Additive Manufacturing of Neuromorphic Systems

  • Jiongyi Yan
  • , Yutai Su
  • , James P.K. Armstrong
  • , Andrew Gleadall

Research output: Contribution to journalReview articlepeer-review

3 Scopus citations

Abstract

Neuromorphic engineering aims to create brain-inspired computing systems based on synaptic electronic hardware and neural network software. It combines intelligent materials, advanced processing technology, and computation programs. Additive manufacturing (AM), despite being one of the advanced manufacturing technologies capable of multimaterial processing at the microscale, is not widely applied in neuromorphic hardware fabrication. This gap suggests not only process incompatibility and limited resolution of AM but opportunities to create novel intelligent systems. Here, the state-of-the-art in AM-printed neuromorphic hardware (synaptic electronics and mechanical systems) is reviewed and discussed the integration of AM techniques with neuromorphic engineering. An outlook of printed neuromorphic systems is provided with low cost and environmental impact but high customizability and design flexibility. With ongoing innovation in AM technologies and materials, AM is envisioned with high throughput and resolution for affordable, scalable, and customizable neuromorphic hardware production. The crossover of AM and neuromorphic engineering facilitates prototyping of brain-inspired computing architectures for efficient and analog computation. This approach may facilitate various applications including neuromorphic robotics, bionics, and real-time sensing.

Original languageEnglish
Article number2504807
JournalAdvanced Materials
Volume37
Issue number39
DOIs
StatePublished - 2 Oct 2025

Keywords

  • additive manufacturing
  • artificial neural networks
  • memristors
  • neuromorphic computing
  • transistors

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