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.

This article combines in silico structural predictions with in planta complementation of the severely defective mtnip-1 mutant plants to understand the role of a series of distinct amino acids in the transporter’s function. The findings add to the knowledge of the mechanism of alternative conformational changes as well as symport transport in NPFs and enhance knowledge of the mechanisms for nitrate signaling.

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, "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.

Data management plan for the grant, "Quantitative PCR Primer Development for Early Detection of Invasive Species."

Data management plan for the grant, "A Laser Microdissection System to Enhance Agricultural and Food Research in the North Texas and Southern Oklahoma Region."

Data management plan for the grant, "The Molecular Building Block Sampling Approach for Polymorphic Free Energy Calculations."

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, "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, "CAREER: Liquid Crystal-Templated Sequential Infiltration Synthesis of Hybrid Organic/Inorganic Materials with Multidimensional Chiral Structures"

Data management plan for the grant, "CAREER: Modeling the Evolution of Massive Galaxies with Enzo-E."

Data management plan for the grant, "CAS: Highly Interacting Panchromatic Push-Pull Systems: Symmetry Breaking and Quantum Coherence in Electron Transfer."