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Additive Manufacturing of Neuromorphic Systems.

Jiongyi Yan1, Yutai Su2, James P K Armstrong3

  • 1Wolfson School of Mechanical Electrical and Manufacturing Engineering, Loughborough University, Loughborough, LE11 3TU, UK.

Advanced Materials (Deerfield Beach, Fla.)
|July 14, 2025
PubMed
Summary

Additive manufacturing (AM) offers a novel approach to fabricating neuromorphic hardware, enabling customizable and low-cost brain-inspired computing systems. This integration promises advancements in robotics, bionics, and real-time sensing applications.

Keywords:
additive manufacturingartificial neural networksmemristorsneuromorphic computingtransistors

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Area of Science:

  • Neuromorphic Engineering
  • Additive Manufacturing (AM)
  • Materials Science

Background:

  • Neuromorphic engineering seeks to replicate brain functions using electronic hardware and neural network software.
  • Current neuromorphic hardware fabrication has limited integration with advanced manufacturing technologies like AM.
  • A gap exists in applying AM's multimaterial microscale processing capabilities to neuromorphic systems.

Purpose of the Study:

  • To review the state-of-the-art in AM-printed neuromorphic hardware.
  • To discuss the integration of AM techniques with neuromorphic engineering.
  • To provide an outlook on the future of printed neuromorphic systems.

Main Methods:

  • Review of current literature on AM techniques for neuromorphic hardware.
  • Analysis of synaptic electronics and mechanical systems fabricated using AM.
  • Discussion on the integration challenges and opportunities between AM and neuromorphic engineering.

Main Results:

  • AM enables the fabrication of customizable neuromorphic hardware with high design flexibility.
  • Printed neuromorphic systems offer potential for low cost and reduced environmental impact.
  • AM integration facilitates prototyping of efficient analog computing architectures.

Conclusions:

  • Additive manufacturing presents a promising pathway for scalable and affordable neuromorphic hardware production.
  • The synergy between AM and neuromorphic engineering can drive innovation in brain-inspired computing.
  • Future advancements in AM technologies will enhance throughput and resolution for neuromorphic applications.