Particle-assisted Formation of Oil-in-liquid Metal Emulsions
Journal of physics Condensed matter(2024)
摘要
Gallium-based liquid metals (LM) have surface tension an order of magnitude higher than water and break up into micro-droplets when mixed with other liquids. In contrast, silicone oil readily mixes into LM foams to create oil-in-LM emulsions with oil inclusions. Previously, the LM was foamed through rapid mixing in air for an extended duration (over 2 hours). This process first results in the internalization of oxide flakes that form at the air-liquid interface. Once a critical fraction of these randomly shaped solid flakes is reached, air bubbles internalize into the LM to create foams that can internalize secondary liquids. Here, we introduce an alternative oil-in-LM emulsion fabrication method that relies on the prior addition of SiO2 micro-particles into the LM before mixing it with the silicone oil. This particle-assisted emulsion formation process provides a higher control over the composition of the LM-particle mixture before oil addition, which we employ to systematically study the impact of particle characteristics and content on the emulsions' composition and properties. We demonstrate that the solid particle size (0.8 µm to 5 µm) and volume fraction (1% to 10%) have a negligible impact on the internalization of the oil inclusions. The inclusions are mostly spherical with diameters of 20 to 100 µm diameter and are internalized by forming new, rather than filling old, geometrical features. We also study the impact of the particle characteristics on the two key properties related to the functional application of the LM emulsions in the thermal management of microelectronics. In particular, we measure the impact of particles and silicone oil on the emulsion's thermal conductivity and its ability to prevent deleterious gallium-induced corrosion and embrittlement of contacting metal substrates.
更多查看译文
关键词
liquid metal,foams,emulsions,silica,thermal interface materials,thermal conductivity,gallium-induced corrosion
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要