NCSI: A First-principles Investigation of V2O5 as a Sensor

Status	Completed
Mentor Name	Hartwin Peelaers
Mentor's XSEDE Affiliation	Startup Allocation/Research Allocation
Mentor Has Been in XSEDE Community	4-5 years
Project Title	A First-principles Investigation of V2O5 as a Sensor
Summary	Using density functional theory, as implemented in the VASP code, and python scripts based on the Atomic Simulation Environment (ASE), we will investigate if V2O5, a layered material, can be used as a sensor material for simple molecules, such as NH3, CO, etc. Some experiments reveal that that should be possible, and in this project we will unravel the mechanisms at an atomic level.
Job Description	The student will use python scripts, using the Atomic Simulation Environment (ASE) framework, to perform simulations using density functional theory (DFT) of investigate the mechanisms of adsorption and desorption of small molecules (CO, NH3, H2O, etc.) on V2O5 surfaces. The framework initially hides much of the quantum mechanical nature and the details of the DFT simulations (using the VASP code). This allows the student to focus on the programming and analysis first. The student will learn python (object oriented code and parallelizing of python loops), and version control using git. Calculations to run will be saved to a database, and the obtained results will also be saved in a database. The student will learn to interact with this database. The actual DFT calculations will be performed on the XSEDE machines. Each individual calculation will be parallelized. The student will learn how to interact with HPC computing facilities and their queuing system, and will write basic python code to do these interactions automatically. This will also require to write code to correct common occurring errors. As the student progresses, more of the underlying calculations will be explained.
Computational Resources	All underlying DFT calculations will be performed on the XSEDE machines. A typical DFT job will require 1-4 nodes and 24-48 hours of running time.
Contribution to Community
Position Type	Learner
Training Plan	The student will learn how to code in python, basic solid state physics (as needed), basic quantum mechanics (later on in the semester), basic linux shell (cd, mkdir, cp, ls, etc.), and interact with HPC resources (ssh, scp, slurm, etc.). This learning will occur through 1-on-1 mentoring with the PI (in person or through Zoom, depending on the COVID19 situation), combined with online tutorials and specific tasks (e.g., write a simple python script to do x). Once initial results are obtained, the student will study these based on guiding questions. The more experienced the student becomes, the more open questions and tasks will become. This will introduce the student gradually to more aspects of the scientific process (making hypothesis, designing calculations to test these, analyse results, refine hypothesis, and so on). The student will also take part in regular group meetings to learn about other group members' research and discussions about that research. Given that this is a "Learner" position, no advance knowledge is required. At the end of the project, the student will have acquired many new skills, and a broader knowledge of materials science and high-performance computing.
Student Prerequisites/Conditions/Qualifications	/
Duration	Semester
Start Date	09/01/2020
End Date	12/01/2020