Data management plan for the grant "High-throughput Screening and Quality Assessment Testing and an AI-based In-Situ Process Monitoring and Quality Control Framework for Additive Manufacturing New Builds and Repaired Parts."

Data management plan for the grant, "Tunable Plasmonic Multispectral Meta surfaces." This project investigates the fundamental light-matter interactions and light emission tunability of 2D materials augmented by plasmonic gratings. A key application of our fundamental research is the development of the next generation of optical transistor that use photons to transmit signals containing digital information.

Data management plan for the grant, "Mechanochemical Reconstruction Principles for Two-Dimensional Material Adaptation to Applied Stresses." This grant focuses on understanding how 2D materials change their structure and function under loading and shear stresses. For this, we will investigate the fundamental origins of solid-state interactions, unraveling the processes occurring at contacting surfaces during sliding, why some materials show better stability than others, and how one can use these novel 2D materials for mitigating friction and wear and enabling superlubricity.

Data management plan for the grant, "Collaborative Research: Research Infrastructure: CCRI: ENS: Enhanced Open Networked Airborne Computing Platform." The project aims to develop an enhanced open networked airborne computing platform to facilitate the design, implementation, and testing of an airborne computing platform that seamlessly integrates control, computing, communication, and networking. The project will provide community support based on the flywheel model, and to attract and engage community users through organized support from four regional sites in the nation, hands-on workshops, testbed access, and technical user services.

Data management plan for the grant, "Collaborative Research: CIF: Medium: Fundamental Limits of Cache-aided Multi-user Private Function Retrieval." This project is motivated by the need to efficiently execute complex queries on massive databases in a way that minimizes the use of communication resources while preserving the privacy of the entity that initiated the query. Such queries are functions of the data points that are stored at remote servers. This project develops a principled and holistic framework for the problem of privately retrieving, at distributed cache-aided nodes, the output of functions based on both data that is locally computed and data that is received from multiple servers.

Data management plan for the grant "Nuclear Safety Testing and Analysis Research (NSTAR) Fellowship Program at the University of North Texas." The proposed NSTAR fellowship program at UNT aims to reinforce the workforce in the nuclear energy safety community by engaging the selected fellowship students (fellows) with interdisciplinary education and research. The overarching theme and research focus of the proposed NSTAR program is acoustics-based non-destructive testing and analysis and nanoparticle processing for thermal management applications. An interdisciplinary research team will investigate these research areas with backgrounds in mechanical engineering, material science, and/or physics. The program will fully support two fellows over four years including full tuition and stipends.

Data management plan for the grant, "CICI: UCSS: Secure Containers in High-Performance Computing Infrastructure." Ensuring the security and privacy of high-performance computing (HPC) infrastructures is of utmost importance due to their handling of sensitive data and critical scientific computations. HPC infrastructures commonly employ containers, which provide lightweight and isolated environments for running applications. Nevertheless, containers in HPC infrastructures encounter security challenges, including insecure container images and vulnerabilities related to isolation. Existing container image scanners face a major challenge of low coverage, while current container runtimes struggle to ensure both security and performance for HPC workloads simultaneously. This project addresses these challenges by developing secure containers specifically tailored for HPC infrastructures. The project introduces innovative solutions, including the development of an efficient image vulnerability scanner and a secure container runtime.

Data management plan for the grant, "New approach based on enzyme stimulating of peptides for targeting drug resistance breast cancers." In this project, we propose the development of selective self-assembling peptides that form nanofibers via a self-assembling process upon the action of Eyes absent (EYA) enzyme, specific to drug resistance Triple Negative Breast cancer cells (TNBC). The objectives are: Aim 1: Design and synthesize self-assembling peptide substrates for EYA enzymes; Aim 2:Determining the efficacy of peptide substrates for inhibiting TNBC in spheroid 3D cell cultures. The correlation between the enzyme kinetic and the activity of nanostructures for targeting EYA will be evaluated. Aim 3: The apoptosis response of the TNBC cells will be determined. This study will lead to finding the potent peptide substrate and the effective dose for inhibiting TNBC cells with apoptosis cell death.

Data management plan for the grant, "CAREER: Shape Memory Polymers as Biomaterial." This CAREER projectaimsto elucidate the underlying mechanism of the plasticization-induced shape memory effect of thiol-enebased polymers. The model application for this material will be a heat shrink tubing that can shrink at bodily conditions (37° C and simulated body fluids) and can be used to seal colonic anastomosis. The specific three aims are to (1) Systematically investigate the effect of crosslink-density and chain extender length on theplasticization-induced shape memory effect of thiol-enebased polymers. Mechanical and thermomechanical measurements inside simulated body fluids will be used to assess shape memory properties and structure-property relationships. (2) Understand the relationship between material thickness, degree of shape-programming, and radial recovery forces of tube-shaped SMPs to determine optimal design parameters for sufficient shape recovery using the heat shrink tube model. (3) Demonstrate the functionality of a biomedical heat shrink tube that utilizes the plasticization-induced shape recovery through an ex vivo colon anastomosis model and quantify mechanical and sealing properties.

Data management plan for the grant, "CPS: Medium: Integrating sensors, controls, and ecotoxicology with decoupled aquaponics using brackish groundwater and desalination concentrate for sustainable food production." This project aims to develop a cyber-physical system (CPS) testbed of integrated sensors, controls, machine learning, and ecotoxicology tools to engineer sustainable food production systems based on aquaculture using brackish water. The testbed includes an automated recirculating aquaculture system integrated with a real-time ecotoxicology system, implementing the system using desalination concentrate to demonstrate that brackish groundwater desalination costs can be offset by using its byproducts for profitable food production. This project will engage students of the local communities in three major ways: developing an exhibit and activity emphasizing interdisciplinary CPS research conducted during the academic year, offering summer research experiences to students from underrepresented groups, and participating in STEM outreach events targeting underrepresented groups.