High-throughput printing of combinatorial materials from aerosols

Autor: Minxiang Zeng, Yipu Du, Qiang Jiang, Nicholas Kempf, Chen Wei, Miles V. Bimrose, A. N. M. Tanvir, Hengrui Xu, Jiahao Chen, Dylan J. Kirsch, Joshua Martin, Brian C. Wyatt, Tatsunori Hayashi, Mortaza Saeidi-Javash, Hirotaka Sakaue, Babak Anasori, Lihua Jin, Michael D. McMurtrey, Yanliang Zhang
Rok vydání: 2023
Předmět:
Zdroj: Nature. 617:292-298
ISSN: 1476-4687
0028-0836
DOI: 10.1038/s41586-023-05898-9
Popis: The development of new materials and their compositional and microstructural optimization are essential in regard to next-generation technologies such as clean energy and environmental sustainability. However, materials discovery and optimization have been a frustratingly slow process. The Edisonian trial-and-error process is time consuming and resource inefficient, particularly when contrasted with vast materials design spaces1. Whereas traditional combinatorial deposition methods can generate material libraries2,3, these suffer from limited material options and inability to leverage major breakthroughs in nanomaterial synthesis. Here we report a high-throughput combinatorial printing method capable of fabricating materials with compositional gradients at microscale spatial resolution. In situ mixing and printing in the aerosol phase allows instantaneous tuning of the mixing ratio of a broad range of materials on the fly, which is an important feature unobtainable in conventional multimaterials printing using feedstocks in liquid–liquid or solid–solid phases4–6. We demonstrate a variety of high-throughput printing strategies and applications in combinatorial doping, functional grading and chemical reaction, enabling materials exploration of doped chalcogenides and compositionally graded materials with gradient properties. The ability to combine the top-down design freedom of additive manufacturing with bottom-up control over local material compositions promises the development of compositionally complex materials inaccessible via conventional manufacturing approaches.
Databáze: OpenAIRE
Externí odkaz: