Magnetic tunnel junctions driven by hybrid optical-electrical signals as a flexible neuromorphic computing platform
Abstract Magnetic tunnel junctions (MTJs) offer a promising pathway toward energy-efficient neuromorphic computing due to their nanoscale footprint, nonvolatile switching, and intrinsic nonlinear dynamics that emulate synaptic behavior. However, generating large thermoelectric voltages with bias-tun...
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| Format: | Article |
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Nature Portfolio
2025-08-01
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| Series: | Communications Physics |
| Online Access: | https://doi.org/10.1038/s42005-025-02257-0 |
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| author | Felix Oberbauer Tristan Joachim Winkel Tim Böhnert Clara C. Wanjura Marcel S. Claro Luana Benetti Ihsan Çaha Francis Leonard Deepak Farshad Moradi Ricardo Ferreira Markus Münzenberg Tahereh Sadat Parvini |
| author_facet | Felix Oberbauer Tristan Joachim Winkel Tim Böhnert Clara C. Wanjura Marcel S. Claro Luana Benetti Ihsan Çaha Francis Leonard Deepak Farshad Moradi Ricardo Ferreira Markus Münzenberg Tahereh Sadat Parvini |
| author_sort | Felix Oberbauer |
| collection | DOAJ |
| description | Abstract Magnetic tunnel junctions (MTJs) offer a promising pathway toward energy-efficient neuromorphic computing due to their nanoscale footprint, nonvolatile switching, and intrinsic nonlinear dynamics that emulate synaptic behavior. However, generating large thermoelectric voltages with bias-tunable nonlinearities for neuromorphic use remains largely unexplored. Here, we introduce a hybrid opto-electrical excitation scheme—combining pulsed laser heating with DC bias—to drive MTJs into the nonlinear bias-enhanced tunnel magneto-Seebeck regime. This regime yields thermoelectric voltages in the tens of millivolts with a strong contrast between magnetic states, while also revealing spiking and double-switching behavior linked to vortex dynamics and fixed-layer depinning. The thermovoltage exhibits cubic dependence on bias current, enabling tunable synaptic weights. We simulate a single-layer neuromorphic network using optically encoded inputs and achieve 93.7% classification accuracy on handwritten digits. These results establish hybrid-driven MTJs as a compact, CMOS-compatible platform for neuromorphic computing, integrating optical input with spintronic functionality. |
| format | Article |
| id | doaj-art-32a82555e2eb4735ab723f0faf43f3a7 |
| institution | Kabale University |
| issn | 2399-3650 |
| language | English |
| publishDate | 2025-08-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Communications Physics |
| spelling | doaj-art-32a82555e2eb4735ab723f0faf43f3a72025-08-20T03:45:57ZengNature PortfolioCommunications Physics2399-36502025-08-01811910.1038/s42005-025-02257-0Magnetic tunnel junctions driven by hybrid optical-electrical signals as a flexible neuromorphic computing platformFelix Oberbauer0Tristan Joachim Winkel1Tim Böhnert2Clara C. Wanjura3Marcel S. Claro4Luana Benetti5Ihsan Çaha6Francis Leonard Deepak7Farshad Moradi8Ricardo Ferreira9Markus Münzenberg10Tahereh Sadat Parvini11Institut für Physik, Universität GreifswaldInstitut für Physik, Universität GreifswaldINL - International Iberian Nanotechnology LaboratoryMax Planck Institute for the Science of LightINL - International Iberian Nanotechnology LaboratoryINL - International Iberian Nanotechnology LaboratoryINL - International Iberian Nanotechnology LaboratoryINL - International Iberian Nanotechnology LaboratoryElectrical and Computer Engineering Department, Aarhus UniversityINL - International Iberian Nanotechnology LaboratoryInstitut für Physik, Universität GreifswaldInstitut für Physik, Universität GreifswaldAbstract Magnetic tunnel junctions (MTJs) offer a promising pathway toward energy-efficient neuromorphic computing due to their nanoscale footprint, nonvolatile switching, and intrinsic nonlinear dynamics that emulate synaptic behavior. However, generating large thermoelectric voltages with bias-tunable nonlinearities for neuromorphic use remains largely unexplored. Here, we introduce a hybrid opto-electrical excitation scheme—combining pulsed laser heating with DC bias—to drive MTJs into the nonlinear bias-enhanced tunnel magneto-Seebeck regime. This regime yields thermoelectric voltages in the tens of millivolts with a strong contrast between magnetic states, while also revealing spiking and double-switching behavior linked to vortex dynamics and fixed-layer depinning. The thermovoltage exhibits cubic dependence on bias current, enabling tunable synaptic weights. We simulate a single-layer neuromorphic network using optically encoded inputs and achieve 93.7% classification accuracy on handwritten digits. These results establish hybrid-driven MTJs as a compact, CMOS-compatible platform for neuromorphic computing, integrating optical input with spintronic functionality.https://doi.org/10.1038/s42005-025-02257-0 |
| spellingShingle | Felix Oberbauer Tristan Joachim Winkel Tim Böhnert Clara C. Wanjura Marcel S. Claro Luana Benetti Ihsan Çaha Francis Leonard Deepak Farshad Moradi Ricardo Ferreira Markus Münzenberg Tahereh Sadat Parvini Magnetic tunnel junctions driven by hybrid optical-electrical signals as a flexible neuromorphic computing platform Communications Physics |
| title | Magnetic tunnel junctions driven by hybrid optical-electrical signals as a flexible neuromorphic computing platform |
| title_full | Magnetic tunnel junctions driven by hybrid optical-electrical signals as a flexible neuromorphic computing platform |
| title_fullStr | Magnetic tunnel junctions driven by hybrid optical-electrical signals as a flexible neuromorphic computing platform |
| title_full_unstemmed | Magnetic tunnel junctions driven by hybrid optical-electrical signals as a flexible neuromorphic computing platform |
| title_short | Magnetic tunnel junctions driven by hybrid optical-electrical signals as a flexible neuromorphic computing platform |
| title_sort | magnetic tunnel junctions driven by hybrid optical electrical signals as a flexible neuromorphic computing platform |
| url | https://doi.org/10.1038/s42005-025-02257-0 |
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