Dr. Muratahan Aykol is a Senior Research Scientist in the AMDD program. At TRI, he currently leads a division project on developing a computational platform for autonomous materials discovery. His research combines solid-state chemistry and physics, ab-initio computations and machine learning to solve complex challenges in materials science including predictive synthesis of inorganic compounds, closed-loop optimization of material properties and development of better energy storage systems.
Prior to TRI, Dr. Aykol was a postdoctoral fellow at Lawrence Berkeley National Laboratory where he developed first-principles methods addressing synthesizability and corrosion, and software for automating simulations. He received his Ph.D. from Northwestern University in Materials Science and Engineering, where he worked on computational design and discovery of novel materials including electrodes, electrolytes and protective coatings for lithium-ion batteries, and designed high-throughput materials screening methods. He has authored more than 50 peer-reviewed publications and is an inventor on more than a dozen granted or pending patents in the United States.