Gallium Oxide RRAM: Materials, Fundamentals and Applications
Source abstract
Abstract
ABSTRACT With the swift advancement of information technology, the demand for data storage is surging exponentially. Mainstream storage technologies are now constrained by physical limitations, making it difficult to improve storage density as well as read/write speeds. Meanwhile, the “storage‐computation” separation in the von Neumann architecture has also created an insurmountable “memory wall” bottleneck, and frequent data transfer reduces energy efficiency. To meet the demand for real‐time data processing and neuromorphic computing's need for in‐memory integration, there's an urgent need for new storage technologies offering ultra‐high density, speed, and storage‐computation integration. Recently, resistive random‐access memory (RRAM) has attracted considerable attention from researchers and stands out as a competitive candidate in the realm of non‐volatile memory. Gallium Oxide (Ga 2 O 3 ), an emerging ultra‐wide bandgap semiconductor material, has emerged as one of the most promising candidates for RRAM due to its unique electrical and physical properties. Herein, this paper introduces the material properties of Ga 2 O 3 , and outlines the working principle of Ga 2 O 3 RRAM, performance evaluation of Ga 2 O 3 RRAM and applications of Ga 2 O 3 RRAM. Finally, insights and perspectives on the future development of Ga 2 O 3 RRAM are discussed to promote its application in the field of storage and neuromorphic computing.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · 2D Materials and Applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Faculty of Infor‐X Xidian University Xi'an China
State Key Laboratory of Wide‐Bandgap Semiconductor Devices and Integrated Technology School of Microelectronics Xidian University Xi'an China
Guangzhou Institute of Technology Xidian University Guangzhou China
Funding
National Natural Science Foundation of China · National Key Research and Development Program of China
References (100+)
Show source-provided references
1. 10.1039/D0CS00569J10.1039/D0CS00569J ↗
2. 10.1016/j.mee.2018.01.00910.1016/j.mee.2018.01.009 ↗
3. 10.1016/j.chip.2024.10012210.1016/j.chip.2024.100122 ↗
4. 10.1063/1.492733210.1063/1.4927332 ↗
5. 10.1063/1.496618110.1063/1.4966181 ↗
6. 10.1038/s41598‐019‐50816‐710.1038/s41598‐019‐50816‐7 ↗
7. 10.1002/aelm.20240051210.1002/aelm.202400512 ↗
8. 10.1002/adma.20231070410.1002/adma.202310704 ↗
9. 10.1007/s10853‐018‐2134‐610.1007/s10853‐018‐2134‐6 ↗
10. 10.1002/adfm.20251516510.1002/adfm.202515165 ↗
11. 10.1021/acsami.0c0647610.1021/acsami.0c06476 ↗
12. 10.1016/j.jallcom.2019.04.25310.1016/j.jallcom.2019.04.253 ↗
13. 10.35848/1347‐4065/acdbf310.35848/1347‐4065/acdbf3 ↗
14. 10.1002/adma.20221173810.1002/adma.202211738 ↗
15. 10.1038/s41467‐025‐57200‐210.1038/s41467‐025‐57200‐2 ↗
16. 10.1002/adfm.20240117010.1002/adfm.202401170 ↗
17. 10.1109/LED.2023.323759810.1109/LED.2023.3237598 ↗
18. 10.1021/acsnano.4c0323810.1021/acsnano.4c03238 ↗
19. 10.1002/inf2.1250310.1002/inf2.12503 ↗
20. 10.1007/s42114-023-00686-510.1007/s42114-023-00686-5 ↗
21. Optimizing Endurance Performance of Ga2O3 Random Resistive Access Memories by Altering Oxygen Vacancy Content
22. 10.1088/1361‐6528/ab758d10.1088/1361‐6528/ab758d ↗
23. 10.1063/5.019994610.1063/5.0199946 ↗
24. 10.1016/j.ceramint.2020.05.19110.1016/j.ceramint.2020.05.191 ↗
25. 10.3390/nano1312185110.3390/nano13121851 ↗
26. 10.1063/5.019938510.1063/5.0199385 ↗
27. 10.1016/j.vacuum.2021.11042210.1016/j.vacuum.2021.110422 ↗
28. 10.3390/ma1711272710.3390/ma17112727 ↗
29. 10.1103/PhysRevMaterials.1.02460410.1103/PhysRevMaterials.1.024604 ↗
30. 10.1063/1.184094510.1063/1.1840945 ↗
31. 10.1063/1.175450010.1063/1.1754500 ↗
32. 10.1063/1.495086710.1063/1.4950867 ↗
33. 10.1063/1.498647810.1063/1.4986478 ↗
34. 10.1002/chem.20120335910.1002/chem.201203359 ↗
35. 10.3390/nano1108201310.3390/nano11082013 ↗
36. 10.1063/1.366587110.1063/1.3665871 ↗
37. 10.1088/1361‐6528/aca41810.1088/1361‐6528/aca418 ↗
38. 10.1088/1361‐6463/ac1af210.1088/1361‐6463/ac1af2 ↗
39. 10.1038/asiamat.2010.510.1038/asiamat.2010.5 ↗
40. 10.1021/acsami.9b1740910.1021/acsami.9b17409 ↗
41. Recent Progress of Deep Ultraviolet Photodetectors using Amorphous Gallium Oxide Thin Films
42. 10.1109/LED.2022.323024710.1109/LED.2022.3230247 ↗
43. 10.1063/1.490717410.1063/1.4907174 ↗
44. 10.1063/1.360148810.1063/1.3601488 ↗
45. 10.1016/j.snb.2012.06.05710.1016/j.snb.2012.06.057 ↗
46. 10.1021/acsami.9b2240010.1021/acsami.9b22400 ↗
47. 10.3390/ma1711272710.3390/ma17112727 ↗
48. 10.1088/0268‐1242/31/3/03400110.1088/0268‐1242/31/3/034001 ↗
49. 10.1088/1674‐4926/40/1/01180310.1088/1674‐4926/40/1/011803 ↗
50. 10.1088/1674-1056/28/1/01710510.1088/1674-1056/28/1/017105 ↗
51. 10.1063/1.367428710.1063/1.3674287 ↗
52. 10.1063/1.133055910.1063/1.1330559 ↗
53. 10.1063/1.505105810.1063/1.5051058 ↗
54. 10.3390/nano1102045610.3390/nano11020456 ↗
55. 10.1143/APEX.1.01120210.1143/APEX.1.011202 ↗
56. 10.1063/1.243294610.1063/1.2432946 ↗
57. 10.1016/j.spmi.2019.10631610.1016/j.spmi.2019.106316 ↗
58. 10.1109/LPT.2018.282656010.1109/LPT.2018.2826560 ↗
59. 10.1016/j.jallcom.2019.15341910.1016/j.jallcom.2019.153419 ↗
60. 10.1021/acsami.1c1169210.1021/acsami.1c11692 ↗
61. 10.1063/1.506447110.1063/1.5064471 ↗
62. 10.1149/08007.0203ecst10.1149/08007.0203ecst ↗
63. 10.1016/j.jssc.2020.12157610.1016/j.jssc.2020.121576 ↗
64. 10.1016/j.mser.2014.06.00210.1016/j.mser.2014.06.002 ↗
65. 10.1038/nnano.2012.24010.1038/nnano.2012.240 ↗
66. 10.1109/JPROC.2012.219036910.1109/JPROC.2012.2190369 ↗
67. I. G.Baek M. S.Lee andS.Seo “Highly scalable nonvolatile resistive memory using simple binary oxide driven by asymmetric unipolar voltage pulses ” inIEDM Technical Digest. IEEE International Electron Devices Meeting(IEEE 2004) 587–590.10.1109/IEDM.2004.1419228 ↗
68. 10.1186/1556‐276X‐8‐41810.1186/1556‐276X‐8‐418 ↗
69. 10.1186/1556‐276X‐9‐52610.1186/1556‐276X‐9‐526 ↗
70. 10.1016/j.apsusc.2012.01.03410.1016/j.apsusc.2012.01.034 ↗
71. 10.1063/1.513626410.1063/1.5136264 ↗
72. 10.1002/pssa.20230041610.1002/pssa.202300416 ↗
73. 10.1063/1.479169510.1063/1.4791695 ↗
74. 10.1063/1.486465310.1063/1.4864653 ↗
75. 10.1016/j.mee.2013.04.00510.1016/j.mee.2013.04.005 ↗
76. 10.1109/LED.2015.247749110.1109/LED.2015.2477491 ↗
77. 10.1063/1.348988210.1063/1.3489882 ↗
78. 10.3390/cryst1303041610.3390/cryst13030416 ↗
79. 10.1149/1.274298910.1149/1.2742989 ↗
80. 10.1021/acsami.7b1621410.1021/acsami.7b16214 ↗
81. 10.1149/2754‐2734/ac79bf10.1149/2754‐2734/ac79bf ↗
82. 10.1109/ACCESS.2019.294842310.1109/ACCESS.2019.2948423 ↗
83. 10.1063/1.499056610.1063/1.4990566 ↗
84. 10.1063/1.350196710.1063/1.3501967 ↗
85. 10.1039/C9TC02055A10.1039/C9TC02055A ↗
86. 10.1039/C7TC02221B10.1039/C7TC02221B ↗
87. 10.1063/1.494106110.1063/1.4941061 ↗
88. 10.1088/1674‐4926/44/7/07410110.1088/1674‐4926/44/7/074101 ↗
89. 10.1039/D0CP06239A10.1039/D0CP06239A ↗
90. 10.1038/s41377‐025‐01773‐610.1038/s41377‐025‐01773‐6 ↗
91. 10.1103/PhysRevLett.98.04550110.1103/PhysRevLett.98.045501 ↗
92. 10.1038/nnano.2009.45610.1038/nnano.2009.456 ↗
93. 10.1021/nl900006g10.1021/nl900006g ↗
94. 10.1063/1.323663210.1063/1.3236632 ↗
95. 10.1038/nnano.2008.16010.1038/nnano.2008.160 ↗
96. 10.1063/1.503078010.1063/1.5030780 ↗
97. 10.1063/1.311580510.1063/1.3115805 ↗
98. 10.1016/j.apsusc.2020.14747610.1016/j.apsusc.2020.147476 ↗
99. 10.1002/pssr.20190007310.1002/pssr.201900073 ↗
100. J.Guy G.Molas andP.Blaise “Experimental and Theoretical Understanding of Forming SET and RESET Operations in Conductive Bridge RAM (CBRAM) for Memory Stack Optimization ” inTechnical Digest—International Electron Devices Meeting IEDM(IEEE 2015).