Monolithically Integrated VO$_2$ Mott Oscillators for Energy-Efficient Spiking Neurons
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| Auteurs principaux: | , , , , , , , , |
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| Format: | Preprint |
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2026
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| _version_ | 1866911618364866560 |
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| author | Bersano, Fabio Masserey, Cyrille Conti, Vanessa Iaconeta, Andrea Martinolli, Niccolo' Ansari, Ehsan Varini, Anna Stolichnov, Igor Ionescu, Adrian Mihai |
| author_facet | Bersano, Fabio Masserey, Cyrille Conti, Vanessa Iaconeta, Andrea Martinolli, Niccolo' Ansari, Ehsan Varini, Anna Stolichnov, Igor Ionescu, Adrian Mihai |
| contents | Brain-inspired non-Boolean computing offers intrinsic error tolerance and parallelism, but its practical deployment is limited by the lack of compact, energy-efficient spiking hardware compatible with large-scale integration. Mott phase-transition materials provide a promising route, as their abrupt insulator-to-metal transitions enable neuron-like thresholding and oscillatory dynamics in compact devices. Among these, vanadium dioxide (VO$_2$) stands out for its near-room-temperature transition, fast switching, and scalability. However, existing VO$_2$-based neuristors rely on discrete components, limiting integration density and system applicability. Here, we report monolithic back-end-of-the-line (BEOL) integration of one-transistor-one-VO2-memristor (1T-1MR) spiking neurons on CMOS-compatible platforms. VO$_2$ nanosheet devices are fabricated by pulsed-laser deposition below 430 °C on dielectrically isolated silicon-on-insulator (SOI) p-type junctionless field-effect transistors (JLFETs) in a compact 1T-1MR configuration. The architecture exhibits gate-tunable oscillations from 40 to 410 kHz in 60 nm-thick VO$_2$ devices with an active area of 6 $μ$m$^2$, achieving energy consumption as low as 18 pJ per spike at room temperature, with memristor power dissipation of 8 $μ$W and potential scaling toward sub-3 $μ$W operation. We further uncover a non-monotonic dependence of oscillation frequency on current and temperature, along with bias-dependent stochastic firing dynamics, highlighting the rich behavior of integrated VO$_2$ memristor systems. Finally, we demonstrate voltage-controlled oscillator functionality and actively tunable resistive coupling of two nano-oscillators mediated by a JLFET. These results establish a pathway toward dense, energy-efficient, and monolithically integrated Mott-based neuromorphic hardware compatible with CMOS technology. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_21487 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Monolithically Integrated VO$_2$ Mott Oscillators for Energy-Efficient Spiking Neurons Bersano, Fabio Masserey, Cyrille Conti, Vanessa Iaconeta, Andrea Martinolli, Niccolo' Ansari, Ehsan Varini, Anna Stolichnov, Igor Ionescu, Adrian Mihai Systems and Control Materials Science Brain-inspired non-Boolean computing offers intrinsic error tolerance and parallelism, but its practical deployment is limited by the lack of compact, energy-efficient spiking hardware compatible with large-scale integration. Mott phase-transition materials provide a promising route, as their abrupt insulator-to-metal transitions enable neuron-like thresholding and oscillatory dynamics in compact devices. Among these, vanadium dioxide (VO$_2$) stands out for its near-room-temperature transition, fast switching, and scalability. However, existing VO$_2$-based neuristors rely on discrete components, limiting integration density and system applicability. Here, we report monolithic back-end-of-the-line (BEOL) integration of one-transistor-one-VO2-memristor (1T-1MR) spiking neurons on CMOS-compatible platforms. VO$_2$ nanosheet devices are fabricated by pulsed-laser deposition below 430 °C on dielectrically isolated silicon-on-insulator (SOI) p-type junctionless field-effect transistors (JLFETs) in a compact 1T-1MR configuration. The architecture exhibits gate-tunable oscillations from 40 to 410 kHz in 60 nm-thick VO$_2$ devices with an active area of 6 $μ$m$^2$, achieving energy consumption as low as 18 pJ per spike at room temperature, with memristor power dissipation of 8 $μ$W and potential scaling toward sub-3 $μ$W operation. We further uncover a non-monotonic dependence of oscillation frequency on current and temperature, along with bias-dependent stochastic firing dynamics, highlighting the rich behavior of integrated VO$_2$ memristor systems. Finally, we demonstrate voltage-controlled oscillator functionality and actively tunable resistive coupling of two nano-oscillators mediated by a JLFET. These results establish a pathway toward dense, energy-efficient, and monolithically integrated Mott-based neuromorphic hardware compatible with CMOS technology. |
| title | Monolithically Integrated VO$_2$ Mott Oscillators for Energy-Efficient Spiking Neurons |
| topic | Systems and Control Materials Science |
| url | https://arxiv.org/abs/2604.21487 |