Open AccessElectronically Reconfigurable Photonic Switches Incorporating Plasmonic Structures and Phase Change Materials
Author(s) -
Farmakidis Nikolaos,
Youngblood Nathan,
Lee June Sang,
Feldmann Johannes,
Lodi Alessandro,
Li Xuan,
Aggarwal Samarth,
Zhou Wen,
Bogani Lapo,
Pernice Wolfram HP,
Wright C David,
Bhaskaran Harish
Publication year - 2022
Publication title -
advanced science
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 5.388
H-Index - 100
ISSN - 2198-3844
DOI - 10.1002/advs.202200383
Subject(s) - photonics , miniaturization , electronics , neuromorphic engineering , materials science , plasmon , routing (electronic design automation) , non volatile memory , optical switch , computer science , optoelectronics , reconfigurability , efficient energy use , nanotechnology , electrical engineering , telecommunications , embedded system , engineering , machine learning , artificial neural network
The ever‐increasing demands for data processing and storage will require seamless monolithic co‐integration of electronics and photonics. Phase‐change materials are uniquely suited to fulfill this function due to their dual electro‐optical sensitivity, nonvolatile retention properties, and fast switching dynamics. The extreme size disparity however between CMOS electronics and dielectric photonics inhibits the realization of efficient and compact electrically driven photonic switches, logic and routing elements. Here, the authors achieve an important milestone in harmonizing the two domains by demonstrating an electrically reconfigurable, ultra‐compact and nonvolatile memory that is optically accessible. The platform relies on localized heat, generated within a plasmonic structure; this uniquely allows for both optical and electrical readout signals to be interlocked with the material state of the PCM while still ensuring that the writing operation is electrically decoupled. Importantly, by miniaturization and effective thermal engineering, the authors achieve unprecedented energy efficiency, opening up a path towards low‐energy optoelectronic hardware for neuromorphic and in‐memory computing.