Award Data

To advance a strong and economical biofuels and bioproducts industry, tools are needed for breeding microalgae to improve phenotypes of commercial interest, including biomass yield, culture stability, harvestability, and accumulation of valuable compounds. This project aims to increase biomass feedstock yields by the phototrophic green alga Scenedesmus obliquus by using classical breeding approach ...

This project will develop a flexible longitudinal electron optical system based on high-precision radio-frequency cavities for short and intense electron bunch compressions, both in the energy and time domains. The proposed system is designed to be insertable into an existing transmission electron microscope column to upgrade its temporal resolution. Active phase-space control enables broad ranges ...

Trabus Technologies (TRABUS), working with Louisiana State University (LSU), will develop a predictive analytics-based US Inland Waterways Voyage Planning Analysis tool to help vessel traffic managers, tow boat pilots, and river lock operators maximize transport logistic resources. This tool will use current and forecasted hydrographic, meteorological, lock status, and Marine Safety Information to ...

The discovery of large shale gas reserves in recent years has resulted in the reduction of natural gas price and a need to develop new applications for the available resource. Upgrading shale gas to liquid fuels which are more easily transportable and have greater economic value can result in significant benefits to the US. Coupled with this challenging problem the DOE has a goal of further develo ...

Ensuring adequate agricultural productivity in the face of an increasing human population is a major concern with implications for both production of bioenergy products (Jones and Hinsinger, 2008) and global food security. Increasing agricultural productivity requires a stronger understanding of soil biogeochemical processes that impact plant nutrient availability. We propose development of an inn ...

Signature Research, Inc. (SGR) and Michigan Technological University (MTU) propose a Phase I STTR effort to develop a learning algorithm which exploits the spatio-spectral characteristics inherent within IR imagery and motion imagery.Our archive of modelled and labeled data sets will allow our team to thoroughly capture the variable elements that will drive machine learning performance.The overall ...