Call for Papers

Please contact the symposium organizers with questions.

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.

Topics will include:

• Functional materials design
• In situ/operando spectroscopy, diffraction, and scattering methods
• Atomistic and coarse-grained simulations
• Autonomous synthesis
• Advanced scanning probe methods
• Simulations of interfacial crystal growth or assembly pathways
• High-throughput synthesis
• New data processing, analysis, and mining methods for large in-situ datasets
• Big data and machine learning
• Nanoscale materials and Nanodevices

Invited Speakers (tentative):

• Paul Ashby (Lawrence Berkeley National Laboratory, USA)
• François Baneyx (University of Washington, USA)
• Carlos Bassani (Friedrich-Alexander-Universität Erlangen-Nürnberg, Germany)
• Guilherme de Vilhena (Instituto de Ciencia de Materiales de Madrid, Spain)
• Mingdong Dong (Aarhus University, Denmark)
• Julia Dshemuchadse (Cornell University, USA)
• Kristen Fichthorn (The Pennsylvania State University, USA)
• Oleg Gang (Columbia University, USA)
• Ricardo Garcia (Instituto de Ciencia de Materiales de Madrid, Spain)
• Michael Gruenwald (The University of Utah, USA)
• Michael Howard (Auburn University, USA)
• Yu Huang (University of California, Los Angeles, USA)
• Fang Jiao (Institute of Physics, Chinese Acadamy of Sciences, China)
• Xuan Mu (The University of Iowa, USA)
• Alex Noy (Lawrence Livermore National Laboratory, USA)
• Wengen Ouyang (Wuhan University, China)
• Kelly Powderly (Washington University in St. Louis, USA)
• Lilo Pozzo (University of Washington, USA)
• Miquel Salmeron (Lawrence Berkeley National Laboratory, USA)
• Mitra Taheri (Johns Hopkins University, USA)
• Tom Truskett (The University of Texas at Austin, USA)
• Tiffany Walsh (Deakin University, Australia)
• Younan Xia (Georgia Institute of Technology, USA)
• Xiao-Ying Yu (Oak Ridge National Laboratory, USA)
• Xiao Zhao (Lawrence Berkeley National Laboratory, USA)

Symposium Organizers