The symposium will delve into recent breakthroughs at the intersection of data science and materials science, focusing on material structure design, autonomous synthesis, advanced characterization tools, computational simulations, and data analysis facilitated by machine learning approaches. This symposium will unfold across four distinct segments. 1) Materials Design and Synthesis: This first segment delves into the realm of materials design, with a specific focus on macromolecular structures and functions. Contributions exploring the design of functional materials and autonomous synthesis, high-throughput synthesis are particularly encouraged. 2) Characterization Tools at the Solid-Liquid Interface: The second part is dedicated to the utilization of characterization tools, especially those performed at the solid-liquid interface. This includes in situ/operando microscopy, spectroscopy, and diffraction/scattering techniques. 3) Simulation and Theory Exploration: The third segment introduces recent advances in the simulation and theory side of materials science, with a special emphasis on data science-transformed modeling techniques and computation-guided material discovery. 4) Nanomaterials and Nanodevices: The fourth part explores the realm of nanodevices, encompassing memristors, artificial synapses, sensors, and batteries. Contributions in all parts are encouraged to present new results in materials design, functionalization, synthesis, characterization, and simulation. The symposium places a particular spotlight on functional materials design and innovative data analysis methods. Fundamental studies based on simulation and other approaches are also welcomed. Additionally, research on nanodevices is highly welcomed.

interface self-assembly