journal article·2018-05-01Open access

Research Update: Ab initio study on resistive memory device optimization trends: Dopant segregation effects and data retention in HfO2−x

Blanka Magyari-Köpe, Yali Song, Dan Duncan, Liang Zhao, Yoshio Nishi

APL Materials· Volume 6· Issue 5

Abstract

Segregation energy trends and their charge state dependence were established for Group II to Group VI substitutional metal dopants in HfO2 using density functional theory. Corroborating the segregation energy with dopant-oxygen bond lengths and charge state stability, strong effects are predicted for Group II and Group III p-type dopants, which can easily reverse their segregation trend due to −2 charge state preference. Transitions between segregation and isolation may occur around 1.5 eV above the valence band maximum, with the exception of Al, which remains barely stable in its segregated form. In Al-doped HfOx, the switching characteristics of filaments formed near Al dopants show subtle changes and the OFF state data retention is degraded. A comprehensive assessment on configurational Al-VO interaction, charge state dependence, and migration energy changes points to the fact that to achieve OFF state data retention improvements, it will be necessary to engineer the filament interaction with Al to stabilize configurations that favor vacancy filament dissolution. Another mode of failure can result from subsequent charge trapping during the operation of the device, which ultimately prohibits the filament dissociation.
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Research context

OpenAlex topics: Semiconductor materials and devices · Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Electrical Engineering, Stanford University , Stanford, California 94305, USA

References (53)

Show source-provided references
1. Nat. Nanotechnol. · 2015 · 10 · 19110.1038/nnano.2015.29 ↗
2. Nat. Commun. · 2015 · 6 · 861010.1038/ncomms9610 ↗
3. Deleonibus · 2014 · 32510.1201/b15600 ↗
4. Nanotechnology · 2011 · 22 · 25402710.1088/0957-4484/22/25/254027 ↗
5. Proc. IEEE · 2010 · 98 · 223710.1109/jproc.2010.2070830 ↗
6. Nat. Mater. · 2007 · 6 · 83310.1038/nmat2023 ↗
7. Nat. Commun. · 2012 · 3 · 73210.1038/ncomms1737 ↗
8. Nano Lett. · 2010 · 10 · 129710.1021/nl904092h ↗
9. Nanotechnology · 2013 · 24 · 38401010.1088/0957-4484/24/38/384010 ↗
10. Nanotechnology · 2011 · 22 · 25402910.1088/0957-4484/22/25/254029 ↗
11. J. Mater. Sci. · 2012 · 47 · 749810.1007/s10853-012-6638-1 ↗
12. IEEE Trans. Electron Devices · 2015 · 62 · 199810.1109/ted.2015.2418114 ↗
13. IEEE Trans. Electron Devices · 2011 · 58 · 430910.1109/ted.2011.2167513 ↗
14. IEEE Trans. Electron Devices · 2014 · 61 · 237810.1109/TED.2014.2325531 ↗
15. 2012 · 75
16. Nat. Nanotechnol. · 2016 · 11 · 6710.1038/nnano.2015.221 ↗
17. 2011 · 46
18. Park · IEEE Electron Device Lett. · 2011 · 32 · 19710.1109/led.2010.2091489 ↗
19. Phys. Rev. Appl. · 2015 · 4 · 06400810.1103/physrevapplied.4.064008 ↗
20. J. Phys.: Condens. Matter · 2015 · 27 · 41540110.1088/0953-8984/27/41/415401 ↗
21. MRS Proc. · 2012 · 1430 · 110310.1557/opl.2012.1103 ↗
22. Zhao · Math. Comput. Modell. · 2013 · 58 · 27510.1016/j.mcm.2012.11.009 ↗
23. Zhao · Appl. Phys. Lett. · 2013 · 102 · 08350610.1063/1.4794083 ↗
24. IEEE Trans. Electron Devices · 2014 · 61 · 139410.1109/ted.2014.2312943 ↗
25. Phys. Status Solidi RRL · 2014 · 8 · 56010.1002/pssr.201409018 ↗
26. ECS Trans. · 2014 · 64 · 15310.1149/06408.0153ecst ↗
27. J. Appl. Phys. · 2014 · 115 · 18370310.1063/1.4876262 ↗
28. Appl. Phys. Lett. · 2012 · 100 · 07350210.1063/1.3685222 ↗
29. Phys. Rev. B · 2013 · 87 · 15520110.1103/physrevb.87.155201 ↗
30. Appl. Phys. Lett. · 2013 · 102 · 20190810.1063/1.4807666 ↗
31. IEEE Electron Device Lett. · 2016 · 37 · 40010.1109/led.2016.2524450 ↗
32. Duncan · Appl. Phys. Lett. · 2016 · 108 · 04350110.1063/1.4940369 ↗
33. Duncan · Phys. Rev. Appl. · 2017 · 7 · 03402010.1103/physrevapplied.7.034020 ↗
34. Phys. Rev. B · 1993 · 47 · 55810.1103/physrevb.47.558 ↗
35. Phys. Rev. B · 1994 · 49 · 1425110.1103/physrevb.49.14251 ↗
36. Phys. Rev. B · 1999 · 59 · 175810.1103/physrevb.59.1758 ↗
37. Phys. Rev. B · 1994 · 50 · 1795310.1103/physrevb.50.17953 ↗
38. Phys. Rev. B · 1998 · 57 · 150510.1103/physrevb.57.1505 ↗
39. Phys. Rev. B · 2010 · 82 · 11510910.1103/physrevb.82.115109 ↗
40. Phys. Rev. Lett. · 2011 · 107 · 21680310.1103/physrevlett.107.216803 ↗
41. Microelectron. Eng. · 2011 · 88 · 146410.1016/j.mee.2011.03.078 ↗
42. J. Semicond. · 2014 · 35 · 04200210.1088/1674-4926/35/4/042002 ↗
43. Semicond. Sci. Technol. · 2012 · 27 · 12500810.1088/0268-1242/27/12/125008 ↗
44. J. Appl. Phys. · 2015 · 117 · 12450110.1063/1.4915946 ↗
45. Nanotechnology · 2012 · 23 · 32570210.1088/0957-4484/23/32/325702 ↗
46. Curr. Appl. Phys. · 2016 · 16 · 63810.1016/j.cap.2016.03.014 ↗
47. J. Appl. Phys. · 2013 · 113 · 16450710.1063/1.4803076 ↗
48. Appl. Phys. Lett. · 2015 · 107 · 01350410.1063/1.4926337 ↗
49. Microelectron. Eng. · 2015 · 147 · 10410.1016/j.mee.2015.04.043 ↗
50. Nanotechnology · 2017 · 28 · 39520210.1088/1361-6528/aa8013 ↗
51. 2017 · 157
52. ACS Appl. Mater. Interfaces · 2017 · 9 · 1629610.1021/acsami.7b00139 ↗
53. Comput. Sci. Eng. · 2014 · 16 · 6210.1109/mcse.2014.80 ↗