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materials-science

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Aya Nawano CAREERS, ACCESS CSSN
Christopher Bl… Campus Champions
Balamurugan Desinghu ACCESS CSSN, Campus Champions, CAREERS, Northeast
Fernando Garzon ACCESS CSSN
Yu-Chieh Chi Campus Champions
Jonathan Lyon At-Large, Campus Champions, Kentucky, ACCESS CSSN
Od Odbadrakh ACCESS CSSN
Justin Oelgoetz Campus Champions
Paul Rulis Campus Champions
Sean Anderson Campus Champions
Simon Delattre
Swabir Silayi Campus Champions
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Exploring Small Metal Doped Magnesium Hydride Clusters for Hydrogen Storage Materials
Murray State University

Solid metal hydrides are an attractive candidates for hydrogen storage materials. Magnesium has the benefit of being inexpensive, abundant, and non-toxic. However, the application of magnesium hydrides is limited by the hydrogen sorption kinetics. Doping magnesium hydrides with transition metal atoms improves this downfall, but much is still unknown about the process or the best choice of dopant type and concentration.

In this position, the student will study magnesium hydride clusters doped with early transition metals (e.g., Ti and V) as model systems for real world hydrogen storage materials.  Specifically, we will search each cluster's potential energy surface for local and global minima and explore the relationship of cluster size and dopant concentration on different properties.  The results from this investigation will then be compared with related cluster systems.

The student will begin by performing a literature search for this system, which will allow the student to pick an appropriate level of theory to conduct this investigation.  This level will be chosen by performing calculations on the MgM, MgH, and MH (M = Ti and V) diatomic species (and select other sizes based on the results of the literature search) and comparing the predictions with experimentally determined spectroscopic data (e.g., bond length, stretching frequency, etc.).  The student will then perform theoretical chemistry calculations using the Gaussian 16 and NBO 7 programs on the EXPANSE cluster housed at the San Diego Supercomputing Center (SDSC) through ACCESS allocation CHE-130094.  First, this student will generate candidate structures for each cluster size and composition using two global optimization procedures.  One program utilizes the artificial bee colony algorithm, whereas the second basin hoping program is written and compiled in-house using Fortran code. Additional structures will be generated by hand from our prior knowledge.  All candidate structures will then be further optimized by the student at the appropriate level determined at the start of the semester.  Higher level (e.g., double hybrid density functional theory) calculations will also be performed as further confirmation of the predicted results. Various results will be visualized with the Avogadro, Gabedit, and Gaussview programs on local machines. 

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People with Expertise

Balamurugan Desinghu

Rutgers, the State University of New Jersey

Programs

ACCESS CSSN, Campus Champions, CAREERS, Northeast

Roles

mentor, researcher/educator, research computing facilitator, cssn, Consultant

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Expertise

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Parameshwaran Pasupathy

Rutgers University - New Brunswick

Programs

ACCESS CSSN, CAREERS

Roles

student-facilitator

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Expertise

Jonathan Lyon

Murray State University

Programs

At-Large, Campus Champions, Kentucky, ACCESS CSSN

Roles

mentor, researcher/educator, cssn

Expertise

People with Interest

Yongan Tang

North Carolina Central University

Programs

Campus Champions

Roles

cssn

NCCU

Interests

Morgan Newton

Santa Monica College

Programs

ACCESS CSSN

Roles

student-facilitator

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Interests

Mariavictoria Moreno

Programs

ACCESS CSSN

Roles

student-facilitator

Placeholder headshot

Interests