SCALE stands for Simulation of Complex Systems Across Length and Energy. We use theory, molecular simulation, and machine learning to understand how complex materials and biological systems behave, and to turn that understanding into predictive design principles.
We develop simulation, physics-based modelling, and machine-learning approaches for two focus areas: electrolyte design for sodium-metal and sodium-sulfur batteries, and gene regulation through genome biophysics, DNA packing, and bioinformatics-informed physical models.
We design liquid, solid, and composite electrolytes for sodium-metal and sodium-sulfur batteries by connecting molecular design, solvation structure, interfacial stability, ion transport, and machine-learning-guided materials discovery.
ExploreWe combine polymer physics, soft-matter physics, kinetic modelling, bioinformatics, and machine learning to understand DNA packing inside the nucleus, enhancer-promoter contacts, TADs, gene regulation, and physics-based models from bioinformatics data.
Explore
