Computational Materials Science
Materials play an essential role in modern technologies. However, the search for new materials with improved properties is never trivial. Years of efforts are often necessary for materials selection and testing before a possible commercialization. For example, the first lithium ion battery was demonstrated in the 1970s, while the first commercial product appeared in 1991, almost 20 years later.
Computational materials science, a relatively new branch in Materials Science and Engineering, has the potential to greatly expedite materials discovery. Advanced computational algorithms have been increasingly employed to design novel materials and structure and predict their properties. In other words, the tedious materials selection and testing process can now be performed computationally, resulting in greatly improved efficiency and much reduced cost.
Dr. Ying Ma, assistant professor of Materials Science, is actively engaged in computational materials research focusing on advanced energy materials. Topics of research include computational screening of novel electrode materials for lithium ion batteries, supercapacitors, and solar cells.
Cathode materials for Lithium-Sulfur Batteries
Our smartphones, laptops, tablets, and many other consumer devices are often powered by Lithium Ion batteries. During discharge of the battery, an electrochemical reaction takes place at the cathode that converts the chemical energy stored in the chemical bonds into electrical energy. Unfortunately, the energy densities of commercial cathode materials are very limited (~300 mAh/g). Sulfur, one of the most abundant elements on earth, offers a theoretical capacity of 1672 mAh/g, highest among all known solid cathode materials. However, the electrochemical processes in sulfur are extremely complicated and are not well understood, hindering a successful commercialization. Until today, there is no commercially available lithium sulfur batteries. To reveal the fundamental reaction mechanisms in sulfur, Dr. Ma and his research students studied the initial reactions that take place at the cathode/electrolyte interfaces using sophisticated computational tools. The team recent presented their research findings on the 229th Electrochemical Society Meeting.
The Blugold Supercomputing Cluster (BGSC), funded by the Blugold Commitment Differential Tuition, provides the supercomputing power necessary for computational materials research. The BGSC consists of 25 computer nodes with 372 CPU cores, 31,744 GPU cores, and 56 TB of disk space. The InfiniBand network installed on BGSC provides high throughput and low latency in internode communication, enabling high parallel efficiency for large scale calculation involving multiple compute nodes.