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Related Experiment Video

Updated: Jun 30, 2025

Hybrid Printing for the Fabrication of Smart Sensors
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Programmable and Modularized Gas Sensor Integrated by 3D Printing.

Shixiang Zhou1, Yijing Zhao2, Yanran Xun1

  • 1Department of Materials Science and Engineering, National University of Singapore, 117575, Singapore.

Chemical Reviews
|March 18, 2024
PubMed
Summary
This summary is machine-generated.

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Three-dimensional (3D) printing enables intelligent manufacturing of advanced gas sensors. This review explores 3D printing techniques for creating customizable, high-performance gas sensor devices with AI-driven optimization.

Area of Science:

  • Intelligent Manufacturing
  • Materials Science
  • Sensor Technology

Background:

  • Intelligent manufacturing and computer-aided engineering facilitate synergistic design and optimization of electronic equipment.
  • Three-dimensional (3D) printing offers mold-free fabrication and near-net-shape forming, ideal for materializing digital designs into functional devices.
  • Gas sensors benefit significantly from 3D printing's ability to tailor internal modules (composition, microstructure, architecture) for performance optimization.

Purpose of the Study:

  • To review the latest advancements in 3D-printed gas sensor devices and components.
  • To elucidate the technical features and advantages of various 3D printing processes for gas sensor fabrication.
  • To propose a testing framework for evaluating customized gas sensor performance.

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Related Experiment Videos

Last Updated: Jun 30, 2025

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Main Methods:

  • Review of current literature on 3D printing technologies applied to gas sensors.
  • Analysis of modularized fabrication approaches for diverse application requirements.
  • Integration of artificial intelligence (AI) software systems for signal precision and hardware optimization.

Main Results:

  • 3D printing allows for collaborative optimization of gas sensor performance through tailored module design.
  • Diverse 3D printing technologies enable modularized fabrication adaptable to specific application needs.
  • AI integration enhances signal dependability and facilitates self-learning for continuous hardware improvement in dynamic environments.

Conclusions:

  • 3D-printed gas sensors offer superior programmability and modularity for enhanced performance.
  • Challenges and advantages of these advanced gas sensors are highlighted.
  • Provides a comprehensive reference for material, structure, and process modifications in gas sensor development.