Ilgen Anastasia G, Borguet Eric, Geiger Franz M, Gibbs Julianne M, Grassian Vicki H, Jun Young-Shin, Kabengi Nadine, Kubicki James D
Geochemistry Department, Sandia National Laboratories, Albuquerque, NM, 87123, USA.
Department of Chemistry, Temple University, Philadelphia, PA, 19122, USA.
Nat Commun. 2024 Jun 22;15(1):5326. doi: 10.1038/s41467-024-49598-y.
Solid-water interfaces are crucial for clean water, conventional and renewable energy, and effective nuclear waste management. However, reflecting the complexity of reactive interfaces in continuum-scale models is a challenge, leading to oversimplified representations that often fail to predict real-world behavior. This is because these models use fixed parameters derived by averaging across a wide physicochemical range observed at the molecular scale. Recent studies have revealed the stochastic nature of molecular-level surface sites that define a variety of reaction mechanisms, rates, and products even across a single surface. To bridge the molecular knowledge and predictive continuum-scale models, we propose to represent surface properties with probability distributions rather than with discrete constant values derived by averaging across a heterogeneous surface. This conceptual shift in continuum-scale modeling requires exponentially rising computational power. By incorporating our molecular-scale understanding of solid-water interfaces into continuum-scale models we can pave the way for next generation critical technologies and novel environmental solutions.
固水界面对于清洁水、传统能源和可再生能源以及有效的核废料管理至关重要。然而,在连续尺度模型中反映反应界面的复杂性是一项挑战,这导致了过于简化的表示,往往无法预测实际行为。这是因为这些模型使用通过在分子尺度上观察到的广泛物理化学范围内进行平均而得出的固定参数。最近的研究揭示了分子水平表面位点的随机性,即使在单个表面上,这些位点也定义了各种反应机制、速率和产物。为了弥合分子知识与预测性连续尺度模型之间的差距,我们建议用概率分布而非通过对异质表面进行平均得出的离散常数值来表示表面性质。连续尺度建模中的这一概念转变需要指数级增长的计算能力。通过将我们对固水界面的分子尺度理解纳入连续尺度模型,我们可以为下一代关键技术和新型环境解决方案铺平道路。