Improvement of the weight update and retention characteristics of Pr 0.7 Ca 0.3 MnO 3− x ECRAM via elevated temperature training
Source abstract
Abstract
To achieve both excellent analog switching for training and retention for inference simultaneously, we investigated elevated-temperature (ET) training of Pr0.7Ca0.3MnO3-x (PCMO) electrochemical random access memory (ECRAM). Improved weight update characteristics can be obtained by thermally reduced ionic resistivity of the HfOx electrolyte at ET (413 K). Furthermore, excellent retention characteristics (108 s) were observed at room temperature, which can be explained by enhanced ion storage within the reservoir (or channel) layer via ET training. By adopting ET training on PCMO ECRAM, we can achieve both training and inference accuracy of neural networks (NNs).
Source: europepmc · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Electrical and Thermal Properties of Materials · Transition Metal Oxide Nanomaterials
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Center for Single Atom-Based Semiconductor Device and Department of Materials Science and Engineering, Pohang University of Science and Technology, Pohang 37673, Republic of Korea
Department of Electronic Materials Engineering, Kwangwoon University, Seoul 01897, Republic of Korea
Funding
National Research Foundation of Korea · Kwangwoon University
References (30)
Show source-provided references
1. Gokmen · Front. Neurosci. · 2016 · 10 · 33310.3389/fnins.2016.00333 ↗
2. Burr · Adv. Phys.:X · 2017 · 2 · 89
3. P.-Y.Chen , X.Peng and S.Yu
4. X.Peng , S.Huang , Y.Luo , X.Sun and S.Yu
5. Burr · IEEE Trans. Electron Devices · 2015 · 62 · 349810.1109/TED.2015.2439635 ↗
6. Woo · IEEE Electron Device Lett. · 2016 · 37 · 99410.1109/LED.2016.2582859 ↗
7. Lee · IEEE Electron Device Lett. · 2019 · 40 · 54610.1109/LED.2019.2897777 ↗
8. Fuller · Adv. Mater. · 2016 · 29 · 160431010.1002/adma.201604310 ↗
9. Lee · IEEE Electron Device Lett. · 2020 · 41 · 150010.1109/LED.2020.3019938 ↗
10. S.Kim , T.Todorov , M.Onen , T.Gokmen , D.Bishop , P.Solomon , K.-T.Lee , M.Copel , D. B.Farmer , J. A.Ott
11. J.Tang , D.Bishop , S.Kim , M.Copel , T.Gokmen , T.Todorov , S.Shin , K.-T.Lee , P.Solomon , K.Chan
12. C.Lee , W.Choi , M.Kwak , S.Kim and H.Hwang
13. Jeong · Adv. Electron. Mater. · 2021 · 7 · 210018510.1002/aelm.202100185 ↗
14. Lee · IEEE Trans. Electron Devices · 2022 · 69 · 221810.1109/TED.2022.3151306 ↗
15. Li · Appl. Phys. Lett. · 2022 · 120 · 02190110.1063/5.0082061 ↗
16. Fuller · Science · 2019 · 364 · 57010.1126/science.aaw5581 ↗
17. Li · Adv. Mater. · 2020 · 32 · 200398410.1002/adma.202003984 ↗
18. C.Lee , M.Kwak , W. K.Choi , S.Kim and H.Hwang
19. M.Baldo and D.Ielmini
20. Lee · Appl. Phys. Lett. · 2021 · 119 · 10350310.1063/5.0059804 ↗
21. Kang · Appl. Phys. Lett. · 2022 · 120 · 12210110.1063/5.0086164 ↗
22. McKenna · Appl. Phys. Lett. · 2009 · 95 · 22211110.1063/1.3271184 ↗
23. Liu · Adv. Electron. Mater. · 2017 · 3 · 160051310.1002/aelm.201600513 ↗
24. Veldhuis · J. Sol-Gel Sci. Technol. · 2014 · 71 · 118
25. Nian · Phys. Rev. Lett. · 2007 · 98 · 14640310.1103/PhysRevLett.98.146403 ↗
26. Nikam · Adv. Electron. Mater. · 2021 · 7 · 210014210.1002/aelm.202100142 ↗
27. Lee · ACS Appl. Mater. Interfaces · 2022 · 14 · 1345010.1021/acsami.1c21045 ↗
28. Lee · Nanotechnology · 2020 · 31 · 23520310.1088/1361-6528/ab793d ↗
29. X.Peng , S.Huang , Y.Luo , X.Sun and S.Yu
30. Lee · Nanotechnology · 2020 · 31 · 45520410.1088/1361-6528/abaa0e ↗