Inhibitory neuristor based on metal-to-insulator transition
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arXiv
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| Format: | Preprint |
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2026
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| author | Palin, Victor Agnihotri, Akash Ghazikhanian, Nareg Frame, Matthew Takamura, Yayoi Schuller, Ivan K. Salev, Pavel |
| author_facet | Palin, Victor Agnihotri, Akash Ghazikhanian, Nareg Frame, Matthew Takamura, Yayoi Schuller, Ivan K. Salev, Pavel |
| contents | Mimicking the collective excitatory and inhibitory behaviors of biological neurons remains a critical challenge in the development of neuromorphic computing systems that rival the complexity and performance of the human brain. Volatile high-to-low resistance switching in insulator-to-metal transition (IMT) materials produces an abrupt increase in current flow, resembling neuronal excitation. This electrical excitation enables IMT materials to be driven into a neuron-like spiking self-oscillation regime using simple RC circuits. Here, we report a new type of self-oscillation dynamics that occurs in the opposite class of metal-to-insulator transition (MIT) materials. Electrical triggering of the MIT suppresses current flow, resembling neuronal inhibition. Using a prototypical MIT material, we experimentally demonstrate inhibitory-like self-oscillations in two-terminal switching devices incorporated into a simple RL circuit. Our results show robust ~0.1 - 1 MHz electric current oscillations with minimal cycle-to-cycle variation, which can be controlled by varying the applied DC voltage, temperature, and inductance. This work demonstrates a new type of inhibitory MIT-based artificial neuron that can complement the excitatory functionalities of IMT-based neuristors in biologically plausible neuromorphic systems. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2604_19951 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | Inhibitory neuristor based on metal-to-insulator transition Palin, Victor Agnihotri, Akash Ghazikhanian, Nareg Frame, Matthew Takamura, Yayoi Schuller, Ivan K. Salev, Pavel Materials Science Strongly Correlated Electrons Mimicking the collective excitatory and inhibitory behaviors of biological neurons remains a critical challenge in the development of neuromorphic computing systems that rival the complexity and performance of the human brain. Volatile high-to-low resistance switching in insulator-to-metal transition (IMT) materials produces an abrupt increase in current flow, resembling neuronal excitation. This electrical excitation enables IMT materials to be driven into a neuron-like spiking self-oscillation regime using simple RC circuits. Here, we report a new type of self-oscillation dynamics that occurs in the opposite class of metal-to-insulator transition (MIT) materials. Electrical triggering of the MIT suppresses current flow, resembling neuronal inhibition. Using a prototypical MIT material, we experimentally demonstrate inhibitory-like self-oscillations in two-terminal switching devices incorporated into a simple RL circuit. Our results show robust ~0.1 - 1 MHz electric current oscillations with minimal cycle-to-cycle variation, which can be controlled by varying the applied DC voltage, temperature, and inductance. This work demonstrates a new type of inhibitory MIT-based artificial neuron that can complement the excitatory functionalities of IMT-based neuristors in biologically plausible neuromorphic systems. |
| title | Inhibitory neuristor based on metal-to-insulator transition |
| topic | Materials Science Strongly Correlated Electrons |
| url | https://arxiv.org/abs/2604.19951 |