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.

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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
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article

Selective UV Sensing for Energy‐Efficient UV‐A Artificial Synapses Using a ZnO/ZnGa2O4 Heterojunction Diode

Taslim Khan, Rajendra Singh, Sazid Ali, Ray‐Hua Horng et al.
16 citations
Small
Advanced Memory and Neural Computing
11.69
article

Selective UV Sensing for Energy‐Efficient UV‐A Artificial Synapses Using a ZnO/ZnGa2O4 Heterojunction Diode

Taslim Khan, Rajendra Singh, Sazid Ali, Ray‐Hua Horng, Santanu Kandar, Pushpapraj Singh
article en
16 citations

Abstract

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.

SmallVol. 21(16)
National Yang Ming Chiao Tung University (TW), Indian Institute of Technology Delhi (IN)
Affordable and clean energy
Openalex Percentile: Top 1%
Advanced Memory and Neural Computing
11.69
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Selective UV Sensing for Energy‐Efficient UV‐A Artificial Synapses Using a ZnO/ZnGa<sub>2</sub>O<sub>4</sub> Heterojunction Diode — Taslim Khan, Rajendra Singh, et al. · Small (2025) | TGRS Research Map | TGRS