I am a postdoctoral fellow in the Department of Mechanical Engineering at Tufts University, working with Dean Qu of the School of Engineering. My research interest lies in developing and applying theoretical and computational models to study the mechanical behaviors of nanostructured materials across different length and time scales, with the combination of in-situ experimental characterizations. Particular emphasis is placed on translating atomistic insights into the coarse-grained continuum models to understand material behaviors and processes at the macroscopic level. The ultimate goal of my research is to guide experiments and rational designs of new materials with improved performance and reliability through predictive numerical modeling. My current research primarily involves chemo-mechanical modelings of lithium-ion battery materials for energy storage applications. My investigations on a broad range of high-capacity energy materials have provided us the opportunities to obtain atomistic understanding of degradation mechanisms in nanoelectrodes, which will pave the way toward the development of failure-resistant high-performance electrodes for the next-generation rechargeable batteries. The HPC cluster at Tufts provides a reliable computational platform that enables me to run multiple jobs across different length scales simultaneously, i.e., the molecular dynamic simulation at the atomic level, phase-field simulation at microscale, and finite element modeling at macroscale. With the HPC cluster, I can run the computationally expensive simulations with multiple CPUs, which are totally impossible for me to run on my office desktop, and thus the efficiency of my simulation work is highly promoted. In addition, with the various installed software and compilers on the cluster, I can also run some in-house codes and user subroutines (i.e., in C or Fortran) to meet my research requirements. Finally, the service and support from the HPC center has been very helpful for software installation, debugging.
The Tufts High Performance Compute (HPC) cluster delivers 35,845,920 cpu hours and 59,427,840 gpu hours of free compute time per year to the user community.
Teraflops: 60+ (60+ trillion floating point operations per second) cpu: 4000 cores gpu: 6784 cores Interconnect: 40GB low latency ethernet
For additional information, please contact Research Technology Services at tts-research@tufts.edu
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