Exploiting Spatial Ionic Dynamics in Solid‐State Organic Electrochemical Transistors for Multi‐Tactile Sensing and Processing
The human nervous system inspires the next generation of sensory and communication systems for robotics, human-machine interfaces (HMIs), biomedical applications, and artificial intelligence. Neuromorphic approaches address processing challenges; however, the vast number of sensors and their large-scale distribution complicate analog data manipulation. Conventional digital multiplexers are limited by complex circuit architecture and high supply voltage. Large sensory arrays further complicate wiring. An 'in-electrolyte computing' platform is presented by integrating organic electrochemical transistors (OECTs) with a solid-state polymer electrolyte. These devices use synapse-like signal transport and spatially dependent bulk ionic doping, achieving over 400 times modulation in channel conductance, allowing discrimination of locally random-access events without peripheral circuitry or address assignment. It demonstrates information processing from 12 tactile sensors with a single OECT output, showing clear advantages in circuit simplicity over existing all-electronic, all-digital implementations. This self-multiplexer platform offers exciting prospects for circuit-free integration with sensory arrays for high-quality, large-volume analog signal processing.
Authors
- Nripan Mathews (ORCID: https://orcid.org/0000-0001-5234-0822)
- Wen Siang Lew (ORCID: https://orcid.org/0000-0002-5161-741X)
- Kunqi Hou
- Wei Lin Leong (ORCID: https://orcid.org/0000-0002-1402-0083)
- Rohit Abraham John (ORCID: https://orcid.org/0000-0002-1709-0386)
- Shuai Chen (ORCID: https://orcid.org/0000-0002-8562-5784)
- Qiang He (ORCID: https://orcid.org/0000-0002-3555-1852)
- Zhongliang Zhou (ORCID: https://orcid.org/0000-0001-6455-2363)
Institutions
- Nanyang Technological University (SG)
- ETH Zurich (CH)
Publication Details
- Journal
- Advanced Science
- Published
- 2024-09-27
- DOI
- https://doi.org/10.1002/advs.202405902
- Citations
- 6
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 1.25
Funders
- Delta Electronics
- Agency for Science, Technology and Research
- Ministry of Education, India
- Kementerian Pendidikan