High-throughput printing of combinatorial materials from aerosols
© 2023. The Author(s)..
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.
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:617 |
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| Enthalten in: |
Nature - 617(2023), 7960 vom: 10. Mai, Seite 292-298 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Zeng, Minxiang [VerfasserIn] |
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| Links: |
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| Anmerkungen: |
Date Completed 12.05.2023 Date Revised 30.01.2024 published: Print-Electronic Citation Status PubMed-not-MEDLINE |
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| doi: |
10.1038/s41586-023-05898-9 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| 520 | |a © 2023. The Author(s). | ||
| 520 | |a 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 | ||
| 650 | 4 | |a Journal Article | |
| 650 | 4 | |a Research Support, U.S. Gov't, Non-P.H.S. | |
| 700 | 1 | |a Du, Yipu |e verfasserin |4 aut | |
| 700 | 1 | |a Jiang, Qiang |e verfasserin |4 aut | |
| 700 | 1 | |a Kempf, Nicholas |e verfasserin |4 aut | |
| 700 | 1 | |a Wei, Chen |e verfasserin |4 aut | |
| 700 | 1 | |a Bimrose, Miles V |e verfasserin |4 aut | |
| 700 | 1 | |a Tanvir, A N M |e verfasserin |4 aut | |
| 700 | 1 | |a Xu, Hengrui |e verfasserin |4 aut | |
| 700 | 1 | |a Chen, Jiahao |e verfasserin |4 aut | |
| 700 | 1 | |a Kirsch, Dylan J |e verfasserin |4 aut | |
| 700 | 1 | |a Martin, Joshua |e verfasserin |4 aut | |
| 700 | 1 | |a Wyatt, Brian C |e verfasserin |4 aut | |
| 700 | 1 | |a Hayashi, Tatsunori |e verfasserin |4 aut | |
| 700 | 1 | |a Saeidi-Javash, Mortaza |e verfasserin |4 aut | |
| 700 | 1 | |a Sakaue, Hirotaka |e verfasserin |4 aut | |
| 700 | 1 | |a Anasori, Babak |e verfasserin |4 aut | |
| 700 | 1 | |a Jin, Lihua |e verfasserin |4 aut | |
| 700 | 1 | |a McMurtrey, Michael D |e verfasserin |4 aut | |
| 700 | 1 | |a Zhang, Yanliang |e verfasserin |4 aut | |
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