Controlled crystallization of thermal evaporated GST-on-SOI for photonic neuromorphic application
Neuromorphic computing is inevitable in addressing the computing challenges faced by the current computing architecture. A nonvolatile process is one of the key elements in realizing a neuromorphic architecture. Realization of a photonic nonvolatile state has been a challenge. Germanium antimony telluride (GST) offers potential electrical and optical characteristics to realize an optical nonvolatile state through a material phase transition. In this work, we demonstrate controlled phase tuning of a thermally evaporated GST-integrated silicon ring-resonator for potential neuromorphic application. We present material characterization and device fabrication and correlate the electrical and photonic phase transitions of ring-integrated GST. The temperature cycling in temperature-dependent resistance measurement shows the feasibility of pinning the phase of the transition region, which could be exploited for multiple non-volatile states. Using a simple device architecture, we have exploited the non-volatile and gradual transition of thermally evaporated GST to access intermediate states, which can be realized as synaptic weights in neural networks.
Authors
- Shankar Kumar Selvaraja (ORCID: https://orcid.org/0000-0003-2670-7058)
- Rakshitha Kallega
- Roopali Shekhawat (ORCID: https://orcid.org/0000-0001-5131-0189)
- K. Ramesh (ORCID: https://orcid.org/0000-0002-8304-6500)
Institutions
- Indian Institute of Science Bangalore (IN)
Publication Details
- Journal
- APL Materials
- Published
- 2025-05-01
- DOI
- https://doi.org/10.1063/5.0257237
- Citations
- 1
- Primary Topic
- Neural Networks and Reservoir Computing
- Type
- article
- Field-Weighted Citation Impact
- 2.48