SC EPSCoR awards five grants for research and collaboration programs

For Immediate Release
February 12, 2019

(Columbia, SC) The SC EPSCoR State Office is pleased to announce the recipients of the 2019 Grants for Exploratory Academic Research (GEAR) Program and GEAR Collaborative Research Program (GEAR CRP).

The goal of the Grants for Exploratory Academic Research (GEAR) Program is to encourage faculty researchers at South Carolina’s three comprehensive research universities (CRUs), Clemson University, the Medical University of South Carolina, and the University of South Carolina Columbia, to work in a collaboration of at least two faculty member teams per project to compete effectively for research funding to support the research clusters associated with the National Science Foundation (NSF) Research Infrastructure Improvement (RII) Track 1-Award entitled Materials Assembly and Design Excellence in South Carolina (MADE in SC)Multi-scale Modeling and Computation Core, Thrust 1 – Optical, Electrochemical and Magnetic Materials, Thrust 2 – Stimuli-responsive Polymeric Materials, and Thrust 3 – Interactive Biomaterials.

The goal of the GEAR CRP (Collaborative Research Program) is to encourage faculty researchers at the three South Carolina CRUs and all statewide predominately undergraduate institutions (PUIs) to build collaborative CRU/PUI academic research teams that will compete effectively for research funding. GEAR CRP grants build and enhance the network of scientists in the state that conduct research related to MADE in SC.

The vision of MADE in SC is to discover and establish new and sustainable approaches for the design and assembly of hierarchical materials at multiple relevant length scales that service South Carolina’s STEM research, education, and workforce needs and invigorate economic development.

Three GEAR awards with a maximum budget of $60,000 each have been made to six researchers:

Ramakrishna Podila – Lead PI (Clemson University) with MVS Chandrashankar (University of South Carolina)
Advancing Defect-Controlled Nonlinear Optical Properties for Nanocarbon-based Photonic Devices

This project proposes to realize a key fundamental element missing in the offering of all-photonic devices- a passive ultra wideband optical diode or isolator, which allows non-reciprocal transmission of light of any energy by breaking inherent time-reversal symmetry in the propagation of light. The challenge to improve the non-reciprocity factor of graphene-based optical diodes or isolators (which is a measure of contrast between light propagating in forward and reverse directions of an optical diode) can be addressed solely by understanding and achieving new ways to control carrier dynamics in graphene through defect engineering or heteroatomic doping. We hypothesize that: i) defect configuration rather than concentration is critical in the determination of carrier dynamics in graphene, ii) the unique linear energy dispersion relations of Dirac fermions in graphene impart equal effective masses for both electrons and holes, and there by eliminate the Auger-like electron-hole energy transfer pathways for carrier cooling that are predominant in other semiconductor systems, thus allowing one to increase photogenerated carrier lifetime. This project will result in the emergence of new fundamental knowledge based on the above hypotheses and strongly non-reciprocal optical diodes or isolators that can enable ultrafast lasers, photonic computing and efficient fiber optic communications.

Tarek Shazly – Lead PI (University of South Carolina) with Francis Spinale (UofSC School of Medicine, Columbia)
Optimization of Injectable Biomaterials for Cardiac Applications

Adverse left ventricular (LV) remodeling following a myocardial infarction (MI) is characterized by deleterious changes in LV geometry and function, most notably expansion of the MI region and increase in LV volume (dilation). Although the rate and magnitude of post-MI remodeling are established clinical indicators of disease progression, current standard-of-care is limited to symptom management. As such, there is a significant need to develop strategies to interrupt adverse post-MI remodeling. While diverse approaches for interruption have been proposed, including physical LV restraint and local delivery of bioactive agents, most seek to directly/indirectly modulate aberrant LV mechanics. One promising approach under broad investigation is the localized injection of drug/cell-eluting degradable biomaterials into the MI region. This goal of this project is to establish translatable strategies to optimize biomaterial design and delivery independently of incorporated bioactive agents.

Lin Zhu – Lead PI (Clemson University) with Yingjie Lao (Clemson University)
Intelligently Designed, Graphene Functionalized, Tunable Optical Metamaterials

The objective of this proposal is to investigate and demonstrate intelligently designed, graphene functionalized, tunable optical metamaterials. Through this research project, we will create multi-functional optical devices including tunable switchers, polarization convertors, absorbers, filters, and sensors, for a wide range of practical applications.

Two GEAR CRP awards with a maximum budget of $60,000 each have been made to five researchers:

F. Wayne Outten – Lead PI (University of South Carolina) with Nicholas Grossoehme (Winthrop University)
GEAR CRP: Building Stimuli-Responsive Ferritin Protein Nanocages for Biomaterial Applications

The iron-storage protein ferritin (Ftn) assembles into an octahedral protein cage structure that is 12 nm in diameter with a large central cavity 7-8 nm in diameter. Human Ftn (hFtn) is biocompatible, thermally stabile up to 100°C, and can be easily and highly expressed using low cost and large-scale microbial expression systems. The central cavity of Ftn can be used for encapsulation and delivery of metals, contrast agents for imaging, small molecule drugs for therapy, as well as smaller nanoparticles. Unmodified hFtn nanocages can enter cells through receptor-mediated endocytosis using native cell surface receptors while ligand conjugated Ftn can be selectively targeted to non-native receptors or other cell targets. Our long-term goal is to design, generate, and test a series of stimuli-responsive Ftn nanocages that are useful for biomaterials assembly and/or drug delivery. In this proposal, we will use a combination of analytical, biochemical, and biophysical techniques to characterize pH-responsive Ftn derivates thereby providing new insight into the principles for engineering bio-macromolecular assemblies for stimuli responsiveness.

Jianjun Hu – Lead PI (University of South Carolina) with Ming Hu (University of South Carolina) and Jie Ling (Claflin University)
Deep Learning for Discovery of Noncentrosymmetric Materials with Second-order Nonlinear Optical Behavior

This project aims to develop novel deep learning techniques to achieve fast and accurate computational prediction of nonlinear optical properties such as secondary harmonic generation (HSG) for high-throughput optical material screening and discovery. It will complement current computationally demanding first-principles based methods and the costly experimental approaches. The interdisciplinary project team is composed of a computer scientist specialized in machine learning, a computational materials expert, and an experimental optical materials investigator. The team will (1) develop graph convolutional neural networks (CNNs) for optical properties modeling by exploiting their automated hierarchical feature learning and non-linear mapping learning and multi resolution data; (2) integrate multi-resolution data and apply the proposed deep learning prediction models for high-throughput screening of binary and ternary noncentrosymmetric optical materials; (3) and conduct experimental verification of the predicted optical materials. This project will achieve integration of MADEinSC core MCC (modeling and simulation) and Thrust 1 (experimental study of magnetic and optical materials).

MADE in SC is supported by the National Science Foundation Award #OIA-1655740.