Conveners
Parallel Session A: AI-Driven Materials Discovery, Energy Systems, and Computational Modeling
- Arunima Singh (Arizona State University)
Liquid electrolytes play a pivotal role in governing the performance, safety, and longevity of lithium and sodium ion batteries. However, designing optimal electrolytes remains a complex challenge due to the need to simultaneously satisfy multiple criteria, including high ionic conductivity, broad electrochemical stability, low viscosity, chemical compatibility with electrodes, and thermal...
Data centers will consume 9% of U.S. electricity generation annually by 2030 according to the Electric Power Research Institute. There are two energy-related challenges for building AI data centers with a greater capacity: a shortage of electricity and the need to reduce carbon emissions. Small modular reactors (SMRs) may solve both issues by co-location with data center campuses. Compared to...
Recent advances of machine learning interatomic potentials (MLIPs) have improved both the accuracy and scalability of energy and force predictions in chemical systems for many practical applications. Here we explore the combination of MLIPs with state-of-the-art ab initio theory of thermal transport, which requires accurate estimations of higher-order derivatives of the potential energy...
Moiré superlattices, formed by stacking layered 2D materials with a twist in orientation, have emerged as a new platform for exploration of new physics and exotic quantum phenomena. The twist-angle dependent moiré effects and superlattice potentials offer a new route in materials design and quantum engineering. However, a direct prediction of the superlattice potential remains challenging due...
