Krista G. Steenbergen, Stephanie Lambie and Nicola Gaston
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引用次数: 0
摘要
液态金属(LM)技术在现代材料科学中迅速发展,低熔点金属在新兴应用中起着举足轻重的作用。最近的研究表明,掺杂液体镓系统在冷却过程中形成壮观和多样的表面结构[Tang et al., Nat. nanotechnology]。[j] .光子学报,2021,16,431-439],激发了人们对纯液态镓表面可能的几何结构的兴趣。与已知的表面密度增加不同,这种侧向表面顺序长期以来一直在实验和理论上暗示,但仍然是谜。在这里,我们首次使用高精度和大规模分子动力学模拟以及机器学习分析技术,定量表征了这种表面排序的深度和性质。我们还量化了添加氧化镓膜所带来的增强结构秩序,以及掺杂剂(铋)所造成的破坏。
Discerning order from chaos: characterising the surface structure of liquid gallium†
Liquid metal (LM) technologies are rapidly advancing in modern materials science, with low melting point metals playing a pivotal role in emerging applications. Recent studies reveal that doped liquid gallium systems form spectacular and diverse surface structures during cooling, [Tang et al., Nat. Nanotechnol., 2021, 16, 431–439] sparking renewed interest in the possible geometric structuring at the surface of pure liquid gallium. Distinct from the known increase in surface density, this lateral surface order has long been hinted at experimentally and theoretically but has remained enigmatic. Here, we quantitatively characterise the depth and nature of this surface ordering for the first time, using highly accurate and large scale molecular dynamics simulations coupled with machine learning analysis techniques. We also quantify the enhanced structural order introduced by the addition of a gallium oxide film as well as the disruption due to a dopant (bismuth).