Lennard Jones

The Lennard-Jones potential, a simple yet powerful model of interatomic interactions, remains a cornerstone of computational physics and chemistry. Current research focuses on leveraging machine learning, particularly graph neural networks and energy-based diffusion models, to improve the efficiency and accuracy of simulations based on this potential, including free energy calculations and molecular dynamics. These advancements enable faster and more scalable simulations of complex systems, impacting fields ranging from materials science (predicting thermal conductivity) to drug discovery (accelerated molecular dynamics). The development of novel algorithms, such as neural thermodynamic integration, further enhances the capabilities of Lennard-Jones-based modeling.