Materials Strategies for Organic Neuromorphic Devices

Neuromorphic computing is becoming increasingly prominent as artificial intelligence (AI) facilitates progressively seamless interaction between humans and machines. The conventional von Neumann architecture and complementary metal-oxide-semiconductor transistor scaling are unable to meet the highly demanding computational density and energy efficiency requirements of AI. Neuromorphic computing aims to address these challenges by using brain-like computing architectures and novel synaptic memories that coallocate information storage and computation, thereby enabling low latency at high energy efficiency and high memory density. Though various emerging memory devices have been extensively studied to emulate the functionality of biological synapses, there is currently nomaterial/device system that encompasses both the needed metrics for high-performance neuromorphic computing and the required biocompatibility for potential bodycomputer integration. In this review, we aim to equip the reader with general design principles and materials requirements for realizing high-performance organic neuromorphic devices. We use instructive examples from recent literature to discuss each requirement, illustrating the challenges as well as future research opportunities. Though organic devices still face many challenges to become major players in neuromorphic computing, mostly due to their lack of compliance with back-end-of-line processes required for integration with digital logic, we propose that their biocompatibility and mechanical conformability give them an advantage for creating adaptive biointerfaces, brain-machine interfaces, and biology-inspired prosthetics.

Automated summary

Neuromorphic computing aims to address the challenges in AI with brain-like computing architectures and novel synaptic memories. Despite various emerging memory devices being studied to emulate biological synapses, a material/device system with both high performance for neuromorphic computing and biocompatibility for potential body-computer integration is currently lacking.