High-throughput printing of functionally gradient material from self-propagation

Yan Zhang (), Yuqiang Liu (), Guangzhen Ren and Chen Yu
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Yan Zhang: Xinjiang University
Yuqiang Liu: Xinjiang University
Guangzhen Ren: Xinjiang University
Chen Yu: Xinjiang University

Nature Communications, 2025, vol. 16, issue 1, 1-12

Abstract: Abstract While combinatorial deposition techniques have accelerated the screening and understanding of materials, the creation of multi-material integration and gradient libraries is limited by mixing and distribution challenges. Here we show arbitrarily formable 3D-printable precursor materials, which are precisely formulated with their compositions by high-throughput techniques to achieve multiple degrees of freedom, efficiently realizing multi-scale, multi-component, and high-throughput printing. Meanwhile, a highly adaptive self-propagating-energy deposition technique based on a redox reaction between the precursors has been established, reducing the dependence on specific equipment and processes. We have realized printing strategies for multiple copper-based composites and multicomponent gradient materials, making possible multiple metallic and nonmetallic compounds as well as multigradient materials with multiple compositions and structures with simultaneous gradient properties. Multi-gradient materials are able to be printed synchronously during the printing process, avoiding structural defects such as thermal accumulation and cracks through thermal stacking between gradients, which cannot be obtained by conventional manufacturing methods.

Date: 2025
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DOI: 10.1038/s41467-025-65189-x

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