“…The emerging use of machine-learning methods was also illustrated in two contributions that parameterize atomic scale simulations, and upscale geomaterials microscopic properties to continuum-scale modeling. Finally, the topics explored in these contributions span a wide range of geochemical topics applicable to environments from the Earth's core to its surface, including: solid-liquid partitioning under Earth's core conditions (Zhang et al, 2020b), chemical geodynamics of the mantle (Zhang and Liu, 2020), recycling of noble gas in the subduction zones (Wang et al, 2020), thermodynamics of hydrothermal fluids (Mei et al, 2020), interfacial and structural properties of clay and (Fe, Mn) oxide materials (Bylaska et al, 2020;Newton and Kwon, 2020;Zhang et al, 2020a), and a machine learning-based framework for coupling and upscaling of reactive transport processes and parameters across spatial scales (Prasianakis et al, 2020). These papers are briefly introduced in the following.…”