Diffusive and Drift Halide Perovskite Memristive Barristors as Nociceptive and Synaptic Emulators for Neuromorphic Computing. Issue 15 (16th March 2021)

• Record Type: Journal Article
• Authors: John, Rohit Abraham; Yantara, Natalia; Ng, Si En; Patdillah, Muhammad Iszaki Bin; Kulkarni, Mohit Rameshchandra; Jamaludin, Nur Fadilah; Basu, Joydeep; Ankit, ; Mhaisalkar, Subodh G.; Basu, Arindam; Mathews, Nripan
• Is Part Of: Advanced materials. Volume 33:Issue 15(2021)
• Page Start: n/a
• Page End: n/a
• Publication Date: 2021-03-16
• Subjects: artificial nociceptors -- diffusive memristors -- drift memristors -- halide perovskite barristors -- neuromorphic computing; Materials -- Periodicals; Chemical vapor deposition -- Periodicals; 620.11
• DOI: 10.1002/adma.202007851
• Languages: English
• ISSNs: 0935-9648

Abstract

Abstract: 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 (CH3 NH3 PbBr3 ) 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. Abstract : Halide perovskite memristive barristors (diodes with variable Schottky barriers) portraying tunable diffusive dynamics and ionic drift as nociceptive and synaptic emulators for neuromorphic sensory signal computing are experimentally demonstrated. Poly(3, 4‐ethylenedioxythiophene) polystyrene sulfonate interfaces promote diffusive kinetics while NiO x interfaces support drift kinetics with CH3 NH3 PbBr3 as the switching matrix, resulting in modulatable diffusive and drift memristors respectively.