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 tel...

Full description

Saved in:
Bibliographic Details
Main Authors: Rakshitha Kallega, Roopali Shekhawat, K. Ramesh, Shankar Kumar Selvaraja
Format: Article
Language:English
Published: AIP Publishing LLC 2025-05-01
Series:APL Materials
Online Access:http://dx.doi.org/10.1063/5.0257237
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1849698289250729984
author Rakshitha Kallega
Roopali Shekhawat
K. Ramesh
Shankar Kumar Selvaraja
author_facet Rakshitha Kallega
Roopali Shekhawat
K. Ramesh
Shankar Kumar Selvaraja
author_sort Rakshitha Kallega
collection DOAJ
description 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.
format Article
id doaj-art-d4d7f6a94ce347ab8e0e4a7bf86e31a5
institution DOAJ
issn 2166-532X
language English
publishDate 2025-05-01
publisher AIP Publishing LLC
record_format Article
series APL Materials
spelling doaj-art-d4d7f6a94ce347ab8e0e4a7bf86e31a52025-08-20T03:18:56ZengAIP Publishing LLCAPL Materials2166-532X2025-05-01135051104051104-810.1063/5.0257237Controlled crystallization of thermal evaporated GST-on-SOI for photonic neuromorphic applicationRakshitha Kallega0Roopali Shekhawat1K. Ramesh2Shankar Kumar Selvaraja3Centre for Nano Science and Engineering, Indian Institute of Science, Bangalore, IndiaDepartment of Physics, Indian Institute of Science, Bangalore, IndiaDepartment of Physics, Indian Institute of Science, Bangalore, IndiaCentre for Nano Science and Engineering, Indian Institute of Science, Bangalore, IndiaNeuromorphic 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.http://dx.doi.org/10.1063/5.0257237
spellingShingle Rakshitha Kallega
Roopali Shekhawat
K. Ramesh
Shankar Kumar Selvaraja
Controlled crystallization of thermal evaporated GST-on-SOI for photonic neuromorphic application
APL Materials
title Controlled crystallization of thermal evaporated GST-on-SOI for photonic neuromorphic application
title_full Controlled crystallization of thermal evaporated GST-on-SOI for photonic neuromorphic application
title_fullStr Controlled crystallization of thermal evaporated GST-on-SOI for photonic neuromorphic application
title_full_unstemmed Controlled crystallization of thermal evaporated GST-on-SOI for photonic neuromorphic application
title_short Controlled crystallization of thermal evaporated GST-on-SOI for photonic neuromorphic application
title_sort controlled crystallization of thermal evaporated gst on soi for photonic neuromorphic application
url http://dx.doi.org/10.1063/5.0257237
work_keys_str_mv AT rakshithakallega controlledcrystallizationofthermalevaporatedgstonsoiforphotonicneuromorphicapplication
AT roopalishekhawat controlledcrystallizationofthermalevaporatedgstonsoiforphotonicneuromorphicapplication
AT kramesh controlledcrystallizationofthermalevaporatedgstonsoiforphotonicneuromorphicapplication
AT shankarkumarselvaraja controlledcrystallizationofthermalevaporatedgstonsoiforphotonicneuromorphicapplication