The use of calcined clays in construction materials has attracted significant attention in the
last few years. Based on the continued need for sustainable construction materials to meet …

The past two decades have been marked by an increased interest in the synthesis and the
properties of geoinspired hydrosilicate nanoscrolls and nanotubes. The present review …

Based on the datasets of first-principle simulations, machine learning potentials (MLPs) can
achieve both accurate predictions of complex material systems and high-efficiency …

Nanoscale mechanical behavior of kaolinite as a fundamental failure mechanism has been
investigated under uniaxial tension and compression using Molecular Dynamics (MD) …

The main objective of this review paper is to take a crossed look at all of the data of elastic
moduli of clay minerals acquired from various experimental and theoretical methods. The …

Influenced by the external environment, clays often contain a large number of lattice defects
inside, and the defects have an essential influence on the physical and mechanical …

In this work, with the assistance of the intercalation modification approach, three kinds of
intercalated compounds, dimethyl sulfoxide (DMSO), potassium acetate (KAc), and …

Kaolinite is the major clay mineral and dispersed widely in topsoil and subsoil in the world.
The structural, electronic, and mechanical properties of kaolinite are closely related to their …

In this study, we simulated the rolling mechanism of Halloysite by molecular dynamics (MD)
under different conditions. We have illustrated that the transformation from slab Halloysite to …

Abstract Machine learning molecular dynamics (MLMD) is a promising method for predicting
material properties with high accuracy and low computational costs. Two kaolinite machine …