Nanoscale soil-water retention mechanism of unsaturated clay via MD and machine learning
Zhe Zhang, Xiaoyu Song

TL;DR
This study combines molecular dynamics simulations and machine learning to analyze the nanoscale soil-water retention mechanisms in unsaturated clay, revealing the dominance of van der Waals forces and capillarity effects.
Contribution
It introduces a novel integrated approach using MD simulations and neural networks to understand nanoscale soil-water interactions in clay minerals.
Findings
Adsorption is dominated by van der Waals forces and hydroxyl hydration.
Capillarity becomes prominent as water content increases.
Machine learning models relate matric suction, water content, and interface area.
Abstract
In this article, we investigate the nanoscale soil-water retention mechanism of unsaturated clay through molecular dynamics and machine learning. Pyrophyllite was chosen due to its stable structure and as the precursor of other 2:1 clay minerals. A series of molecular dynamics simulations of clay at low degrees of saturation were conducted. Soil water was represented by a point cloud through the center-of-mass method. Water-air interface area was measured numerically by the alpha-shape method. The soil-water retention mechanism at the nanoscale was analyzed by distinguishing adsorptive pressure and capillary pressure at different mass water contents and considering the apparent capillary interface area (i.e., water-air interface area per unit water volume). The water number density profile was used to quantify the adsorption effect. A neural-network based machine learning technique was…
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Taxonomy
TopicsSoil and Unsaturated Flow · Nanopore and Nanochannel Transport Studies · Groundwater flow and contamination studies
