Data management plan for the grant, "Exploring thermal properties of nanoscale wide bandgap semiconductors via ultrafast thermal-emission spectroscopy." In this project, we aim to develop a new thermometrology technique based on ultrafast thermal emission to directly and accurately measure thermal properties of thin-film wide bandgap semiconductors.

Data management plan for the research grant "Generating pathogen- / pest-resistant non-GMO cotton through targeted genome editing of oxylipin signaling pathways."

Data Management Plan for the research project: Metal Organic Frameworks Containing Frustrated Lewis Pairs for Hydrogen Storage at Ambient Temperature. Research to design, synthesize, and characterize novel sorbent materials for hydrogen storage. The materials are based on a Metal-Organic Framework and incorporate Frustrated Lewis Pairs (FLP-MOF). The project seeks to optimize the hydrogen storage capacity of the FLP-MOF systems at ambient temperature and under high pressure.

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, "Structural and mechanistic studies of oxalate catabolism." Biologically derived oxalic acid has been shown to have a negative impact on crop production and human health. Oxalate present in plant foods can decrease their nutritional value by binding to calcium and rendering that calcium unavailable for nutritional absorption. This project will study the structure and function of key enzymes in oxalate turnover to understand their biological functions and mechanisms, facilitating metabolic engineering of plants toward improving nutritional quality and production of plant derived foods.

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 Novel Approaches to Earth-abundant Methane Catalysis." Research on catalytic cycles for C–H activation and functionalization of light alkanes based on the CMD (concerted metalation deprotonation) mechanism will be modeled for Earth-abundant metal dicarboxylates and related complexes. The impact of inner and outer coordination sphere effects upon catalytic cycles for light alkane functionalization will be assessed using computational chemistry techniques. The aforementioned studies will be leveraged to identify promising, synthetically feasible lead catalysts for experimental collaborators.

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 grant, "Fatty Acid Amide Hydrolases and Chemical Communication in Plants." Research seeking to understand how an evolutionarily-conserved group of plant enzymes utilizes chemical signals to regulate growth and to influence their microbial environment. Specific research aims include the discovery of new enzymes and their substrate molecules that act as communication signals. Broader applications of this research may offer new strategies to enhance agricultural outputs by manipulating plant-microbe interactions in crop and soil systems.

Data management plan for the grant, "Encapsulated perovskite in NiO nanotube for topological meta-photonic devices." Research studying meta-photonic devices with high absorption and topological photonic devices using encapsulated perovskites in NiO nanotubes. The goal is to achieve high-efficiency solar cells and electrically pumped laser in perovskite/NiO nanotubes patterned in the graded photonic super-crystal. The success of this project will lead to high-efficiency integrated lasers and solar cell devices. It also enhances the abilities in the education arena by enriching program offerings in nanotechnology, clean-energy, and photonics technology.

Data management plan for the grant, "Collaborative Research: A Systematic and Comprehensive Study of Black Hole-Driven Turbulence in Massive Galactic Systems." This research team has developed a technique to measure gas turbulence in systems hosting giant central black holes and will directly evaluate the viability of this mechanism using a large sample of galaxies. This project will deliver a more complete view of the “feedback” provided by accreting SMBHs, leading to a better understanding of the black hole-host galaxy relation. More specifically, it will directly probe the energetics of the intra-cluster, circum-galactic, and interstellar media of massive early-type galaxies.

Data management plan for the grant "Metal Oxynitrides: Tuning Metal-N and Metal-O Interactions for Improved Electrocatalytic Properties at the Liquid/Solid Interface." Research investigating the fundamental chemical interactions relevant to the conversion of dinitrogen to ammonia via more energy-efficient routes. The studies will help in understanding the chemical and material factors that are most important for optimizing new materials for ammonia production from dinitrogen, and applications to other important industrial reactions.

Data management plan for the grant, "Examining the Viability of the use of Sarocladium zeae as a Biocontrol Agent in the Agricultural Production of Maize." Sarocladium zeae is a fungus that naturally grows within corn and produces pyrrocidines, compounds that inhibit the production of two exogenous threats to maize, aflatoxins and fumonisins. This project aims to identify other natural products that may be produced by S. zeae through genetic modification in native and non-native fungal hosts to ensure there are no toxins present. In doing so, further information will be gathered about the possibility of using S. zeae as a targeted biocontrol agent that protects against exogenous threats while remaining safe for consumption.

Data management plan for the grant, "Collaborative Research: LTREB Renewal - River ecosystem responses to floodplain restoration." This project centers on researching the metabolic transformations of the metal-contaminated Upper Clark Fork River in western Montana, USA, that are shifting with environmental restoration efforts. Specifically, the work conducted at UNT includes dissolved organic matter (DOM) chemical characterization of river samples along a 200 km transect from the Upper Clark Fork River, metal concentration analysis, and short-term incubation experiments on the river water (30 days of microbial processes) using multiple analytical chemistry techniques such as absorbance and fluorescence spectroscopy and atomic absorption spectroscopy or inductively coupled plasma mass spectrometry. Data will be analyzed to identify chemical and biological signals of restoration and assess ecosystem health.

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, "Chemical-Guided Identification of Primary Metabolic Targets for Improvement of Hydroxy Fatty Acid Synthesis in Physaria fendleri." Research on the identification of primary metabolic targets using chemical-guided identification. The first objective of this research is to conduct metabolomics analysis on P. fendleri embryos cultured with two identified chemical regulators of fatty acid metabolism. The second objective of this research is to generate a metabolic flux map of embryos treated with these regulatory compounds in order to determine how metabolic rates and carbon flow can be manipulated to improve HFA production in this species and increase its commercial viability. With properties that could replace imported castor oil, research on the crop in discussion is situated directly in the scope of the USDA-AFRI Education and Workforce Development goals.

Data management plan for the grant, "MRI: Acquisition of a High Performance Hybrid Computer Cluster for Computational Modeling." Research grant for the purchase, installation, and operation of a new high-performance computing (HPC) resource, called CRUNTCH4, to be deployed at the University of North Texas’ (UNT) Center for Advanced Scientific Computing and Modeling (CASCaM). This much needed HPC resource combines different computing architectures and significant amounts of data storage, all connected via a high-speed communications fabric. This computing resource will provide the means for CASCaM investigators to continue research on a broad range of topics including quantum chemistry, materials design, biomolecular simulations, machine-learning based chemical discovery, and bioinformatics, among others.

Data management plan for the grant, "NSFDEB-NERC: Collaborative Research: Wildlife corridors: do they work and who benefits?" Research on the impact of wildlife corridors using genetics as the measure of effectiveness. The study will use 20 independent landscapes to quantify how corridor traits affect gene flow, and will use non-flying mammals as focal species because they are strongly affected by fragmentation. The research team hypothesizes (1) a strong non-linear decline in success (gene flow) with corridor length, reflecting the skewed distribution of dispersal distances within species; (2) success will drop steeply as corridor width falls below a threshold, with the threshold determined by species traits; and (3) species that are bigger, are habitat specialists, or have greater dispersal abilities (relative to brain size or reproductive rate) will benefit more from corridors. Testing these hypotheses will allow generalization to a wide range of mammal species not included in this project. It will use highly flexible Random Forest models to answer the overarching question: What landscape traits (e.g., corridor width, degree of human disturbance) and species traits (mobility, affinity to particular land cover types) are associated with effective corridors?

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 the grant, "Approximation Theory and Complex Dynamics." This project involves the study of approximation theory in the setting of complex functions, with applications to complex dynamics. Approximation theory seeks to understand the extent to which the behavior of a general function can be effectively modeled by that of functions drawn from a more restricted class. Efficient approximation of functions is of relevance for numerical calculation. Since the only calculations that can be carried out numerically are the elementary operations of addition, subtraction, multiplication, and division, in practical terms it is of importance to understand when the values of general functions are well approximated by the values of either polynomial or rational functions. In many situations, the values of the approximant resemble those of the general function only for a sampling of input values. What can be said about values of the approximant for other choices of input? This is the main question studied in this project, with the following application in mind: when a general function is iterated to produce a dynamical system, to what extent does the dynamical behavior of an approximant resemble the dynamical behavior of the original function? The project will also contribute …

Data management plan for the grant, "Non-Genetic Inheritance of Hypoxia Tolerance in Fishes: Dynamics and Mechanisms." Research quantifying the inheritance of tolerance to low oxygen in a model fish and then determine the tolerance mechanisms, at organismal to molecular levels, that are passed on from parents to their offspring. The investigators will not only focus on conventional, well-studied genetic mechanisms for inheritance, but will explore so-called “epigenetic” forms of inheritance that may transfer parental characteristics for only a generation or two. Such “temporary inheritance” might actually require less energy and be more beneficial to a species than the more permanent form of genetic inheritance. This project will quantify non-genetic inheritance of hypoxia tolerance in zebrafish as a model organism and then identify underlying mechanisms, at organismal to molecular levels, in parents and in their progeny. Specifically, this project will quantify non-genetically inherited traits that allow hypoxia tolerance, determine “wash-in” and “wash-out” (i.e., the dynamics) of hypoxia-tolerant phenotypes across multiple generations, and establish epigenetic mechanism(s) of non-genetic inheritance in subsequent generations. The information provided by this project will allow biologists to better predict, and perhaps even mitigate, the negative consequences of future episodes of low oxygen in rivers and lakes.

Data management plan for the grant, "Developing a Biomanufacturing Platform for the Site-Selective Functionalization and Structural Diversification of Cytochalasan-Based Carbon Skeletons." This project will identify fungal enzymes that efficiently modify more than one substrate in a predictable way. Also, enzymes will be engineered to expand the range of substrates. A biomanufacturing platform to synthesize bioactive molecules at lower costs will be the end result. Fungi can synthesize small molecules with complex structures using a number of highly coordinated enzymes. These molecules are difficult to make synthetically, and they can aid in crop production or have beneficial human health effects. Cytochalasans are phytotoxic, cytotoxic and actin-binding natural products. Produced by fungi, over 400 variants have been described. The structural diversity is partly explained by the flexibility of the enzymes that introduce and modify functional groups. These enzymes structurally rearrange the core carbon skeleton in a site-selective manner, often on more than one substrate. Genome mining will be used to identify cytochalasan tailoring enzymes. Overproducing strains will be characterized chemically. Transcription factor over-expression will be investigated. Targeted gene knock-out will confirm the function and scope of the enzymes. The enzymes will be engineered to expand their substrate range. Synthetic biology and metabolic …

Data management plan for the grant "Functional Porous Organic Polymers as Advanced Decontamination Materials for Water Purification." This project seeks to develop and deploy a new class of porous organic polymers which have high capacity and selectivity to rapidly remove heavy metal contaminants well below parts per million level standards set by the Environmental Protection Agency. The project will engineer porosity and surface chemistry of porous organic polymers to clean inorganic heavy metal contaminants from both surface water and wastewater. Porous organic polymers are robust, chemically and thermally stable, scalable, and modular, with very high surface area. The modularity of these polymers allows for a molecular-level tuning of the pore structure and surface chemistry that allows for engineered site-specificity of binding sites that target the heavy metal contaminants. Recent data shows these new materials offer a significant increase in capacity relative to benchmark materials, with a rapid removal of mercury and other heavy metal ions. This project will advance the concept by exploring rational design of these porous polymers with different topologies by customizing the monomer with various binding groups. The objectives of the project include design, synthesis, and characterization, followed by assessment of these materials to remove inorganic contaminants …