SOMA: A Single-Material Organic Multivibrator Adaptive Neuron for Fully Integrated PEDOT:PSS Neuromorphic Systems
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arXiv
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| Format: | Preprint |
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2026
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| _version_ | 1866908965798936576 |
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| author | Prudnikov, Nikita Yoon, Yeohoon Kleemann, Hans |
| author_facet | Prudnikov, Nikita Yoon, Yeohoon Kleemann, Hans |
| contents | Neuromorphic electronics and spiking neural networks (SNNs) offer energy-efficient data processing, essential for real-time and edge-computing applications. In particular, interfacing and processing biological signals require devices that combine electronic performance with ionic sensitivity, which are capabilities uniquely provided by organic electrochemical transistors (OECTs). However, realizing a simple, fully integrated OECT-based neuron with rich dynamics and adaptability remains challenging. Most reported implementations rely on current-driven operation, which complicates large-scale integration and neuron-neuron coupling due to the need for precise matching of operating currents and bias voltages. Here we present a voltage-driven neuron circuit based on a multivibrator oscillator architecture, entirely fabricated from poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS). The neuron exhibits tunable adaptability through an additional control input, enabling switching between burst latency and length encoding modes. We further demonstrate a hardware-implemented two-neuron unit consisting of an inhibitory and a readout neuron, where readout activity is suppressed depending on the relative timing of the inhibitory input. Finally, we demonstrate that the fabrication process is compatible with polymer dendrite growth, enabling on-chip integration of synaptic elements on the same substrate. Owing to its structural simplicity and compatibility with a single, available material, this approach offers a scalable and accessible route toward integrated OECT-based SNNs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2603_20954 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | SOMA: A Single-Material Organic Multivibrator Adaptive Neuron for Fully Integrated PEDOT:PSS Neuromorphic Systems Prudnikov, Nikita Yoon, Yeohoon Kleemann, Hans Applied Physics Neuromorphic electronics and spiking neural networks (SNNs) offer energy-efficient data processing, essential for real-time and edge-computing applications. In particular, interfacing and processing biological signals require devices that combine electronic performance with ionic sensitivity, which are capabilities uniquely provided by organic electrochemical transistors (OECTs). However, realizing a simple, fully integrated OECT-based neuron with rich dynamics and adaptability remains challenging. Most reported implementations rely on current-driven operation, which complicates large-scale integration and neuron-neuron coupling due to the need for precise matching of operating currents and bias voltages. Here we present a voltage-driven neuron circuit based on a multivibrator oscillator architecture, entirely fabricated from poly(3,4-ethylenedioxythiophene):polystyrene sulfonate (PEDOT:PSS). The neuron exhibits tunable adaptability through an additional control input, enabling switching between burst latency and length encoding modes. We further demonstrate a hardware-implemented two-neuron unit consisting of an inhibitory and a readout neuron, where readout activity is suppressed depending on the relative timing of the inhibitory input. Finally, we demonstrate that the fabrication process is compatible with polymer dendrite growth, enabling on-chip integration of synaptic elements on the same substrate. Owing to its structural simplicity and compatibility with a single, available material, this approach offers a scalable and accessible route toward integrated OECT-based SNNs. |
| title | SOMA: A Single-Material Organic Multivibrator Adaptive Neuron for Fully Integrated PEDOT:PSS Neuromorphic Systems |
| topic | Applied Physics |
| url | https://arxiv.org/abs/2603.20954 |