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<p>Recently, polymer-2D nanomaterial composites have attracted significant attention due to their novel properties and multifunctional capabilities. The integration of AI with 3D printing autonomously tune printing conditions and refine microstructures in polymer-2D nanomaterial composites, creating multifunctional architectures, and minimizes human errors. We review the AI-driven 3D printing, with focus on materials discovery, ink formulation, process monitoring, and performance optimization for specific applications. As data-rich experimental platforms and physics-informed modeling continue to advance, AI-enabled 3D printing provides a scalable and reliable route for translating high-performance 2D nanomaterial–polymer composites from laboratory-scale demonstrations to practical, real-world applications.</p> Graphical abstract <p></p>

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Artificial intelligence in 3D printing: Unlocking the potential of 2D nanomaterial–polymer composites

  • 期刊论文

  • 发表日期：

    2026年5月18日

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  • Wonbong Choi,
  • Md Luthfar Rahman Liman,
  • Maryam Tajik Hesaramiri,
  • Narendra Dahotre,
  • R. C. Advincula,
  • Yijie Jiang

摘要

Recently, polymer-2D nanomaterial composites have attracted significant attention due to their novel properties and multifunctional capabilities. The integration of AI with 3D printing autonomously tune printing conditions and refine microstructures in polymer-2D nanomaterial composites, creating multifunctional architectures, and minimizes human errors. We review the AI-driven 3D printing, with focus on materials discovery, ink formulation, process monitoring, and performance optimization for specific applications. As data-rich experimental platforms and physics-informed modeling continue to advance, AI-enabled 3D printing provides a scalable and reliable route for translating high-performance 2D nanomaterial–polymer composites from laboratory-scale demonstrations to practical, real-world applications.

Graphical abstract