NCSI: First Principles Calculation of Binding Energies of Li/Metal Interfaces Using Hybrid Functionals in DFT

Status	Completed
Mentor Name	Kevin Brandt
Mentor's XSEDE Affiliation	Campus Champion
Mentor Has Been in XSEDE Community	4-5 years
Project Title	First Principles Calculation of Binding Energies of Li/Metal Interfaces Using Hybrid Functionals in DFT
Summary	The primary goal of this project is to investigate the surface chemistry and the mechanical and ion-transport properties of several Li: Metal, Li: Metalloid interfaces using Density Functional Theory (DFT) – for applications as Li-anode in the Li-ion batteries. This research will result in a comprehensive summary of the binding of energies between Li, Na, and graphite with other metallic and non-metallic thin films. Besides performing a systematic study for each of the systems using PBE functionals, we will also use hybrid functional, PBE0, to further increase the accuracy of the results, that were not reported thus far. In addition, to knowing interfaces, it will also include novel systems which not yet studied, either using PBE or PBE0. This investigation will add new knowledge to the field of Li-ion batteries, which experimentalists may use as a guide to fabricate high energy-density Li-ion batteries in the future, which can also extend the life cycling life of the anodes.
Job Description	The student will perform the systematic calculation of the Li: metal, metalloids, semiconductors, and PMNS interfaces using DFT as implemented in Quantum Espresso. A series of optimized lattice structure modeling, convergence testing, ion/cell relaxation, band structure, and atom projected density of states calculations will be also performed. The student will also import the previous codes in this project and cross-validate their results using CP2K. Finally, the student will write a paper/report on research findings for publication in a scientific manuscript and/or oral/poster presentations.
Computational Resources	The student will work with the PI, Dr. Yue Zhou, and along with a group of graduate students (experimentalists) to validate the simulation results with lab experiment data. The simulations will be performed on the NSF-funded Roaring Thunder Cluster facility housed at the South Dakota State University.
Contribution to Community	This position will add new knowledge and possible innovation associated with the subject matter.
Position Type	Intern
Training Plan	The student was trained on parallel programming using OpenMP and MPI. The student is also experienced in running DFT and MD simulations using Quantum Espresso and Gaussian 9 and MATLAB programs on a Linux workstation from previous semesters and has become relatively independent. This semester, the student will be trained to gain fluency in SLURM and implement parallel algorithms in various DFT and MD codes to efficiently run jobs on the cluster independently. And the student will mainly focus on a scientific literature review, running regular DFT simulations/experiments on the cluster, and meeting with the PI and mentor on a weekly basis to get advice/directions regarding the plan and progress of the research.
Student Prerequisites/Conditions/Qualifications	South Dakota State University will work with the student on a regular basis to ensure effective training. The student has also completed HPC Summer Boot Camp last year, Computational Chemistry, other training workshops, and webinars by XSEDE.
Duration	Semester
Start Date	01/10/2022
End Date	05/06/2022