NCSI: Quantum Simulation of Two-dimensional Materials

Status	Completed
Mentor Name	Zlatan Aksamija
Mentor's XSEDE Affiliation	Startup and Education Allocations
Mentor Has Been in XSEDE Community	4-5 years
Project Title	Quantum Simulation of Two-dimensional Materials
Summary	In this summer position, the student will simulate two-dimensional materials using time-dependent density functional theory (TDDFT). The goal of the project is to use our in-house TDDFT code NESSIE in order to study the electronic and vibrational properties of graphene nanostructures and their interactions with other materials such as a silicon dioxide substrate.
Job Description	This position will place the student intern at the center of an active collaboration between Profs. Aksamija and Polizzi in the Nanoelectronics Theory and Simulation Lab at the University of Massachusetts Amherst. The student will develop skills in high-performance computing and scientific simulation through hands-on work on our time-dependent density functional code NESSIE. The student will perform simulations, first on the Massachusetts Green High-Performance Computing Cluster and then scale up to XSEDE. The simulations will aim to include hundreds of atoms in a fully quantum (all-electron) TDDFT treatment of graphene flakes supported on a silicon dioxide substrate. The goal of the simulations is to capture the atomic vibrations (phonons) and their interactions with the substrate, in order to quantify the transfer of heat from the graphene to the substrate.
Computational Resources	The student will have access to XSEDE to run simulations, specifically the Density Functional Theory code Quantum Espresso, through my Educational Allocation. I will apply for a research allocation to follow on from the earlier Startup Allocation, which will give us additional access to XSEDE.
Contribution to Community
Position Type	Apprentice
Training Plan	The student should have basic programming skills. These skills will be further developed by interacting with an active research group of 5 PhDs and 3 MS students, all of whom are active in computational science and HPC. This position will also require some background in solid-state electronics, as well as some programming skills in either Python, C/C++, Fortran, or Matlab. The apprentice will gain valuable skills in both parallel/high-performance computing and numerical simulation in the context of semiconductor device engineering and applied nanoscience. Work done during this apprenticeship will have a strong impact both on the environment (through developing more energy efficient nanoelectronics) and on the broader scientific computing community (by sharing both the codes and the results of the work on-line and through publications).
Student Prerequisites/Conditions/Qualifications
Duration
Start Date	05/25/2019
End Date	08/25/2019