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Diffusive and Drift Halide Perovskite Memristive Barristors as Nociceptive and Synaptic Emulators for Neuromorphic Computing
Author(s) -
John Rohit Abraham,
Yantara Natalia,
Ng Si En,
Patdillah Muhammad Iszaki Bin,
Kulkarni Mohit Rameshchandra,
Jamaludin Nur Fadilah,
Basu Joydeep,
Mhaisalkar Subodh G.,
Basu Arindam,
Mathews Nripan
Publication year - 2021
Publication title -
advanced materials
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 10.707
H-Index - 527
eISSN - 1521-4095
pISSN - 0935-9648
DOI - 10.1002/adma.202007851
Subject(s) - neuromorphic engineering , memristor , materials science , bioelectronics , perovskite (structure) , electrode , ambipolar diffusion , nanotechnology , optoelectronics , artificial neural network , computer science , electronic engineering , physics , biosensor , engineering , chemical engineering , artificial intelligence , plasma , quantum mechanics
With the current research impetus on neuromorphic computing hardware, realizing efficient drift and diffusive memristors are considered critical milestones for the implementation of readout layers, selectors, and frameworks in deep learning and reservoir computing networks. Current demonstrations are predominantly limited to oxide insulators with a soft breakdown behavior. While organic ionotronic electrochemical materials offer an attractive alternative, their implementations thus far have been limited to features exploiting ionic drift a.k.a. drift memristor technology. Development of diffusive memristors with organic electrochemical materials is still at an early stage, and modulation of their switching dynamics remains unexplored. Here, halide perovskite (HP) memristive barristors (diodes with variable Schottky barriers) portraying tunable diffusive dynamics and ionic drift are proposed and experimentally demonstrated. An ion permissive poly(3,4‐ethylenedioxythiophene):polystyrene sulfonate interface that promotes diffusive kinetics and an ion source nickel oxide (NiO x ) interface that supports drift kinetics are identified to design diffusive and drift memristors, respectively, with methylammonuim lead bromide (CH 3 NH 3 PbBr 3 ) as the switching matrix. In line with the recent interest on developing artificial afferent nerves as information channels bridging sensors and artificial neural networks, these HP memristive barristors are fashioned as nociceptive and synaptic emulators for neuromorphic sensory signal computing.