journal article·2026-01Open access

VO 2 Oscillator Circuits Optimized for Ultrafast, 100 MHz‐Range Operation

Zsigmond Pollner, Tímea Nóra Török, László Pósa, Miklós Csontos, Sebastian Werner Schmid, Zoltán Balogh, András Bükkfejes, Heungsoo Kim, Alberto Piqué, Juerg Leuthold, János Volk, András Halbritter

Advanced Electronic Materials· Volume 12· Issue 1

Abstract

Abstract Oscillating neural networks are promising candidates for a new computational paradigm, where complex optimization problems are solved by physics itself through the synchronization of coupled oscillating circuits. VO 2 Mott memristors are particularly promising building blocks for such oscillating neural networks. Until now, however, not only the maximum frequency of VO 2 oscillating neural networks, but also the maximum frequency of individual VO 2 oscillators is severely limited, which has restricted their efficient and energy‐saving use. In this study, it is showed how to increase the oscillating frequency by more than an order of magnitude into the 100 MHz range utilizing ultrasmall, ≈30 nm wide active volume VO 2 devices and optimizing the circuit layout for high frequency operation. In addition, the physical limiting factors of the oscillation frequencies are studied by investigating the complex switching dynamics of our nanoscale VO 2 devices. These dynamical studies, together with simulations, provide a clear conclusion on the maximum achievable operating frequencies and the optimal operating parameters under which these can be reached.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Transition Metal Oxide Nanomaterials · Advanced Memory and Neural Computing · Optical Wireless Communication Technologies

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

Affiliations

Department of Physics Institute of Physics Budapest University of Technology and Economics Műegyetem rkp. 3 Budapest H‐1111 Hungary

HUN‐REN‐BME Condensed Matter Research Group Budapest University of Technology and Economics Műegyetem rkp. 3 Budapest H‐1111 Hungary

Institute of Technical Physics and Materials Science HUN‐REN Centre for Energy Research Konkoly‐Thege M. út 29‐33 Budapest H‐1121 Hungary

Institute of Electromagnetic Fields ETH Zurich Gloriastrasse 35 Zurich 8092 Switzerland

Experimental Physics V Center for Electronic Correlations and Magnetism University of Augsburg Universitätsstrasse 2 86135 Augsburg Germany

Emerson ‐ Test and Measurement (NI) Hungária körút 30/A Budapest H‐1087 Hungary

Naval Research Laboratory 4555 Overlook Ave Washington DC 20375 USA

Funding

National Research, Development and Innovation Office · Magyar Tudományos Akadémia · Werner Siemens-Stiftung

References (41)

Show source-provided references
1. J.vonNeumann Non‐linear capacitance or inductance switching amplifying and memory organs 1957 US Patent 2 815 488.
2. 10.1109/JRPROC.1959.28731110.1109/JRPROC.1959.287311 ↗
3. 10.1038/s44335-024-00015-z10.1038/s44335-024-00015-z ↗
4. 10.1038/s41467-020-18445-110.1038/s41467-020-18445-1 ↗
5. 10.1103/PhysRevResearch.6.02316210.1103/PhysRevResearch.6.023162 ↗
6. 10.1109/JSSC.2021.306282110.1109/JSSC.2021.3062821 ↗
7. 10.1038/s41598-023-31155-010.1038/s41598-023-31155-0 ↗
8. 10.1007/s11047-021-09845-310.1007/s11047-021-09845-3 ↗
9. 10.1109/JPROC.2018.287885410.1109/JPROC.2018.2878854 ↗
10. B.Datta Sahoo in2017 IEEE International Symposium on Circuits and Systems (ISCAS).2017 pp.1–4.
11. 10.1063/1.512041210.1063/1.5120412 ↗
12. Chen P. · Adv. Funct. Mater.
13. 10.1021/acsami.4c1295610.1021/acsami.4c12956 ↗
14. 10.1063/1.492174510.1063/1.4921745 ↗
15. 10.1021/acs.nanolett.9b0155410.1021/acs.nanolett.9b01554 ↗
16. 10.1038/s41467-018-07052-w10.1038/s41467-018-07052-w ↗
17. 10.1038/srep0496410.1038/srep04964 ↗
18. 10.1038/s41467-024-47642-510.1038/s41467-024-47642-5 ↗
19. 10.1038/s41928-021-00616-710.1038/s41928-021-00616-7 ↗
20. 10.1038/s42254-022-00440-810.1038/s42254-022-00440-8 ↗
21. 10.1038/s41467-024-45992-810.1038/s41467-024-45992-8 ↗
22. 10.1038/s41467-022-31747-w10.1038/s41467-022-31747-w ↗
23. 10.3389/fnins.2021.62825410.3389/fnins.2021.628254 ↗
24. 10.1109/LED.2020.297200610.1109/LED.2020.2972006 ↗
25. 10.1109/TNNLS.2023.323847310.1109/TNNLS.2023.3238473 ↗
26. 10.1063/1.492212210.1063/1.4922122 ↗
27. 10.1038/s41467-024-49925-310.1038/s41467-024-49925-3 ↗
28. 10.1109/TED.2015.247562310.1109/TED.2015.2475623 ↗
29. 10.1021/acsanm.3c0015010.1021/acsanm.3c00150 ↗
30. 10.1088/2634-4386/acf2bf10.1088/2634-4386/acf2bf ↗
31. 10.1021/acsnano.4c0384010.1021/acsnano.4c03840 ↗
32. 10.1109/MEMC.0.754395010.1109/MEMC.0.7543950 ↗
33. 10.1002/aelm.20220110410.1002/aelm.202201104 ↗
34. 10.1103/PhysRevApplied.10.05400110.1103/PhysRevApplied.10.054001 ↗
35. 10.1038/s41586-019-1159-610.1038/s41586-019-1159-6 ↗
36. 10.1126/science.abd908810.1126/science.abd9088 ↗
37. 10.1063/1.500412510.1063/1.5004125 ↗
38. 10.1002/admi.20170081010.1002/admi.201700810 ↗
39. 10.1063/1.486680610.1063/1.4866806 ↗
40. 10.1016/j.tsf.2015.07.06210.1016/j.tsf.2015.07.062 ↗
41. 10.1109/TCSI.2015.245233210.1109/TCSI.2015.2452332 ↗