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NSF
Many processes of industrial and technological importance involve the impact of drops on a surface. Drop impact is a key step in applying coatings to solid surfaces and in various printing processes. Controlling the dynamics of drop impact is essential in achieving uniform coatings and in realizing high-resolution printing. One way to regulate drop impact is to tailor the properties of the substrate – the surface upon which drops impact. Prior research demonstrated that soft substrates could inhibit splashing and avoid the formation of small extraneous drops. However, the underlying physics and the role of substrate properties on drop impact are poorly understood. This project will systematically study how variations in substrate properties influence drop impact behaviors. Conducted in collaboration with industrial engineers, the research will focus on substrates most relevant to industrial coating processes. Thus, the proposed research will enrich the fundamental understanding of drop impact dynamics and potentially revolutionize existing industrial coating practices, particularly the processes of multi-layer coating and coating on compliant surfaces. The central hypothesis of this research is that precise tuning of substrate mechanical properties offers a powerful route to control drop impact outcomes with high specificity. This research will systematically investigate how compliant, heterogeneous, and non-Newtonian substrates influence drop impact dynamics. By modulating substrate elasticity to control drop impact, the research aims to reveal the missing link between the onset of splashing and the distribution of impact pressure, addressing a long-standing question in the study of drop impact. The project will unfold in three stages, examining how (1) thin elastic substrates, (2) mechanically heterogeneous substrates, and (3) rheologically complex substrates alter the underlying fluid dynamics of drop impact. Motivated by pressing engineering challenges such as multi-layer coatings and coatings on compliant surfaces, this research will decompose complex impact scenarios into simple model processes, enabling the development of predictive understanding applicable to more complex industrial settings. A strong partnership with industrial researchers ensures that the project remains aligned with the most relevant and urgent engineering needs. In addition to industrial impact, the project will contribute to STEM education through student exchange programs and outreach initiatives. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
Up to $324K
2028-06-30
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