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Multilevel storage and linear optoelectronic response in mixed-dimensional photomemories
Chen-Yo Tsai1, Dun-Jie Jhan2, Che-Ming Wu2
1College of Semiconductor Research, National Tsing Hua University, Hsinchu 300, Taiwan. mylu@mx.nthu.edu.tw.
Nanoscale Horizons
|September 18, 2025
Summary
We developed a novel perovskite quantum dot photomemory device for AI computing. It achieves efficient, low-energy data storage by optimizing a mixed-dimensional architecture.
Area of Science:
- Materials Science
- Nanotechnology
- Optoelectronics
Background:
- AI computing requires advanced memory solutions for speed and energy efficiency.
- Existing technologies face challenges in integrating processing and storage.
Purpose of the Study:
- To develop a mixed-dimensional photomemory device using perovskite quantum dots (PQDs).
- To optimize device architecture for energy-efficient data storage in AI applications.
Main Methods:
- Fabrication of a CsPbBr3/Al2O3/MoS2 device architecture.
- Optical characterization: photoluminescence (PL), time-resolved PL.
- Electrical characterization: Kelvin probe force microscopy (KPFM), current-voltage (I-V) measurements.
Main Results:
- Optimized Al2O3 dielectric layer (5.5 nm) enabled precise charge transfer control.
- Achieved low-energy (sub-pJ) storage of single positive charges in PQDs.
- Demonstrated high on/off ratio, multilevel storage, and linear photocurrent response.
Conclusions:
- The PQD-based photomemory device offers a robust platform for next-generation AI hardware.
- Optimized interfacial effects and dielectric thickness are key for high-performance optoelectronics.
- This work provides insights into energy-efficient, high-performance optoelectronic systems for AI.
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