
Analytical Macrospin Modeling of the Stochastic Switching Time of Spin-Transfer Torque Devices |
url |
http://dx.doi.org/10.1109/TED.2014.2372475 http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6981938 http://search.proquest.com/docview/1640794838 |
remote_bool |
false |
author2 |
Locatelli, Nicolas Klein, Jacques-Olivier Zhao, Weisheng S Galdin-Retailleau, Sylvie Querlioz, Damien |
author2Str |
Locatelli, Nicolas Klein, Jacques-Olivier Zhao, Weisheng S Galdin-Retailleau, Sylvie Querlioz, Damien |
ppnlink |
129602922 |
mediatype_str_mv |
n |
isOA_txt |
false |
hochschulschrift_bool |
false |
author2_role |
oth oth oth oth oth |
doi_str |
10.1109/TED.2014.2372475 |
up_date |
2024-07-04T01:52:35.187Z |
_version_ |
1803611490419212288 |
fullrecord_marcxml |
<?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>01000caa a2200265 4500</leader><controlfield tag="001">OLC1967766029</controlfield><controlfield tag="003">DE-627</controlfield><controlfield tag="005">20210716042055.0</controlfield><controlfield tag="007">tu</controlfield><controlfield tag="008">160206s2015 xx ||||| 00| ||eng c</controlfield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.1109/TED.2014.2372475</subfield><subfield code="2">doi</subfield></datafield><datafield tag="028" ind1="5" ind2="2"><subfield code="a">PQ20160617</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-627)OLC1967766029</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(DE-599)GBVOLC1967766029</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(PRQ)c2574-c32dbd5c0078f165ffbc2eb01262c23a945176fb4219fe51c786a432ea81282c0</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(KEY)0079428720150000062000100164analyticalmacrospinmodelingofthestochasticswitchin</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">DE-627</subfield><subfield code="b">ger</subfield><subfield code="c">DE-627</subfield><subfield code="e">rakwb</subfield></datafield><datafield tag="041" ind1=" " ind2=" "><subfield code="a">eng</subfield></datafield><datafield tag="082" ind1="0" ind2="4"><subfield code="a">620</subfield><subfield code="q">DNB</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Vincent, Adrien F</subfield><subfield code="e">verfasserin</subfield><subfield code="4">aut</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Analytical Macrospin Modeling of the Stochastic Switching Time of Spin-Transfer Torque Devices</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="c">2015</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">Text</subfield><subfield code="b">txt</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">ohne Hilfsmittel zu benutzen</subfield><subfield code="b">n</subfield><subfield code="2">rdamedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">Band</subfield><subfield code="b">nc</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="520" ind1=" " ind2=" "><subfield code="a">Owing to their nonvolatility, outstanding endurance, high write and read speeds, and CMOS process compatibility, spin-transfer torque magnetoresistive memories (MRAMs) are prime candidates for innovative memory applications. However, the switching delay of their core components-the magnetic tunnel junctions (MTJs)-is a stochastic quantity. To account for this in electronic design, only partial models (working in extreme regimes) are available. In this paper, we propose an analytical model for the stochastic switching delay of a current-driven MTJ, with in-plane magnetization, that agrees with physical simulations, from low- to high-current regimes through intermediate regime. We performed physical macrospin simulations of MTJs for a wide range of current. We developed an analytical model for the mean switching delay that fits those simulations results, and smoothly connects well-accepted models for the extreme low and extreme high currents limits. In addition, a probability distribution in agreement with our simulations results is proposed, leading to a full model of the stochastic switching delay. An example for the application of the model is proposed. Our analytical model can help to evaluate the error rate in MRAM designs, and allow designing innovative electronic circuits that exploit the intrinsic stochastic behavior of MTJs as a beneficial feature.</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">MRAM</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">simulation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Stochastic processes</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">spin-transfer torque magnetoresistive memories</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">magnetic tunnel junctions</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">in-plane magnetization</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">MRAM devices</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">probability</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">physical macrospin simulations</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">magnetic memories</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Switches</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">stochastic switching delay</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">CMOS process compatibility</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Mathematical model</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Delays</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">current-driven MTJ</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">intrinsic stochastic behavior</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">mean switching</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">magnetisation</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Current density</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">partial models</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">modeling</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Magnetic devices</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">error rate</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Analytical models</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">magnetic tunnelling</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Magnetic tunneling</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">probability distribution</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Computer memory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Random access memory</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Design</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Models</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Magnetoresistance</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Analysis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Magnetic tunnel junctions</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Distribution (Probability theory)</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Stochastic analysis</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Complementary metal oxide semiconductors</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Design and construction</subfield></datafield><datafield tag="650" ind1=" " ind2="4"><subfield code="a">Usage</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Locatelli, Nicolas</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Klein, Jacques-Olivier</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Zhao, Weisheng S</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Galdin-Retailleau, Sylvie</subfield><subfield code="4">oth</subfield></datafield><datafield tag="700" ind1="1" ind2=" "><subfield code="a">Querlioz, Damien</subfield><subfield code="4">oth</subfield></datafield><datafield tag="773" ind1="0" ind2="8"><subfield code="i">Enthalten in</subfield><subfield code="t">IEEE transactions on electron devices</subfield><subfield code="d">New York, NY : IEEE, 1963</subfield><subfield code="g">62(2015), 1, Seite 164-170</subfield><subfield code="w">(DE-627)129602922</subfield><subfield code="w">(DE-600)241634-7</subfield><subfield code="w">(DE-576)015096734</subfield><subfield code="x">0018-9383</subfield><subfield code="7">nnns</subfield></datafield><datafield tag="773" ind1="1" ind2="8"><subfield code="g">volume:62</subfield><subfield code="g">year:2015</subfield><subfield code="g">number:1</subfield><subfield code="g">pages:164-170</subfield></datafield><datafield tag="856" ind1="4" ind2="1"><subfield code="u">http://dx.doi.org/10.1109/TED.2014.2372475</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6981938</subfield></datafield><datafield tag="856" ind1="4" ind2="2"><subfield code="u">http://search.proquest.com/docview/1640794838</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_USEFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SYSFLAG_A</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_OLC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-TEC</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">SSG-OLC-MAT</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_70</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_170</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_2004</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4313</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">GBV_ILN_4314</subfield></datafield><datafield tag="951" ind1=" " ind2=" "><subfield code="a">AR</subfield></datafield><datafield tag="952" ind1=" " ind2=" "><subfield code="d">62</subfield><subfield code="j">2015</subfield><subfield code="e">1</subfield><subfield code="h">164-170</subfield></datafield></record></collection>
|
score |
7.400962 |