Data management plan for the grant, "Collaborative Research: PIC: Slow Wave Enhanced Electrooptically Tuned Michelson Interferometer Biosensor for On-Chip Polarization Interferometry."

Data management plan for the grant, "Low-Energy Atomic Processes Including Ones Involving a Positron." The proposed research in theoretical atomic physics involves few-body systems of charged particles, especially ones that involve the antiparticle of the electron, which is a positron. One of these systems is the positronium negative ion, which is comprised of two electrons and a positron. The exotic positronium atom is similar to the conventional hydrogen atom, but the positive charge in the atom is a positron rather than a proton. The proposed studies of these few-body charged systems will support international collaborations with scientists in the UK and Japan.

Data management plan for the grant, "Development of advanced biocatalyst tools and resources to enable biogas-based biomanufacturing."

Data management plan for the research grant, "Collaborative Research: Using Uncertainty Quantification and Validated Computational Models to Analyze Pumping Performance of Valveless, Tubular Hearts." This project will develop a computational model of the essential features of the circulatory system: the electrical activity of the heart, muscle contractions of the tube walls, and the fluid-structure interactions of the heart walls and blood within. This computational framework aims to be faithful to that of a real, model animal (tunicate, or sea squirt). The model will then be analyzed with mathematical tools to determine the physical limits of the pumping system. Results of this project will improve the understanding of human heart development at the earliest stages. Also, it will point to how the large, multi-chambered hearts of vertebrates could have evolved from smaller structures.

Data management plan for the grant "Elucidating Cyclic Fatty Acid Biosynthesis and Compartmentalization to Improve Cottonseed Value." Cotton is an important oilseed crop in the U.S. economy. Cotton seed and other vegetative tissues produce unusual chemicals called cyclic fatty acids that have wide-ranging potential uses from high-value industrial properties to nutrition-oriented uses. This project focuses on identifying genes that contribute to the production and storage of these high value bioproducts.

Data management plan for the grant, "Building a Team for EXtragalactic AStrophysics (TEXAS) in the Dallas-Fort Worth Metroplex". The project will build a new partnership between the University of North Texas (UNT), an R1 Minority-Serving Institution (MSI)/ Hispanic-Serving Institution (HSI), and the University of Texas at Dallas (UTD). During the pilot phase, the team will establish a post-baccalaureate bridge program and organize monthly colloquia and annual symposia to broaden the participation of underrepresented groups in astronomy.

Data management plan for the grant, "Connecting Galaxies and Supermassive Black Holes: Meso-scale Simulations of Multiphase Accretion Flows." It proposes to study how gas flows onto the supermassive black holes in massive galaxies and galaxy clusters. They will perform numerical simulations with a nested zoom-in technique, focusing on the mesoscale accretion flows from the Bondi radius to hundreds of Schwarzschild radii. They will predict the mass flux of different phases, as well as their angular momentum and magnetic flux.

Data management plan for the research grant, "Using uncertainty quantification and machine learning techniques to study the evolution of odor capture." This research proposes the application of uncertainty quantification (UQ) and machine learning (ML) to a CFD model of odor capture to understand the role of hair-array morphology, kinematics, and fluid environment in odor capture. The combination of CFD modeling and UQ&ML techniques can map out the performance space under which these chemosensory hair arrays operate and the relative sensitivity of each parameter of odor capture to construct a global, quantitative understanding of how parameters control odor-capture performance. Furthermore, this analysis can eliminate parameters that have no influence on odor capture, extracting the root principles of odor capture and providing a more efficient way to construct bioinspired devices for chemical detection. This work is of interest to the Army for extracting design principles that can be used for biomimetic and/or bioinspired devices for sensing hazardous chemicals in the environment (e.g. explosives).

Data management plan for a grant seeking to analyze existing support structures for transfer students in Chemistry between the University of North Texas and Dallas College.