Influence of wetted micro/nano-structures on bubble nucleation in flow boiling: a molecular dynamics study

IF 2.1 4区 化学 Q4 BIOCHEMISTRY & MOLECULAR BIOLOGY
Chengdi Xiao, Dalin Yu, Jiaxun Huang, Haitao Zhang, Xixin Rao
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引用次数: 0

Abstract

Context

Ongoing advancements in microelectronic device integration and performance have intensified thermal management challenges. Surface roughness and wettability are key parameters for bubble nucleation during flow boiling, yet their nano-scale effects are not fully understood. This study uses molecular dynamics simulations to explore how wetted micro/nano-structured surfaces affect flow boiling, focusing on roughness, alignment, and driving forces. Results show that applying a force and optimizing wettability can boost heat transfer efficiency and accelerate heterogeneous bubble nucleation. Specifically, liquid film detachment time was reduced by 1888 ps on hydrophobic and 1370 ps on hydrophilic surfaces. The study also shows a subtle relationship between roughness and boiling performance. On different wettable surfaces, the average heat flux of hydrophobic surfaces can increase by up to 9.21% and that of hydrophilic surfaces by up to 7.90% with increasing roughness. Surface B2 (hydrophilic, roughness = 1.13), despite being rougher than B1 (hydrophilic, roughness = 1.09), has a delayed detachment time, highlighting the complex interdependence of surface morphology and fluid dynamics. In addition, the parallel flow arrangement promotes bubble nucleation by adjusting the flow field distribution while slowing bubble growth. The explosive boiling time is delayed by 6.5% compared to the staggered arrangement. These findings offer insights for designing more efficient thermal management systems in high-performance microelectronics.

Methods

In this study, the synergistic effect of the roughness of different wettabilities micro/nano-structures and their arrangement on the flow boiling was systematically analyzed by molecular dynamics simulation method based on the open-source software LAMMPS. The wall material is modelled as an L-J solid with a face-centered cubic (FCC) lattice structure, with a lattice constant of 3.5 Å. The structure was divided into three parts: the fixed layer, the thermostatic layer, and the heat-conducting layer. The L-J fluid system was composed of a FCC lattice arrangement, with a lattice constant of 5.8 Å in the liquid region and 32 Å in the vapor region. All interatomic interactions are described by the Lennard–Jones (L-J) potential function.

Graphical Abstract

Boiling nucleation for different operating conditions. a Roughness average. b Parallel flow and staggered arrangement

湿润微纳结构对流动沸腾中气泡成核的影响:分子动力学研究
微电子器件集成和性能的不断进步加剧了热管理的挑战。表面粗糙度和润湿性是流动沸腾过程中气泡成核的关键参数,但它们在纳米尺度上的影响尚不完全清楚。本研究使用分子动力学模拟来探索湿润的微/纳米结构表面如何影响流动沸腾,重点关注粗糙度、排列和驱动力。结果表明,施加作用力和优化润湿性可以提高传热效率,加速非均相气泡成核。具体来说,疏水表面的液膜剥离时间减少了1888 ps,亲水表面的液膜剥离时间减少了1370 ps。该研究还显示了粗糙度和沸腾性能之间的微妙关系。在不同的可湿性表面上,随着粗糙度的增加,疏水表面的平均热流密度可增加9.21%,亲水表面的平均热流密度可增加7.90%。表面B2(亲水性,粗糙度= 1.13)尽管比B1(亲水性,粗糙度= 1.09)粗糙,但剥离时间延迟,突出了表面形态和流体动力学之间复杂的相互依存关系。此外,平行流排列通过调节流场分布促进气泡成核,同时减缓气泡生长。与交错排列相比,爆炸沸腾时间延迟6.5%。这些发现为在高性能微电子中设计更有效的热管理系统提供了见解。方法采用基于开源软件LAMMPS的分子动力学模拟方法,系统分析了不同润湿性微纳结构粗糙度及其排列方式对流动沸腾的协同效应。墙体材料建模为L-J固体,具有面心立方(FCC)晶格结构,晶格常数为3.5 Å。该结构分为三部分:固定层、恒温层和导热层。L-J流体体系由FCC晶格排列组成,液体区晶格常数为5.8 Å,蒸汽区晶格常数为32 Å。所有的原子间相互作用都用Lennard-Jones (L-J)势函数描述。图解:不同操作条件下的沸腾成核。粗糙度平均值。b平行流动,交错排列
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来源期刊
Journal of Molecular Modeling
Journal of Molecular Modeling 化学-化学综合
CiteScore
3.50
自引率
4.50%
发文量
362
审稿时长
2.9 months
期刊介绍: The Journal of Molecular Modeling focuses on "hardcore" modeling, publishing high-quality research and reports. Founded in 1995 as a purely electronic journal, it has adapted its format to include a full-color print edition, and adjusted its aims and scope fit the fast-changing field of molecular modeling, with a particular focus on three-dimensional modeling. Today, the journal covers all aspects of molecular modeling including life science modeling; materials modeling; new methods; and computational chemistry. Topics include computer-aided molecular design; rational drug design, de novo ligand design, receptor modeling and docking; cheminformatics, data analysis, visualization and mining; computational medicinal chemistry; homology modeling; simulation of peptides, DNA and other biopolymers; quantitative structure-activity relationships (QSAR) and ADME-modeling; modeling of biological reaction mechanisms; and combined experimental and computational studies in which calculations play a major role.
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