journal article·2024-02-27Open access

Thermal Compact Modeling and Resistive Switching Analysis in Titanium Oxide-Based Memristors

Juan B. Roldán, Antonio Cantudo, David Maldonado, Cristina Aguilera-Pedregosa, Enrique Moreno, Timm Swoboda, Francisco Jiménez-Molinos, Yue Yuan, Kaichen Zhu, Mario Lanza, Miguel Muñoz Rojo

Abstract

High Resolution Image Download MS PowerPoint Slide Resistive switching devices based on the Au/Ti/TiO 2 /Au stack were developed. In addition to standard electrical characterization by means of I – V curves, scanning thermal microscopy was employed to localize the hot spots on the top device surface (linked to conductive nanofilaments, CNFs) and perform in-operando tracking of temperature in such spots. In this way, electrical and thermal responses can be simultaneously recorded and related to each other. In a complementary way, a model for device simulation (based on COMSOL Multiphysics) was implemented in order to link the measured temperature to simulated device temperature maps. The data obtained were employed to calculate the thermal resistance to be used in compact models, such as the Stanford model, for circuit simulation. The thermal resistance extraction technique presented in this work is based on electrical and thermal measurements instead of being indirectly supported by a single fitting of the electrical response (using just I – V curves), as usual. Besides, the set and reset voltages were calculated from the complete I – V curve resistive switching series through different automatic numerical methods to assess the device variability. The series resistance was also obtained from experimental measurements, whose value is also incorporated into a compact model enhanced version.
Source: openalex_inverted_index · Quality: baseline

Research context

OpenAlex topics: Advanced Memory and Neural Computing · Ferroelectric and Negative Capacitance Devices · Neuroscience and Neural Engineering

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

Affiliations

Departamento de Electrónica y Tecnología de Computadores, Universidad de Granada, Facultad de Ciencias. Avenida Fuentenueva s/n, 18071 Granada, Spain

IHP-Leibniz-Institut für innovative Mikroelektronik, 15236 Frankfurt (Oder), Germany

CEMDATIC─E.T.S.I Telecomunicación, Universidad Politécnica de Madrid (UPM), 28040 Madrid, Spain

Department of Thermal and Fluid Engineering, Faculty of Engineering Technology, University of Twente, 7500 AE Enschede, The Netherlands

Materials Science and Engineering Program, Physical Sciences and Engineering Division, King Abdullah University of Science and Technology (KAUST), Thuwal 23955-6900, Saudi Arabia

MIND, Department of Electronic and Biomedical Engineering, Universitat de Barcelona, Martí i Franquès 1, E-08028 Barcelona, Spain

2D Foundry, Instituto de Ciencia de Materiales de Madrid (ICMM), CSIC, Madrid 28049, Spain

Funding

Ministerio de Ciencia e Innovaci?n · King Abdullah University of Science and Technology

References (56)

Show source-provided references
1. 10.1126/science.abj997910.1126/science.abj9979 ↗
2. 10.1109/isscc.2018.831039210.1109/isscc.2018.8310392 ↗
3. 10.1109/vlsitechnology18217.2020.926506010.1109/vlsitechnology18217.2020.9265060 ↗
4. 10.1109/vlsicircuits18222.2020.916301410.1109/vlsicircuits18222.2020.9163014 ↗
5. 10.1109/isscc.2019.866239310.1109/isscc.2019.8662393 ↗
6. 10.1038/s41565-020-0655-z10.1038/s41565-020-0655-z ↗
7. 10.1109/TED.2011.214779110.1109/TED.2011.2147791 ↗
8. 10.3390/electronics1006064510.3390/electronics10060645 ↗
9. 10.1038/s41586-018-0180-510.1038/s41586-018-0180-5 ↗
10. 10.1126/science.125464210.1126/science.1254642 ↗
11. 10.1002/smll.20210110010.1002/smll.202101100 ↗
12. 10.1038/ncomms307210.1038/ncomms3072 ↗
13. 10.1038/nature1444110.1038/nature14441 ↗
14. 10.1038/s41928-017-0006-810.1038/s41928-017-0006-8 ↗
15. 10.1038/s41699-022-00341-510.1038/s41699-022-00341-5 ↗
16. 10.1109/MCAS.2021.309253310.1109/MCAS.2021.3092533 ↗
17. 10.1109/iedm.2016.783834910.1109/iedm.2016.7838349 ↗
18. 10.1002/adma.20210018510.1002/adma.202100185 ↗
19. 10.1002/aelm.20190019810.1002/aelm.201900198 ↗
20. 10.1088/1361-6463/aa793910.1088/1361-6463/aa7939 ↗
21. 10.1021/acsaelm.1c0039810.1021/acsaelm.1c00398 ↗
22. Ielmini D. · 2015
23. 10.1088/1361-6463/ab7bb610.1088/1361-6463/ab7bb6 ↗
24. 10.1021/acs.nanolett.5b0069710.1021/acs.nanolett.5b00697 ↗
25. 10.3390/nano1105126110.3390/nano11051261 ↗
26. 10.1002/aelm.20170029410.1002/aelm.201700294 ↗
27. 10.1109/TED.2011.216751310.1109/TED.2011.2167513 ↗
28. 10.1002/aisy.20220033810.1002/aisy.202200338 ↗
29. 10.1021/acsami.2c2261710.1021/acsami.2c22617 ↗
30. 10.1021/acsaelm.3c0078210.1021/acsaelm.3c00782 ↗
31. 10.1109/LED.2012.221085610.1109/LED.2012.2210856 ↗
32. 10.1109/sispad.2014.693155810.1109/sispad.2014.6931558 ↗
33. 10.1109/TED.2016.254541210.1109/TED.2016.2545412 ↗
34. 10.1109/TED.2015.249242110.1109/TED.2015.2492421 ↗
35. 10.1039/d3nr00343d10.1039/d3nr00343d ↗
36. 10.1126/sciadv.abk151410.1126/sciadv.abk1514 ↗
37. 10.3390/nano1004067010.3390/nano10040670 ↗
38. 10.1063/1.502104410.1063/1.5021044 ↗
39. 10.1109/LED.2010.204631010.1109/LED.2010.2046310 ↗
40. 10.1063/1.481849910.1063/1.4818499 ↗
41. 10.1063/1.500699510.1063/1.5006995 ↗
42. 10.1063/1.488150010.1063/1.4881500 ↗
43. 10.1109/ULIS.2012.619336710.1109/ULIS.2012.6193367 ↗
44. Chiu Y.-C. · 2019
45. 10.1038/s41928-020-0416-x10.1038/s41928-020-0416-x ↗
46. 10.1038/s41928-018-0039-710.1038/s41928-018-0039-7 ↗
47. 10.1038/s41928-020-00473-w10.1038/s41928-020-00473-w ↗
48. 10.1038/s41586-023-05973-110.1038/s41586-023-05973-1 ↗
49. 10.3390/math917215910.3390/math9172159 ↗
50. 10.1063/5.005598210.1063/5.0055982 ↗
51. 10.1038/nature2574710.1038/nature25747 ↗
52. 10.1038/s41586-018-0574-410.1038/s41586-018-0574-4 ↗
53. 10.1038/s41586-020-2861-010.1038/s41586-020-2861-0 ↗
54. 10.1038/s41586-020-2038-x10.1038/s41586-020-2038-x ↗
55. 10.1109/IEDM19574.2021.972065110.1109/IEDM19574.2021.9720651 ↗
56. Dorow C. J. · 2021 · 1