Gate-Programmable Ozone Adsorption Gradients for Reconfigurable and Low-Power Palladium Diselenide Electronics.
Fei Xie1, Wei Luo1, Wanqian Wang1
1College of Science and Hunan Research Center of the Basic Discipline for Physical States, National University of Defense Technology, Changsha, Hunan 410073, P. R. China.
ACS Applied Materials & Interfaces
|October 16, 2025
Summary
Researchers developed a new gate-controlled ozone strategy to reconfigure palladium diselenide (PdSe2) devices. This method enables programmable logic inverters and artificial synapses with ultralow voltage and energy consumption for advanced electronics.
Area of Science:
- Materials Science
- Nanotechnology
- Electronics Engineering
Background:
- Reconfigurable two-dimensional (2D) devices offer adaptive functionality for next-generation electronics.
- Achieving nondestructive, programmable reconfiguration in 2D transistors is a significant challenge.
Purpose of the Study:
- To introduce a gate-controlled graded ozone (O3) strategy for dynamically reconfiguring palladium diselenide (PdSe2) devices.
- To demonstrate programmable logic inverters and artificial synapses using this O3-mediated approach.
Main Methods:
- Utilized a gate-controlled graded ozone (O3) adsorption strategy on PdSe2 devices.
- Performed systematic characterization to confirm nondestructive O3 adsorption and controllable hole doping via surface charge transfer.
- Integrated the reconfigured PdSe2 devices into complementary logic inverters and artificial synapses.
Main Results:
- Confirmed the nondestructive nature of O3 adsorption on PdSe2.
- Achieved controllable hole doping through surface charge transfer modulation, creating a graded doping profile.
- Demonstrated ultralow voltage operation (0.05 V) in PdSe2-based complementary inverters.
- Exhibited metaplasticity in artificial synapses with ultralow energy consumption (0.35 fJ per synaptic event).
Conclusions:
- The O3-mediated reconfiguration strategy provides a versatile platform for multifunctional 2D electronics.
- This approach enables adaptive neuromorphic computing applications.
- The demonstrated ultralow voltage and energy efficiency highlight the potential for advanced electronic devices.
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