Scalable Microscale Artificial Synapses of Lead Halide Perovskite with Femtojoule Energy Consumption
Source abstract
Abstract
The efficient conduction of mobile ions in halide perovskites is highly promising for artificial synapses (or memristive devices), devices with a conductivity that can be varied by applying a bias voltage. Here we address the challenge of downscaling halide perovskite-based artificial synapses to achieve low energy consumption and allow high-density integration. We fabricate halide perovskite artificial synapses in a back-contacted architecture to achieve microscale devices despite the high solubility of halide perovskites in polar solvents that are commonly used in lithography. The energy consumption of a conductance change of the device is as low as 640 fJ, among the lowest reported for two-terminal halide perovskite artificial synapses so far. Moreover, the high resistance of the device up to hundreds of megaohms, low operating voltage of 100 mV and simple two-terminal architecture enable implementation in highly dense crossbar arrays. These arrays could potentially show orders of magnitude lower energy consumption for computation compared to conventional digital computers.
Source: openalex_inverted_index · Quality: baseline
Research context
OpenAlex topics: Perovskite Materials and Applications · Advanced Memory and Neural Computing · Conducting polymers and applications
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Center for Nanophotonics, AMOLF, 1098 XG Amsterdam, The Netherlands
Funding
H2020 European Research Council · Nederlandse Organisatie voor Wetenschappelijk Onderzoek
References (56)
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