NCSI: Ab Initio Calculation for the Prediction of New Perovskite-based Solar Cell Materials using High-performance Computing

Status	Completed
Mentor Name	Kevin Brandt
Mentor's XSEDE Affiliation	Campus Champion and past Regional Campus Champion
Mentor Has Been in XSEDE Community	4-5 years
Project Title	Ab Initio Calculation for the Prediction of New Perovskite-based Solar Cell Materials using High-performance Computing
Summary	Hybrid organic-inorganic lead halide perovskites are of great interest in the scientific community due to their impressive power conversion efficiency for solar cell applications. However, despite numerous studies on their 3D structural properties, relatively little progress has been made in our understanding of their various properties, such as the role of hydrogen bonding in orthorhombic phases in the organic lead(halides). Theoretical approaches have been found to be very powerful predictive tools for exploring and "tailoring" new perovskites with desired properties. In this project, we'll use ab-initio density functional theory (DFT) and molecular dynamics (MD) methods to predict and study such properties extensively using high-performance computing and compare it with experimental results found at the Center for Advanced Photovoltaics at South Dakota State University, and elsewhere.
Job Description	This student will perform DFT, MD, and other related simulations using mainly Quantum Espresso, Gaussian 9, and MATLAB programs on the NSF funded Roaring Thunder high-performance cluster housed at the South Dakota State University High-Performance Computing Center. The student completing this project was already trained and began initial calculations during the Summer of 2020. The student will also write a paper/report on the research findings for publication in a scientific manuscript and/or oral/poster presentations.
Computational Resources	The student will work with the PI, Dr. Qiquan Qiao, 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 Roaring Thunder Cluster at the South Dakota State University in consultation with his mentor. The student also has access to Bridges at the Pittsburg Supercomputing Center (PSC) during Summer 2020.
Contribution to Community
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 regularly to ensure effective training. The student has also completed HPC Summer Boot Camp, Computational Chemistry, other training workshops, and webinars by XSEDE before and during summer 2020.
Duration	Semester
Start Date	08/17/2020
End Date	11/10/2020