Diffusive and Drift Halide Perovskite Memristive Barristors as Nociceptive and Synaptic Emulators for Neuromorphic Computing

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 ar...

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Veröffentlicht in:Advanced materials (Weinheim) 2021-04, Vol.33 (15), p.n/a, Article 2007851
Hauptverfasser: 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
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Sprache:eng
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Zusammenfassung: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 (NiOx) interface that supports drift kinetics are identified to design diffusive and drift memristors, respectively, with methylammonuim lead bromide (CH3NH3PbBr3) 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. 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 NiOx interfaces support drift kinetics with CH3NH3PbBr3 as the switching matrix, resulting in modulatable diffusive and drift memristors respectively.
ISSN:0935-9648
1521-4095
DOI:10.1002/adma.202007851