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Published on: May 13, 2020
Tailoring resistive switching in ultra-thin tellurium films by interface engineering
Sara Ghomi1, Carlo Grazianetti1, Andrea Serafini2
1CNR IMM, Unit of Agrate Brianza, via C. Olivetti 2, Agrate Brianza 20864, Italy. christian.martella@cnr.it.
Interface engineering significantly enhances resistive switching (RS) performance in memristive devices. Optimizing the interface between nanoscaled tellurium and reconstructed gold substrates reduces switching voltages for improved neuromorphic computing applications.
Area of Science:
- Materials Science
- Nanotechnology
- Solid State Physics
Background:
- Resistive switching (RS) materials are crucial for neuromorphic and in-memory computing.
- The role of interfaces between active materials and metallic electrodes in RS is often overlooked.
- Scalable, low-temperature growth of active materials on metallic substrates is vital for device fabrication.
Purpose of the Study:
- To investigate the impact of gold substrate surface reconstruction on the resistive switching properties of nanoscaled tellurium.
- To explore interface engineering strategies for improving memristive device performance.
- To demonstrate the importance of electrode-material interfaces in device functionality.
Main Methods:
- Vapour transport deposition of tellurium on Au(111) substrates at 100 °C.
- Utilizing conductive atomic force microscopy (C-AFM) to probe resistive switching characteristics.
- Comparing RS performance on reconstructed and un-reconstructed Au(111) surfaces.
Main Results:
- Tellurium grown on reconstructed Au(111) exhibited improved resistive switching.
- Nanoscaled tellurium morphology was influenced by the gold surface reconstruction.
- Reduced set and reset voltages were observed on the reconstructed surface compared to the un-reconstructed surface.
Conclusions:
- Surface reconstruction of metallic substrates plays a critical role in the resistive switching performance of deposited nanomaterials.
- Interface engineering is as important as material selection for optimizing memristive devices.
- These findings offer a pathway for developing high-performance, scalable memristive devices.
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