Session

DescriptionUnderstanding the intricate interplay between a material's structure and its macroscopic properties is essential in materials science, particularly for soft matter systems like polymers, composites, and colloidal systems. The complexity arises from the relevant length and timescales spanning nanometers to meters and picoseconds to years. Properties such as mechanical strength, thermal conductivity, and responsiveness to external stimuli are closely linked to molecular and macromolecular structures, introducing challenges in predicting overall behavior. Scattering experiments from large-scale neutron or X-ray facilities, coupled with benchtop techniques like microscopy, rheology, and spectroscopy, offer insights into materials' structures. Yet, data analysis and interpretation of experiments and simulation results often requires computational assistance. In this minisymposium, diverse researchers showcase computational tools, such as molecular dynamics simulations, numerical computations based on physical theories, and deep/machine learning techniques for investigating soft matter. These tools bridge experimental observations and theoretical predictions, facilitating the exploration of both structure and dynamics in soft matter systems. Serving as a bridge between experimental and theoretical realms, these computational tools contribute to a multidisciplinary effort, enhancing our understanding of fundamental material aspects and opening avenues for innovative applications across diverse industries.