A Three‐Terminal Memristive Artificial Neuron with Tunable Firing Probability
Abstract The human brain facilitates information processing via generating and receiving temporal patterns of short voltage pulses, a.k.a. neural spikes. This approach simultaneously grants low‐power operation as well as a high degree of noise immunity and fault tolerance at a small footprint and si...
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| Format: | Article |
| Language: | English |
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Wiley-VCH
2024-12-01
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| Series: | Advanced Electronic Materials |
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| Online Access: | https://doi.org/10.1002/aelm.202400432 |
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| author | Mila Lewerenz Elias Passerini Luca Weber Markus Fischer Nadia Jimenez Olalla Raphael Gisler Alexandros Emboras Mathieu Luisier Miklos Csontos Ueli Koch Juerg Leuthold |
| author_facet | Mila Lewerenz Elias Passerini Luca Weber Markus Fischer Nadia Jimenez Olalla Raphael Gisler Alexandros Emboras Mathieu Luisier Miklos Csontos Ueli Koch Juerg Leuthold |
| author_sort | Mila Lewerenz |
| collection | DOAJ |
| description | Abstract The human brain facilitates information processing via generating and receiving temporal patterns of short voltage pulses, a.k.a. neural spikes. This approach simultaneously grants low‐power operation as well as a high degree of noise immunity and fault tolerance at a small footprint and simplistic structure of the neurons. To date, the latter two key features are critically missing from the toolbox of artificial spiking neural network hardware, hindering the development of scalable and sustainable artificial intelligence (AI) platforms. Here, a compact, gate‐tunable neuron circuit is demonstrated, and its potential as a functional leaky integrate‐and‐fire (LIF) neuron is explored. It relies on a single nanoscale three‐terminal (3T) memristor device, which has been downscaled by 30% compared to previous work, where the set voltage and, thereby, the spiking probability of the neuron circuit can be widely tuned by the low‐voltage operation of the gate electrode. The influence of the gate voltage on the two‐terminal (2T) current–voltage characteristics is measured, statistically analyzed, and further utilized in a custom‐built LTspice model. The circuit simulations account for the experimentally observed, adjustable set voltage. The presented results demonstrate the merits of 3T memristors as compact, tunable, and versatile artificial neurons for neuromorphic computing applications. |
| format | Article |
| id | doaj-art-05c50df911594dbca77baa8224167707 |
| institution | Kabale University |
| issn | 2199-160X |
| language | English |
| publishDate | 2024-12-01 |
| publisher | Wiley-VCH |
| record_format | Article |
| series | Advanced Electronic Materials |
| spelling | doaj-art-05c50df911594dbca77baa82241677072025-01-09T11:51:13ZengWiley-VCHAdvanced Electronic Materials2199-160X2024-12-011012n/an/a10.1002/aelm.202400432A Three‐Terminal Memristive Artificial Neuron with Tunable Firing ProbabilityMila Lewerenz0Elias Passerini1Luca Weber2Markus Fischer3Nadia Jimenez Olalla4Raphael Gisler5Alexandros Emboras6Mathieu Luisier7Miklos Csontos8Ueli Koch9Juerg Leuthold10Institute of Electromagnetic Fields (IEF) ETHZ Zürich 8092 SwitzerlandInstitute of Electromagnetic Fields (IEF) ETHZ Zürich 8092 SwitzerlandInstitute of Electromagnetic Fields (IEF) ETHZ Zürich 8092 SwitzerlandInstitute of Electromagnetic Fields (IEF) ETHZ Zürich 8092 SwitzerlandInstitute of Electromagnetic Fields (IEF) ETHZ Zürich 8092 SwitzerlandInstitute of Electromagnetic Fields (IEF) ETHZ Zürich 8092 SwitzerlandIntegrated Systems Laboratory (IIS) ETHZ Zürich 8092 SwitzerlandIntegrated Systems Laboratory (IIS) ETHZ Zürich 8092 SwitzerlandInstitute of Electromagnetic Fields (IEF) ETHZ Zürich 8092 SwitzerlandInstitute of Electromagnetic Fields (IEF) ETHZ Zürich 8092 SwitzerlandInstitute of Electromagnetic Fields (IEF) ETHZ Zürich 8092 SwitzerlandAbstract The human brain facilitates information processing via generating and receiving temporal patterns of short voltage pulses, a.k.a. neural spikes. This approach simultaneously grants low‐power operation as well as a high degree of noise immunity and fault tolerance at a small footprint and simplistic structure of the neurons. To date, the latter two key features are critically missing from the toolbox of artificial spiking neural network hardware, hindering the development of scalable and sustainable artificial intelligence (AI) platforms. Here, a compact, gate‐tunable neuron circuit is demonstrated, and its potential as a functional leaky integrate‐and‐fire (LIF) neuron is explored. It relies on a single nanoscale three‐terminal (3T) memristor device, which has been downscaled by 30% compared to previous work, where the set voltage and, thereby, the spiking probability of the neuron circuit can be widely tuned by the low‐voltage operation of the gate electrode. The influence of the gate voltage on the two‐terminal (2T) current–voltage characteristics is measured, statistically analyzed, and further utilized in a custom‐built LTspice model. The circuit simulations account for the experimentally observed, adjustable set voltage. The presented results demonstrate the merits of 3T memristors as compact, tunable, and versatile artificial neurons for neuromorphic computing applications.https://doi.org/10.1002/aelm.202400432electrochemical metallization cellleaky‐integrate‐and‐firememristorsthree‐terminaltunable |
| spellingShingle | Mila Lewerenz Elias Passerini Luca Weber Markus Fischer Nadia Jimenez Olalla Raphael Gisler Alexandros Emboras Mathieu Luisier Miklos Csontos Ueli Koch Juerg Leuthold A Three‐Terminal Memristive Artificial Neuron with Tunable Firing Probability Advanced Electronic Materials electrochemical metallization cell leaky‐integrate‐and‐fire memristors three‐terminal tunable |
| title | A Three‐Terminal Memristive Artificial Neuron with Tunable Firing Probability |
| title_full | A Three‐Terminal Memristive Artificial Neuron with Tunable Firing Probability |
| title_fullStr | A Three‐Terminal Memristive Artificial Neuron with Tunable Firing Probability |
| title_full_unstemmed | A Three‐Terminal Memristive Artificial Neuron with Tunable Firing Probability |
| title_short | A Three‐Terminal Memristive Artificial Neuron with Tunable Firing Probability |
| title_sort | three terminal memristive artificial neuron with tunable firing probability |
| topic | electrochemical metallization cell leaky‐integrate‐and‐fire memristors three‐terminal tunable |
| url | https://doi.org/10.1002/aelm.202400432 |
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