Selective UV Sensing for Energy‐Efficient UV‐A Artificial Synapses Using a ZnO/ZnGa<sub>2</sub>O<sub>4</sub> Heterojunction Diode
As neuromorphic computing systems, which allow for parallel data storage and processing with high area and energy efficiency, show great potential for future storage and in-memory computing technologies. In this article, a high-performance UV detector for artificial optical synapse applications is demonstrated that can selectively detect UV-A and UV-C, with a responsivity of 407 A W<sup>-1</sup>. The pyrophototronic effect increases photocurrent dramatically under UV-A irradiation due to heat accumulation in the ZnO layer and ZnGa<sub>2</sub>O<sub>4</sub>'s low thermal conductivity. In context of synaptic device, it's shown that a ZnO/ZnGa<sub>2</sub>O<sub>4</sub> heterostructure can be used as a light-tunable charge trapping medium to create an electro-photoactive synapse. The photogating effect enables via pyrophototronic, which traps photogenerated electrons within the ZnO/ZnGa<sub>2</sub>O<sub>4</sub> interface, and drives synaptic activity, as proven by electrical techniques based on UV-A stimuli. This phenomenon results in a selective detection capability for UV-A over UV-C. Thermally produced pyrophototronic effect synaptic plasticity, simulating biological synapse activity. Persistent photoconductivity under 380 (UV-A) nm UV light mimics synaptic processes, with low thermal conductivity enhancing synaptic weight updates during learning and forgetting. These findings show the possibility of using ZnO/ZnGa<sub>2</sub>O<sub>4</sub> heterostructures into artificial optoelectronic synapse systems controlled by thermal dynamics.
Authors
- Taslim Khan (ORCID: https://orcid.org/0009-0007-5120-8505)
- Rajendra Singh (ORCID: https://orcid.org/0000-0002-6890-6904)
- Sazid Ali
- Ray‐Hua Horng (ORCID: https://orcid.org/0000-0002-1160-6775)
- Santanu Kandar (ORCID: https://orcid.org/0009-0009-4670-5499)
- Pushpapraj Singh
Institutions
- National Yang Ming Chiao Tung University (TW)
- Indian Institute of Technology Delhi (IN)
Publication Details
- Journal
- Small
- Published
- 2025-03-05
- DOI
- https://doi.org/10.1002/smll.202500098
- Citations
- 16
- Primary Topic
- Advanced Memory and Neural Computing
- Type
- article
- Field-Weighted Citation Impact
- 11.69