Berlin 2024 – scientific programme

Parts | Days | Selection | Search | Updates | Downloads | Help

MM: Fachverband Metall- und Materialphysik

MM 20: Data Driven Material Science: Big Data and Workflows III

MM 20.5: Talk

Tuesday, March 19, 2024, 11:15–11:30, C 243

Peeling back the layers; Incorporating Dispersion Interactions and Quantum Mechanics at Clay Mineral Interfaces. — •Sam Shepherd, Gareth. A Tribello, and David. M Wilkins — Queen's University Belfast, Belfast, Northern Ireland, BT7 1NN

Clay minerals are complex layered materials whose unique structures allow them to be used in a range of processes. Accurately describing the interactions which take place between their layers however, remains a challenge. When studying these minerals theoretically, the need for accurate dispersion interactions is well understood, but accounting for the necessarily large system sizes and long timescales has hitherto limited theoretical study into these minerals.

To rectify this, we created a family of machine learned interatomic potentials (MLIPs), trained using dispersion corrected DFT calculations. We used these potentials to minimise computational expense while studying kaolinite for extended timescales. Thus, we have obtained structural and dynamical properties of kaolinite with previously unachievable levels of accuracy. Due to the nature of the interlayer interactions, we performed path integral molecular dynamics (PIMD) to include nuclear quantum effects (NQEs). This allowed us to perform simulations of kaolinite while treating the system fully quantum-mechanically.

We find that the addition of NQEs significantly impacts the dynamical properties of the system. This finding conclusively shows the need for full quantum mechanical approaches to gain a better appreciation of mechanistic processes like adsorption.

Keywords: Neural-Networks; Clay Minerals; Path Integral Molecular Dynamics; Density Functional Theory; Dispersion Interactions