This NSF-funded project establishes a Research Experience for Undergraduates (REU) in Interdisciplinary, Multiscale Materials Modeling (I3M) at the University of Louisville (UofL) specifically focusing on Computational Chemistry and Molecular Dynamics methods and their application to materials and biological and biomimetic systems. This site will host 9 undergraduate students (Fellows) each summer from 2021 to 2023 at the University of Louisville located in Louisville. KY. It is not expected that REU fellows would have this background prior to their summer internship. Fundamentals of computational chemistry and molecular simulations coupled with hands-on computer laboratory training will be provided at the start of the REU program. Additional training will be provided by faculty mentors and participating graduate students as pertains to the specific REU project. Eighteen faculty members from the SPEED School of Engineering (Chemical Engineering, Mechanical Engineering, Bioengineering), Chemistry, Physics, and Medicine have provided 15 projects from which the REU Fellows can select. Participating Faculty Mentors are identified in the section on REU Faculty Mentors and Departmental Affiliations. All 15 projects are listed in the following section on Available REU Projects. REU Fellows will have the opportunity to become proficient in a particular method associated with their selected project.
The research focus of our REU Site is Multiscale Materials Modeling. The 15 projects utilize different computational approaches to address focused projects offered by experienced faculty members representing multiple disciplines. In addition to working with project faculty, REU Fellows will interact with graduate students pursuing PhD degrees. The REU Fellows will be introduced to a variety of different computational methods such as Computational Chemistry (quantum mechanics), Molecular Dynamics, and Finite Elements that span the range of size and time domains as illustrated in Figure 1 and discussed briefly in the following sections. Individual REU Projects that utilize one or more specific computational approach are identified in each of the following sections.
uses different approaches to obtain an approximate solution to the classical SchrÖdinger wave equation that can provide valuable information about individual molecules or small molecular clusters (small scale). Computational Chemistry methods include atomistic approaches such as first principles or ab initio methods, density function theory (DFT), and semiempirical approaches that require experimental parameterization but have the advantage of being computationally quicker and can be used to characterize larger molecules, such as proteins; however, results may be less accurate than achieved using ab initio methods. Molecular properties that can be obtained using Computational Chemistry include molecular geometry, conformation energies, band gaps, UV and IR spectra, dipole and quadrupole moments, and charge distribution. Programs such as Gaussian provide a graphical user interface (GUI) that facilitates computations. Gaussian and its graphical user interface (GUI), GaussView, will be discussed with hands-on training during the first week of the REU program. Projects: 1, 2, 6, 11, 15
(MD) lies at the next level of scale. MD simulations enables study of larger molecular structures whose conformational and diffusional properties cover a longer size and time range as was illustrated in Figure 1. In contrast to Computational Chemistry methods, Molecular Dynamics and related Monte Carlo methods can model a broad range of molecular size to enable molecular level characterization of polymers, zeolites, DNA, and proteins. Figure 3 shown a MD simulation of a gramicidin channel (colored purple) sitting in a lipid bilayer membrane (colored green). The solid spheres show water molecules passing through the membrane channel.
Projects: 1, 2, 3, 5
Methods lie at the far range of size and time domains as was illustrated in Figure 1. These methods provide a bridge between Molecular Dynamics and experiment. They use computational methods distinct from Computational Chemistry and Molecular Dynamics. Figure 4 illustrates how medical imaging of arteries can be used to develop system models to study blood flow using Computational Fluid Dynamics.
|Delaina Amos||Chemical Engineering||Associate Professor|
|Eric Berson||Chemical Engineering||Professor|
|Albert R. Cunningham||Medicine||Associate Professor|
|Hermann B. Frieboes||Bioengineering||Associate Professor|
|Joel R. Fried||Chemical Engineering||Professor|
|Gautam Gupta||Chemical Engineering||Associate Professor|
|Vance W. Jaeger||Chemical Engineering||Assistant Professor|
|Chakram S. Jayanthi||Department of Physics and Astronomy||Chair Person & Professor|
|Pawel M. Kozlowski||Chemistry||Chair Person & Professor|
|Jinjun Liu||Chemical Engineering||Associate Professor|
|Badri Narayanan||Mechanical Engineering||Assistant Professor|
|Joshua Spurgeon||Conn Center for Renewable Energy Research||Theme Leader, Solar Fuels|
|Jill Steinbach-Rankins||Bioengineering||Associate Professor|
|Lee Thompson||Chemistry, College of Arts & Science||Assistant Professor|
|John O. Trent||James Graham Brown Cancer Center, School of Medicine||Professor|
|Stuart Williams||Mechanical Engineering||Associate Professor|
|Jerry Willing||Chemical Engineering||Interim Chairperson & Professor|
|Ming Yu||Physics||Associate Professor|
|Application Deadline||Friday, April 27, 2022|
|Notification of Selection||Friday, May 4, 2022|
|REU Program Starts||Monday, May 16, 2022|
|Research Poster Competition Week||Friday, July 22, 2022|