NCSI: Computational Study of Covalency in Trivalent Actinide and Lanthanide Complexes with Soft-donor Ligands

Status	Completed
Mentor Name	Zhiyong Zhang
Mentor's XSEDE Affiliation	Campus Champion
Mentor Has Been in XSEDE Community	4-5 years
Project Title	Computational Study of Covalency in Trivalent Actinide and Lanthanide Complexes with Soft-donor Ligands
Summary	Besides the lanthanides, fission of uranium or plutonium by neutron irradiation in a nuclear reactor also generates highly radioactive "minor actinides" (MA), including Np, Am, and Cm, that constitute the main long-term radiation hazards. To reduce the cost for the long-term disposal of nuclear wastes, the M's are separated from the lanthanides. The chemical similarity between trivalent actinides and lanthanides makes the partitioning extremely challenging. To understand the underlying principles that govern the selective separations of actinides from lanthanides, this project will carry out Ab Initio calculations to obtain the optimal structures, energetics, and electronic properties of the trivalent actinide and lanthanide complexes with bis(methyl)dithiophosphinic acid, (CH3)2PS(H)S.
Job Description	We have already carried out a large number of calculations for this study. (1) The student will carry out further calculations needed for the completion of the project. (2) The student will help with the gathering and interpretation of results. (3) The student will help with development of python and bash scripts for automatic extraction and plotting of results from the outputs of calculations. During this project, the student will be well trained for and develop expertise in using modern HPC resources to carry out the state of the art computational chemistry calculations, a critical component of the essential skills in a graduate research career in many important areas in chemistry, physics, material sciences, and biological sciences.
Computational Resources	The students will have access to computational resources at XSEDE (stampede and Bridges2) and at Stanford University.
Contribution to Community	It is a great opportunity for students to develop skills that are critical for a successful career in graduate studies, as well as a career in and/or related to HPC. The work is related to nuclear energy applications that is critical to address the nuclear waste issues as well as to the development of reliable renewable energy sources. The project will contribute to the development of advocates for XSEDE, increased awareness and utilization of XSEDE resources, as well as the development of future workforces for XSEDE and related work.
Position Type	Apprentice
Training Plan	(1) Learn the usage of HPC resources for the calculations. (2) Learn to set up, configure, run, interpret results for computational chemistry calculations. (3) Learn and develop python/bash scripts for output results for computational chemistry calculations. Learn to use the important computational chemistry programs. (4) Contribute to the draft of scientific publications.
Student Prerequisites/Conditions/Qualifications	general knowledge of chemistry. Experiences in computational sciences are highly desired. Previous programming experiences and ability to program or the ability to learn to program in python and/or bash scripts are important.
Duration	Semester
Start Date	01/20/2022
End Date	04/20/2022