Artificial Neuron and Synapse Realized in an Antiferromagnet/Ferromagnet Heterostructure Using Dynamics of Spin–Orbit Torque Switching
Efficient information processing in the human brain is achieved by dynamics of neurons and synapses, motivating effective implementation of artificial spiking neural networks. Here, the dynamics of spin–orbit torque switching in antiferromagnet/ferromagnet heterostructures is studied to show the cap...
Saved in:
Published in | Advanced materials (Weinheim) Vol. 31; no. 23; pp. e1900636 - n/a |
---|---|
Main Authors | , , , , , |
Format | Journal Article |
Language | English |
Published |
Germany
Wiley Subscription Services, Inc
01.06.2019
|
Subjects | |
Online Access | Get full text |
Cover
Loading…
Abstract | Efficient information processing in the human brain is achieved by dynamics of neurons and synapses, motivating effective implementation of artificial spiking neural networks. Here, the dynamics of spin–orbit torque switching in antiferromagnet/ferromagnet heterostructures is studied to show the capability of the material system to form artificial neurons and synapses for asynchronous spiking neural networks. The magnetization switching, driven by a single current pulse or trains of pulses, is examined as a function of the pulse width (1 s to 1 ns), amplitude, number, and pulse‐to‐pulse interval. Based on this dynamics and the unique ability of the system to exhibit binary or analog behavior depending on the device size, key functionalities of a synapse (spike‐timing‐dependent plasticity) and a neuron (leaky integrate‐and‐fire) are reproduced in the same material and on the basis of the same working principle. These results open a way toward spintronics‐based neuromorphic hardware that executes cognitive tasks with the efficiency of the human brain.
Control of spintronics‐based binary and analog devices by pulses down to 1 ns and its applications are studied. It is found that the response of the binary device reproduces the behavior of a biological neuron while the analog device responds like a synapse. This is the first implementation of both elements based on the same material and working principle. |
---|---|
AbstractList | Abstract Efficient information processing in the human brain is achieved by dynamics of neurons and synapses, motivating effective implementation of artificial spiking neural networks. Here, the dynamics of spin–orbit torque switching in antiferromagnet/ferromagnet heterostructures is studied to show the capability of the material system to form artificial neurons and synapses for asynchronous spiking neural networks. The magnetization switching, driven by a single current pulse or trains of pulses, is examined as a function of the pulse width (1 s to 1 ns), amplitude, number, and pulse‐to‐pulse interval. Based on this dynamics and the unique ability of the system to exhibit binary or analog behavior depending on the device size, key functionalities of a synapse (spike‐timing‐dependent plasticity) and a neuron (leaky integrate‐and‐fire) are reproduced in the same material and on the basis of the same working principle. These results open a way toward spintronics‐based neuromorphic hardware that executes cognitive tasks with the efficiency of the human brain. Efficient information processing in the human brain is achieved by dynamics of neurons and synapses, motivating effective implementation of artificial spiking neural networks. Here, the dynamics of spin–orbit torque switching in antiferromagnet/ferromagnet heterostructures is studied to show the capability of the material system to form artificial neurons and synapses for asynchronous spiking neural networks. The magnetization switching, driven by a single current pulse or trains of pulses, is examined as a function of the pulse width (1 s to 1 ns), amplitude, number, and pulse‐to‐pulse interval. Based on this dynamics and the unique ability of the system to exhibit binary or analog behavior depending on the device size, key functionalities of a synapse (spike‐timing‐dependent plasticity) and a neuron (leaky integrate‐and‐fire) are reproduced in the same material and on the basis of the same working principle. These results open a way toward spintronics‐based neuromorphic hardware that executes cognitive tasks with the efficiency of the human brain. Control of spintronics‐based binary and analog devices by pulses down to 1 ns and its applications are studied. It is found that the response of the binary device reproduces the behavior of a biological neuron while the analog device responds like a synapse. This is the first implementation of both elements based on the same material and working principle. Efficient information processing in the human brain is achieved by dynamics of neurons and synapses, motivating effective implementation of artificial spiking neural networks. Here, the dynamics of spin-orbit torque switching in antiferromagnet/ferromagnet heterostructures is studied to show the capability of the material system to form artificial neurons and synapses for asynchronous spiking neural networks. The magnetization switching, driven by a single current pulse or trains of pulses, is examined as a function of the pulse width (1 s to 1 ns), amplitude, number, and pulse-to-pulse interval. Based on this dynamics and the unique ability of the system to exhibit binary or analog behavior depending on the device size, key functionalities of a synapse (spike-timing-dependent plasticity) and a neuron (leaky integrate-and-fire) are reproduced in the same material and on the basis of the same working principle. These results open a way toward spintronics-based neuromorphic hardware that executes cognitive tasks with the efficiency of the human brain. |
Author | DuttaGupta, Samik Fukami, Shunsuke Horio, Yoshihiko Zhang, Chaoliang Kurenkov, Aleksandr Ohno, Hideo |
Author_xml | – sequence: 1 givenname: Aleksandr surname: Kurenkov fullname: Kurenkov, Aleksandr organization: Tohoku University – sequence: 2 givenname: Samik surname: DuttaGupta fullname: DuttaGupta, Samik organization: Tohoku University – sequence: 3 givenname: Chaoliang surname: Zhang fullname: Zhang, Chaoliang organization: Tohoku University – sequence: 4 givenname: Shunsuke orcidid: 0000-0001-5750-2990 surname: Fukami fullname: Fukami, Shunsuke email: s-fukami@riec.tohoku.ac.jp organization: Tohoku University – sequence: 5 givenname: Yoshihiko surname: Horio fullname: Horio, Yoshihiko organization: Tohoku University – sequence: 6 givenname: Hideo surname: Ohno fullname: Ohno, Hideo organization: Tohoku University |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/30989740$$D View this record in MEDLINE/PubMed |
BookMark | eNqF0T1v1DAYB3ALFdFrYWVEllhYcn38Eiceo74iFSpxxxw5zpPiKnEOO1F1TIzs_YZ8Eny60kosTI9l_fy3rf8ROfCjR0LeMlgyAH5i2sEsOTANoIR6QRYs5yyToPMDsgAt8kwrWR6SoxjvAEArUK_IoQBd6kLCgvyqwuQ6Z53p6Wecw-ip8S1dbb3ZRKRf0PTuB7bU7fZp5RPGEMbB3HqcTi6e1_QKJwxjnMJspzkg_Rqdv6VnKWhwNtKxo6uN879_PtyExk10PYbvM9LVvZvstyRfk5ed6SO-eZzHZH1xvj69yq5vLj-eVteZlUKrTIhWylY3UILlHbNSqbbUedmAYqzkplAIqhFQGqOZNFwjFEqkKRgIq8Ux-bCP3YQx3R-nenDRYt8bj-Mca84ZcMW4zhN9_w-9G-fg0-OSEqKQusiLpJZ7ZdPnY8Cu3gQ3mLCtGdS7iupdRfVTRenAu8fYuRmwfeJ_O0lA78G963H7n7i6OvtUPYf_AfGAoIU |
CitedBy_id | crossref_primary_10_1007_s11433_019_1499_3 crossref_primary_10_1103_PhysRevApplied_19_034039 crossref_primary_10_1063_5_0011448 crossref_primary_10_1002_adma_201907148 crossref_primary_10_1002_aelm_201900782 crossref_primary_10_1063_5_0039069 crossref_primary_10_1063_5_0009482 crossref_primary_10_3389_fnano_2021_732916 crossref_primary_10_1088_0256_307X_37_7_078501 crossref_primary_10_1016_j_procs_2020_02_122 crossref_primary_10_1063_1_5129829 crossref_primary_10_1039_D0NA00009D crossref_primary_10_1063_5_0035667 crossref_primary_10_1002_smll_202006662 crossref_primary_10_1587_essfr_14_1_6 crossref_primary_10_1002_adfm_201909092 crossref_primary_10_7498_aps_72_20230285 crossref_primary_10_1002_aelm_202200939 crossref_primary_10_1063_5_0193436 crossref_primary_10_1002_aelm_201901107 crossref_primary_10_1021_acs_nanolett_4c01712 crossref_primary_10_1063_5_0155559 crossref_primary_10_1103_PhysRevApplied_13_024052 crossref_primary_10_1002_adfm_202107870 crossref_primary_10_1021_acs_nanolett_1c04786 crossref_primary_10_1039_D1CS00886B crossref_primary_10_3390_electronics11040516 crossref_primary_10_1109_TMAG_2020_3032099 crossref_primary_10_3390_electronics11030365 crossref_primary_10_1002_adma_202301063 crossref_primary_10_1063_5_0142374 crossref_primary_10_1063_5_0079532 crossref_primary_10_1002_pi_5980 crossref_primary_10_1038_s41467_020_19511_4 crossref_primary_10_7498_aps_70_20210611 crossref_primary_10_1063_5_0094205 crossref_primary_10_1557_s43577_023_00613_5 crossref_primary_10_1109_TNANO_2023_3313313 crossref_primary_10_1002_aelm_202101127 crossref_primary_10_1021_acsaelm_9b00560 crossref_primary_10_1103_PhysRevB_109_L060405 crossref_primary_10_1109_TMAG_2021_3078583 crossref_primary_10_1063_5_0053430 crossref_primary_10_1021_acsaelm_3c00429 crossref_primary_10_3389_fnins_2020_00309 crossref_primary_10_1021_acsami_1c18017 crossref_primary_10_1038_s41598_024_60929_3 crossref_primary_10_35848_1347_4065_acbc2a crossref_primary_10_1021_acsaelm_4c00521 crossref_primary_10_1002_adma_202311831 crossref_primary_10_3389_fnins_2021_717947 crossref_primary_10_35848_1347_4065_ab6867 crossref_primary_10_1002_adma_202104960 crossref_primary_10_1021_acsaelm_2c01488 crossref_primary_10_15541_jim20230405 crossref_primary_10_1063_5_0014771 crossref_primary_10_1103_PhysRevApplied_19_064010 crossref_primary_10_1038_s41565_023_01452_w crossref_primary_10_1039_D1NR00346A crossref_primary_10_1038_s41467_023_36728_1 crossref_primary_10_1103_PhysRevApplied_14_044036 crossref_primary_10_1021_acs_nanolett_2c02409 crossref_primary_10_1103_PhysRevMaterials_8_064407 crossref_primary_10_1007_s11433_022_2081_5 crossref_primary_10_1063_1_5143382 crossref_primary_10_1016_j_pmatsci_2020_100761 crossref_primary_10_1021_acs_nanolett_9b05271 crossref_primary_10_1109_TCSII_2023_3324584 crossref_primary_10_1016_j_isci_2020_101614 crossref_primary_10_1109_JEDS_2020_3025336 crossref_primary_10_1103_PhysRevApplied_13_034072 crossref_primary_10_1103_PhysRevLett_125_207202 crossref_primary_10_1002_adfm_202008971 crossref_primary_10_1038_s41928_020_00506_4 crossref_primary_10_1038_s41928_022_00870_3 crossref_primary_10_1002_aisy_202100054 crossref_primary_10_1038_s41598_024_60492_x crossref_primary_10_1002_adfm_202111996 crossref_primary_10_1002_aelm_202001133 crossref_primary_10_1063_5_0128530 crossref_primary_10_1002_adfm_202404679 crossref_primary_10_1063_5_0054025 crossref_primary_10_3389_fnins_2021_786694 crossref_primary_10_1080_14686996_2023_2188878 crossref_primary_10_1109_TNANO_2023_3315071 crossref_primary_10_3389_fnins_2021_661667 crossref_primary_10_1002_adma_202205047 crossref_primary_10_1038_s41928_020_0373_4 crossref_primary_10_3390_cryst13060940 crossref_primary_10_1007_s11433_022_2012_2 crossref_primary_10_1063_5_0101981 crossref_primary_10_1002_adfm_202305238 crossref_primary_10_1021_acsmaterialslett_3c00088 crossref_primary_10_1021_acsaelm_3c01179 crossref_primary_10_1016_j_jmmm_2022_169974 crossref_primary_10_1109_LMAG_2021_3136154 crossref_primary_10_1587_nolta_12_309 crossref_primary_10_1002_adma_202403142 crossref_primary_10_1002_adma_201903800 crossref_primary_10_3390_magnetochemistry7100139 crossref_primary_10_1063_5_0149290 crossref_primary_10_1080_21663831_2022_2147803 crossref_primary_10_1002_aisy_202200123 crossref_primary_10_1002_advs_202203006 crossref_primary_10_1038_s41586_020_2211_2 crossref_primary_10_1109_TMAG_2023_3283034 crossref_primary_10_1002_aisy_202000182 crossref_primary_10_1142_S201032472340026X crossref_primary_10_1002_adfm_202111653 crossref_primary_10_1063_5_0145497 crossref_primary_10_1039_D1MA00862E crossref_primary_10_1063_5_0013917 crossref_primary_10_1016_j_jmmm_2022_169960 crossref_primary_10_1063_5_0177232 crossref_primary_10_1063_5_0131399 crossref_primary_10_1088_1361_6463_abea3b crossref_primary_10_1109_TED_2023_3327031 crossref_primary_10_1002_aelm_202100465 crossref_primary_10_1063_5_0092115 crossref_primary_10_1063_1_5120565 crossref_primary_10_1002_aisy_202000111 crossref_primary_10_1063_5_0049928 crossref_primary_10_1002_sstr_202200064 crossref_primary_10_1088_2634_4386_acdb96 crossref_primary_10_1007_s12274_024_6447_2 crossref_primary_10_1002_adma_202103672 crossref_primary_10_7498_aps_71_20220252 |
Cites_doi | 10.1088/1741-2552/aa7075 10.1038/nnano.2016.29 10.1038/ncomms14736 10.1038/nmat4566 10.1073/pnas.0913991107 10.1103/PhysRevApplied.9.064040 10.1063/1.4977838 10.1038/srep01619 10.1038/s41928-018-0131-z 10.55782/ane-2011-1862 10.1038/s41928-017-0006-8 10.3389/fncom.2015.00099 10.3389/fnins.2016.00474 10.1038/s41467-017-02780-x 10.1126/science.1218197 10.1109/TMAG.2017.2703817 10.3389/fnins.2011.00026 10.1126/science.1225266 10.1109/TNNLS.2015.2388544 10.1103/PhysRevApplied.9.064018 10.1038/nn.4241 10.1038/78829 10.1016/S0896-6273(01)00451-2 10.1063/1.2926374 10.1126/science.1254642 10.1038/ncomms15434 10.1038/nn.3948 10.1103/PhysRevApplied.9.014034 10.1016/j.neunet.2014.01.006 10.1002/adfm.201604740 10.1126/science.aab1031 10.1002/adma.201802353 10.1021/nl201040y 10.1162/jocn.1990.2.1.58 10.1002/adma.201103723 10.1038/srep10150 10.1038/nature23011 10.1038/236 10.1109/JPROC.2014.2313954 10.7554/eLife.23612 10.1038/nature06932 10.1038/s41598-017-07418-y 10.1371/journal.pcbi.1003408 10.1038/nature10309 10.1073/pnas.0712231105 10.1523/JNEUROSCI.18-24-10464.1998 10.1002/adfm.201101935 |
ContentType | Journal Article |
Copyright | 2019 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. |
Copyright_xml | – notice: 2019 WILEY‐VCH Verlag GmbH & Co. KGaA, Weinheim – notice: 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. |
DBID | NPM AAYXX CITATION 7SR 8BQ 8FD JG9 7X8 |
DOI | 10.1002/adma.201900636 |
DatabaseName | PubMed CrossRef Engineered Materials Abstracts METADEX Technology Research Database Materials Research Database MEDLINE - Academic |
DatabaseTitle | PubMed CrossRef Materials Research Database Engineered Materials Abstracts Technology Research Database METADEX MEDLINE - Academic |
DatabaseTitleList | CrossRef PubMed Materials Research Database |
Database_xml | – sequence: 1 dbid: NPM name: PubMed url: https://proxy.k.utb.cz/login?url=http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=PubMed sourceTypes: Index Database |
DeliveryMethod | fulltext_linktorsrc |
Discipline | Engineering |
EISSN | 1521-4095 |
EndPage | n/a |
ExternalDocumentID | 10_1002_adma_201900636 30989740 ADMA201900636 |
Genre | article Journal Article |
GrantInformation_xml | – fundername: JSPS KAKENHI funderid: 17H06093; 18KK0143 – fundername: JSPS KAKENHI grantid: 17H06093 – fundername: JSPS KAKENHI grantid: 18KK0143 |
GroupedDBID | --- .3N .GA 05W 0R~ 10A 1L6 1OB 1OC 1ZS 23M 33P 3SF 3WU 4.4 4ZD 50Y 50Z 51W 51X 52M 52N 52O 52P 52S 52T 52U 52W 52X 53G 5GY 5VS 66C 6P2 702 7PT 8-0 8-1 8-3 8-4 8-5 8UM 930 A03 AAESR AAEVG AAHHS AANLZ AAONW AASGY AAXRX AAZKR ABCQN ABCUV ABIJN ABJNI ABLJU ABPVW ACAHQ ACCFJ ACCZN ACGFS ACIWK ACPOU ACXBN ACXQS ADBBV ADEOM ADIZJ ADKYN ADMGS ADOZA ADXAS ADZMN ADZOD AEEZP AEIGN AEIMD AENEX AEQDE AEUQT AEUYR AFBPY AFFPM AFGKR AFPWT AFZJQ AHBTC AITYG AIURR AIWBW AJBDE AJXKR ALAGY ALMA_UNASSIGNED_HOLDINGS ALUQN AMBMR AMYDB ATUGU AUFTA AZBYB AZVAB BAFTC BDRZF BFHJK BHBCM BMNLL BMXJE BNHUX BROTX BRXPI BY8 CS3 D-E D-F DCZOG DPXWK DR1 DR2 DRFUL DRSTM EBS EJD F00 F01 F04 F5P G-S G.N GNP GODZA H.T H.X HBH HGLYW HHY HHZ HZ~ IX1 J0M JPC KQQ LATKE LAW LC2 LC3 LEEKS LH4 LITHE LOXES LP6 LP7 LUTES LYRES MEWTI MK4 MRFUL MRSTM MSFUL MSSTM MXFUL MXSTM N04 N05 N9A NF~ NNB O66 O9- OIG P2P P2W P2X P4D Q.N Q11 QB0 QRW R.K RNS ROL RWI RWM RX1 RYL SUPJJ TN5 UB1 UPT V2E W8V W99 WBKPD WFSAM WIB WIH WIK WJL WOHZO WQJ WRC WXSBR WYISQ XG1 XPP XV2 YR2 ZZTAW ~02 ~IA ~WT .Y3 31~ 6TJ 8WZ A6W AAYOK ABEML ABTAH ACBWZ ACSCC AFFNX ASPBG AVWKF AZFZN FEDTE FOJGT HF~ HVGLF LW6 M6K NDZJH NPM PALCI RIWAO RJQFR SAMSI WTY ZY4 AAYXX CITATION 7SR 8BQ 8FD JG9 7X8 |
ID | FETCH-LOGICAL-c4396-33d44d9b080c2f1c466d8958b061182a76e06b308aa914a29e0763a293103c93 |
IEDL.DBID | DR2 |
ISSN | 0935-9648 |
IngestDate | Fri Aug 16 09:03:51 EDT 2024 Thu Oct 10 16:41:13 EDT 2024 Thu Sep 26 21:14:02 EDT 2024 Wed Oct 16 00:51:51 EDT 2024 Sat Aug 24 01:19:39 EDT 2024 |
IsPeerReviewed | true |
IsScholarly | true |
Issue | 23 |
Keywords | spintronics antiferromagnets synapses neurons neural networks |
Language | English |
License | 2019 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim. |
LinkModel | DirectLink |
MergedId | FETCHMERGED-LOGICAL-c4396-33d44d9b080c2f1c466d8958b061182a76e06b308aa914a29e0763a293103c93 |
Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 |
ORCID | 0000-0001-5750-2990 |
PMID | 30989740 |
PQID | 2233749757 |
PQPubID | 2045203 |
PageCount | 7 |
ParticipantIDs | proquest_miscellaneous_2210261295 proquest_journals_2233749757 crossref_primary_10_1002_adma_201900636 pubmed_primary_30989740 wiley_primary_10_1002_adma_201900636_ADMA201900636 |
PublicationCentury | 2000 |
PublicationDate | 2019-06-01 |
PublicationDateYYYYMMDD | 2019-06-01 |
PublicationDate_xml | – month: 06 year: 2019 text: 2019-06-01 day: 01 |
PublicationDecade | 2010 |
PublicationPlace | Germany |
PublicationPlace_xml | – name: Germany – name: Weinheim |
PublicationTitle | Advanced materials (Weinheim) |
PublicationTitleAlternate | Adv Mater |
PublicationYear | 2019 |
Publisher | Wiley Subscription Services, Inc |
Publisher_xml | – name: Wiley Subscription Services, Inc |
References | 2017; 6 2017; 7 2017; 8 2011; 476 2013; 3 2015; 5 2015; 19 2016; 19 2015; 18 2010; 107 2000; 3 2017; 27 2016; 10 2008; 105 2017; 110 2015; 9 2012; 12 2008; 92 2016; 15 2011; 5 2016; 11 1990; 2 2015; 26 1998; 18 2018; 9 2017; 53 2017; 14 2018; 1 2011; 71 2018 2018; 30 1998; 1 2014; 52 2008; 453 2012; 24 2012; 336 2012; 22 2012; 338 2014; 345 2016; 351 2014; 10 2014; 102 2017; 547 2001; 32 e_1_2_5_27_1 e_1_2_5_25_1 e_1_2_5_48_1 e_1_2_5_23_1 e_1_2_5_46_1 e_1_2_5_21_1 Ballestero J. (e_1_2_5_39_1) 2015; 19 e_1_2_5_44_1 e_1_2_5_29_1 e_1_2_5_42_1 e_1_2_5_40_1 e_1_2_5_15_1 e_1_2_5_38_1 e_1_2_5_17_1 e_1_2_5_36_1 e_1_2_5_9_1 e_1_2_5_11_1 e_1_2_5_34_1 e_1_2_5_7_1 e_1_2_5_13_1 e_1_2_5_32_1 e_1_2_5_5_1 Ponulak F. (e_1_2_5_4_1) 2011; 71 e_1_2_5_3_1 e_1_2_5_1_1 e_1_2_5_19_1 e_1_2_5_30_1 e_1_2_5_28_1 e_1_2_5_49_1 Wang Z. (e_1_2_5_24_1) 2018 e_1_2_5_26_1 e_1_2_5_47_1 e_1_2_5_45_1 e_1_2_5_22_1 e_1_2_5_43_1 e_1_2_5_20_1 e_1_2_5_41_1 e_1_2_5_14_1 e_1_2_5_16_1 e_1_2_5_37_1 e_1_2_5_8_1 e_1_2_5_10_1 e_1_2_5_35_1 e_1_2_5_6_1 e_1_2_5_12_1 e_1_2_5_33_1 e_1_2_5_2_1 e_1_2_5_18_1 e_1_2_5_31_1 e_1_2_5_50_1 |
References_xml | – volume: 338 start-page: 1202 year: 2012 publication-title: Science – volume: 345 start-page: 668 year: 2014 publication-title: Science – volume: 9 start-page: 014034 year: 2018 publication-title: Phys. Rev. Appl. – volume: 32 start-page: 339 year: 2001 publication-title: Neuron – volume: 22 start-page: 609 year: 2012 publication-title: Adv. Funct. Mater. – volume: 19 start-page: 350 year: 2016 publication-title: Nat. Neurosci. – volume: 453 start-page: 80 year: 2008 publication-title: Nature – volume: 18 start-page: 10464 year: 1998 publication-title: J. Neurosci. – volume: 9 start-page: 064018 year: 2018 publication-title: Phys. Rev. Appl. – volume: 14 start-page: 046021 year: 2017 publication-title: J. Neural Eng. – volume: 110 start-page: 092410 year: 2017 publication-title: Appl. Phys. Lett. – volume: 9 start-page: 064040 year: 2018 publication-title: Phys. Rev. Appl. – volume: 3 start-page: 1619 year: 2013 publication-title: Sci. Rep. – volume: 26 start-page: 2635 year: 2015 publication-title: IEEE Trans. Neural Networks Learn. Syst. – volume: 107 start-page: 1648 year: 2010 publication-title: Proc. Natl. Acad. Sci. USA – year: 2018 – volume: 105 start-page: 3593 year: 2008 publication-title: Proc. Natl. Acad. Sci. USA – volume: 9 start-page: 348 year: 2018 publication-title: Nat. Commun. – volume: 1 start-page: 22 year: 2018 publication-title: Nat. Electron. – volume: 10 start-page: e1003408 year: 2014 publication-title: PLoS Comput. Biol. – volume: 1 start-page: 36 year: 1998 publication-title: Nat. Neurosci. – volume: 8 start-page: 15434 year: 2017 publication-title: Nat. Commun. – volume: 5 start-page: 26 year: 2011 publication-title: Front. Neurosci. – volume: 8 start-page: 14736 year: 2017 publication-title: Nat. Commun. – volume: 27 start-page: 1604740 year: 2017 publication-title: Adv. Funct. Mater. – volume: 336 start-page: 555 year: 2012 publication-title: Science – volume: 30 start-page: 1802353 year: 2018 publication-title: Adv. Mater. – volume: 10 start-page: 474 year: 2016 publication-title: Front. Neurosci. – volume: 9 start-page: 99 year: 2015 publication-title: Front. Computat. Neurosci. – volume: 5 start-page: 10150 year: 2015 publication-title: Sci. Rep. – volume: 11 start-page: 621 year: 2016 publication-title: Nat. Nanotechnol. – volume: 102 start-page: 1367 year: 2014 publication-title: Proc. IEEE – volume: 6 start-page: 23612 year: 2017 publication-title: eLife – volume: 476 start-page: 189 year: 2011 publication-title: Nature – volume: 18 start-page: 444 year: 2015 publication-title: Nat. Neurosci. – volume: 12 start-page: 2179 year: 2012 publication-title: Nano Lett. – volume: 2 start-page: 58 year: 1990 publication-title: J. Cognit. Neurosci. – start-page: 13.3.1 year: 2018 – volume: 1 start-page: 508 year: 2018 publication-title: Nat. Electron. – volume: 24 start-page: 762 year: 2012 publication-title: Adv. Mater. – volume: 547 start-page: 428 year: 2017 publication-title: Nature – volume: 92 start-page: 192509 year: 2008 publication-title: Appl. Phys. Lett. – volume: 15 start-page: 535 year: 2016 publication-title: Nat. Mater. – volume: 71 start-page: 409 year: 2011 publication-title: Acta Neurobiol. Exp. – volume: 3 start-page: 919 year: 2000 publication-title: Nat. Neurosci. – volume: 351 start-page: 587 year: 2016 publication-title: Science – volume: 53 start-page: 1 year: 2017 publication-title: IEEE Trans. Magn. – volume: 19 start-page: 1 year: 2015 publication-title: Trends Hear. – volume: 52 start-page: 62 year: 2014 publication-title: Neural Networks – volume: 7 start-page: 8257 year: 2017 publication-title: Sci. Rep. – ident: e_1_2_5_41_1 doi: 10.1088/1741-2552/aa7075 – ident: e_1_2_5_44_1 doi: 10.1038/nnano.2016.29 – ident: e_1_2_5_16_1 doi: 10.1038/ncomms14736 – start-page: 13.3.1 volume-title: Proc. Int. Electron Devices Meeting (IEDM) year: 2018 ident: e_1_2_5_24_1 contributor: fullname: Wang Z. – volume: 19 start-page: 1 year: 2015 ident: e_1_2_5_39_1 publication-title: Trends Hear. contributor: fullname: Ballestero J. – ident: e_1_2_5_31_1 doi: 10.1038/nmat4566 – ident: e_1_2_5_7_1 doi: 10.1073/pnas.0913991107 – ident: e_1_2_5_49_1 doi: 10.1103/PhysRevApplied.9.064040 – ident: e_1_2_5_32_1 doi: 10.1063/1.4977838 – ident: e_1_2_5_20_1 doi: 10.1038/srep01619 – ident: e_1_2_5_45_1 doi: 10.1038/s41928-018-0131-z – volume: 71 start-page: 409 year: 2011 ident: e_1_2_5_4_1 publication-title: Acta Neurobiol. Exp. doi: 10.55782/ane-2011-1862 contributor: fullname: Ponulak F. – ident: e_1_2_5_1_1 doi: 10.1038/s41928-017-0006-8 – ident: e_1_2_5_5_1 doi: 10.3389/fncom.2015.00099 – ident: e_1_2_5_8_1 doi: 10.3389/fnins.2016.00474 – ident: e_1_2_5_48_1 doi: 10.1038/s41467-017-02780-x – ident: e_1_2_5_43_1 doi: 10.1126/science.1218197 – ident: e_1_2_5_50_1 doi: 10.1109/TMAG.2017.2703817 – ident: e_1_2_5_36_1 doi: 10.3389/fnins.2011.00026 – ident: e_1_2_5_10_1 doi: 10.1126/science.1225266 – ident: e_1_2_5_6_1 doi: 10.1109/TNNLS.2015.2388544 – ident: e_1_2_5_28_1 doi: 10.1103/PhysRevApplied.9.064018 – ident: e_1_2_5_3_1 doi: 10.1038/nn.4241 – ident: e_1_2_5_13_1 doi: 10.1038/78829 – ident: e_1_2_5_35_1 doi: 10.1016/S0896-6273(01)00451-2 – ident: e_1_2_5_33_1 doi: 10.1063/1.2926374 – ident: e_1_2_5_11_1 doi: 10.1126/science.1254642 – ident: e_1_2_5_27_1 – ident: e_1_2_5_47_1 doi: 10.1038/ncomms15434 – ident: e_1_2_5_42_1 doi: 10.1038/nn.3948 – ident: e_1_2_5_25_1 doi: 10.1103/PhysRevApplied.9.014034 – ident: e_1_2_5_9_1 doi: 10.1016/j.neunet.2014.01.006 – ident: e_1_2_5_22_1 doi: 10.1002/adfm.201604740 – ident: e_1_2_5_46_1 doi: 10.1126/science.aab1031 – ident: e_1_2_5_21_1 doi: 10.1002/adma.201802353 – ident: e_1_2_5_18_1 doi: 10.1021/nl201040y – ident: e_1_2_5_37_1 doi: 10.1162/jocn.1990.2.1.58 – ident: e_1_2_5_15_1 doi: 10.1002/adma.201103723 – ident: e_1_2_5_17_1 doi: 10.1038/srep10150 – ident: e_1_2_5_26_1 doi: 10.1038/nature23011 – ident: e_1_2_5_34_1 doi: 10.1038/236 – ident: e_1_2_5_14_1 doi: 10.1109/JPROC.2014.2313954 – ident: e_1_2_5_38_1 doi: 10.7554/eLife.23612 – ident: e_1_2_5_30_1 doi: 10.1038/nature06932 – ident: e_1_2_5_23_1 doi: 10.1038/s41598-017-07418-y – ident: e_1_2_5_40_1 doi: 10.1371/journal.pcbi.1003408 – ident: e_1_2_5_29_1 doi: 10.1038/nature10309 – ident: e_1_2_5_2_1 doi: 10.1073/pnas.0712231105 – ident: e_1_2_5_12_1 doi: 10.1523/JNEUROSCI.18-24-10464.1998 – ident: e_1_2_5_19_1 doi: 10.1002/adfm.201101935 |
SSID | ssj0009606 |
Score | 2.651932 |
Snippet | Efficient information processing in the human brain is achieved by dynamics of neurons and synapses, motivating effective implementation of artificial spiking... Abstract Efficient information processing in the human brain is achieved by dynamics of neurons and synapses, motivating effective implementation of artificial... |
SourceID | proquest crossref pubmed wiley |
SourceType | Aggregation Database Index Database Publisher |
StartPage | e1900636 |
SubjectTerms | Antiferromagnetism antiferromagnets Brain Cognitive tasks Data processing Dynamics Ferromagnetism Heterostructures Materials science Neural networks Neurons Orbital mechanics Pulse duration Spiking Spin dynamics Spintronics Switching theory Synapses Torque |
Title | Artificial Neuron and Synapse Realized in an Antiferromagnet/Ferromagnet Heterostructure Using Dynamics of Spin–Orbit Torque Switching |
URI | https://onlinelibrary.wiley.com/doi/abs/10.1002%2Fadma.201900636 https://www.ncbi.nlm.nih.gov/pubmed/30989740 https://www.proquest.com/docview/2233749757 https://search.proquest.com/docview/2210261295 |
Volume | 31 |
hasFullText | 1 |
inHoldings | 1 |
isFullTextHit | |
isPrint | |
link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpZ3Pa9swFMfF6Kk77PcPd-3QYLCTW8f6YesY2oYw2AZNBr0Z_cowo3ZwEkZ76nH3_Yf7S_aelDjNdhhsJ8s_ZMuSnt7X9vNHhLwFF-fFTMhU69ymoP95quBBKGXlLHNSuVzoECD7UY4_8_eX4vLOX_yRD9G_cEPLCOM1Grg2i5MtNFS7wA0ChwZeFpnbSNNDVXSx5UehPA-wPSZSJXm5oTZm-clu9l2v9IfU3FWuwfWMHhK9KXSMOPl6vFqaY3vzG8_xf-7qEXmw1qV0GDvSY3LPN0_I_Tu0wqfkO-6MwAkamB4N1Y2jk-tGzxeeXoDkrG-8ozVup0OMQvJd117pL_j6Y7RN0zHG4LQRXbvqPA1xC_QMTnRV2wVtZ3Qyr5uftz8-daZe0mnbQUXRybd6GSI_n5Hp6Hx6Ok7XEzmkFvSOTBlznDtlQJ3afDawXEpXKlEaEBPwfKML6TNpWFZqrQZc58pnMOzBEidBs4o9J3tN2_iXhAqjTWZZ7hBrA1pEa-fLTMHJRGkHRZmQd5t2rOYR11FFMHNeYdVWfdUm5HDTzNXabBcVaCVWcFWIIiFv-t1gcPgVRTe-XeExg8BdUyIhL2L36C_FsCgFzxKSh0b-Sxmq4dmHYb928C-ZXpF9TMfgtUOyBy3nj0AmLc3rYAq_APsfCbY |
link.rule.ids | 315,786,790,1382,27955,27956,46327,46751 |
linkProvider | Wiley-Blackwell |
linkToHtml | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV3LjtMwFL2CYQEseA8EBjASEqvMpPEj8bKiVAVmBmlaJHaRY7soQpNUaSvErFiy5w_5Eq7tJqWwQIJVEjt2HNvX99g5OQZ4ji7O8jkXsVKpjhH_s1jiRCim-TwxQpqUK0-QPRWT9-zNB96xCd2_MEEfol9wc5bhx2tn4G5B-mirGqqMFw5Cj4ZuVlyGK2jz3Nnm6GyrIOUAupfbozyWguWdbmOSHu2m3_VLf4DNXezqnc_4JpRdsQPn5NPhelUe6ovfFB3_671uwY0NNCXD0JduwyVb34HrvwgW3oVvLjJoThAv61ETVRsy_VKrxdKSM0Sd1YU1pHLhZOiISLZtm3P10a2AjLfnZOJoOE1Qr123lnjqAhlhRueVXpJmTqaLqv7x9fu7tqxWZNa0WFNk-rlaefLnPZiNX81eTuLNXg6xRsgjYkoNY0aWCFB1Oh9oJoTJJc9LxBM4xVGZsIkoaZIrJQdMpdImOPLh0e2DpiXdh726qe0DILxUZaJpapyyDcIRpYzNE4mZ8VwPsjyCF11DFoug2FEEbea0cFVb9FUbwUHXzsXGcpcFwiWaMZnxLIJnfTTanPuQomrbrN09Ay-9JnkE90P_6B9FXVEylkSQ-lb-SxmK4ehk2F89_JdET-HqZHZyXBy_Pn37CK658MBlO4A9bEX7GFHTqnzi7eInoVcN1g |
linkToPdf | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwpV1Lj9MwEB7BIiE48H4EFjASEqfspn4lPlaUqrwWtC3S3iLHdlCENqnSVog9ceTOP-SXMHbadAsHJDglsWPH8Xg83ziTzwDP0MQ5UQoZa01NjPifxwodoZhlZWKlslToECB7JCcf-esTcXLuL_6OH6JfcPOaEeZrr-BzWx5uSUO1DbxBaNDQysqLcIlLRr37NTreEkh5fB7Y9piIleTZhrYxoYe75XfN0h9Ycxe6Btszvg560-ou5OTzwWpZHJiz3wgd_-e1bsC1NTAlw24k3YQLrr4FV8_RFd6G7z6zY5wggdSjJrq2ZPq11vOFI8eIOaszZ0nl08nQhyG5tm1O9Se__jHenpOJD8JpOu7aVetICFwgI6zotDIL0pRkOq_qn99-vG-LaklmTYsdRaZfqmUI_bwDs_HL2YtJvN7JITYIeGTMmOXcqgLhqaHlwHApbaZEViCaQAdHp9IlsmBJprUacE2VS3Dew6PfBc0odhf26qZ294GIQheJYdR6XhsEI1pblyUKKxOZGaRZBM83csznHV9H3jEz09x3bd53bQT7GzHna71d5AiWWMpVKtIInvbZqHH-M4quXbPy9wwC8ZoSEdzrhkf_KOabkvIkAhqE_Jc25MPRu2F_9eBfCj2Byx9G4_ztq6M3D-GKT-4C2fZhD4XoHiFkWhaPg1b8AmkpDIU |
openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Ajournal&rft.genre=article&rft.atitle=Artificial+Neuron+and+Synapse+Realized+in+an+Antiferromagnet%2FFerromagnet+Heterostructure+Using+Dynamics+of+Spin%E2%80%93Orbit+Torque+Switching&rft.jtitle=Advanced+materials+%28Weinheim%29&rft.au=Kurenkov%2C+Aleksandr&rft.au=DuttaGupta%2C+Samik&rft.au=Zhang%2C+Chaoliang&rft.au=Fukami%2C+Shunsuke&rft.date=2019-06-01&rft.issn=0935-9648&rft.eissn=1521-4095&rft.volume=31&rft.issue=23&rft.epage=n%2Fa&rft_id=info:doi/10.1002%2Fadma.201900636&rft.externalDBID=10.1002%252Fadma.201900636&rft.externalDocID=ADMA201900636 |
thumbnail_l | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/lc.gif&issn=0935-9648&client=summon |
thumbnail_m | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/mc.gif&issn=0935-9648&client=summon |
thumbnail_s | http://covers-cdn.summon.serialssolutions.com/index.aspx?isbn=/sc.gif&issn=0935-9648&client=summon |