The University of North Dakota is a public research university located in Grand Forks, North Dakota, United States.Established by the Dakota Territorial Assembly in 1883, six years before the establishment of the state of North Dakota, UND is the oldest and largest university in the state. UND was founded as a university with a strong liberal arts foundation and is classified by the Carnegie Foundation as high research activity institution. UND is ranked among the top 100 public universities in the country by U.S. News & World Report. UND offers a variety of professional and specialized programs, including the only schools of law and medicine in the state, but is perhaps best known for its John D. Odegard School of Aerospace science, which trains pilots and air traffic controllers from around the world. It is the first university to offer a degree in unmanned aircraft systems operations.UND specializes in aerospace, health science, nutrition, energy and environmental protection, and engineering research. Several research institutions are located on the UND campus including the Energy and Environmental Research Center, the School of Medicine and Health science, and the USDA Human Nutrition Research Center.The athletic teams compete in the NCAA's Division I. Most teams compete as members of the Big Sky Conference, with the exceptions of men's hockey , women's hockey , baseball , and swimming . The men's ice hockey team has won seven national championships, and plays in the Ralph Engelstad Arena. Wikipedia.
University of North Dakota | Date: 2016-09-01
An iridium silicide structure, devices made from iridium silicide structures, and associated methods are shown. Example devices include iridium silicide structures formed on a (110) surface of a silicon substrate. After formation of the iridium silicide structures, any number of possible electronic devices may be formed, including, but not limited to IR detectors and FinFET devices.
Agency: Department of Energy | Branch: | Program: STTR | Phase: Phase II | Award Amount: 999.58K | Year: 2015
Existing methodologies for attrition evaluation of oxygen carriers in Chemical Looping Combustion systems do not adequately reflect the unique process conditions to which oxygen carriers are exposed, specifically high temperatures and cyclically reacting oxidizing and reducing atmospheres. This proposed Small Business Innovation Research (SBIR/STTR) project targets the development of novel equipment and methodologies that address the shortcomings of existing attrition evaluation methods through use of test conditions that broadly account for the process requirements of coal-based chemical looping systems. Phase I successfully demonstrated the dramatically improved attrition evaluation methodology, and allowed the ability to isolate the relative attrition effects due to mechanical, thermal and chemical stresses to which oxygen carriers are subjected. Phase I performed a detailed analysis of an iron-based oxygen carrier hematite and demonstrated dramatically higher attrition rates under the cyclic reacting conditions compared to non-reacting test conditions. Phase II will include more extensive testing with several additional oxygen carriers over a wider range of process conditions. A new test system will also be constructed to examine the effect of a second important attrition mechanism, and associated methodologies developed. An extensive test campaign will be completed using this new equipment. Additionally, Phase II will develop empirical models that describe the attrition behavior of oxygen carriers as a function of process conditions and attrition mechanism. Focus will be on not only the attrition of the oxygen carriers, but also the reactivity, in order to accurately project the lifetime of oxygen carriers in chemical looping systems. The main benefit of the proposed work is an enabling service for expedited development of chemical looping combustion technology, an emerging strategy for reducing carbon dioxide emissions from fossil- fuel based energy production systems. The information gathered will be useful in designing not only the oxygen carriers themselves, but also the processes and equipment which employ those materials. Additionally, the proposed work will provide a low-cost and expedited approach to material screening. In addition to chemical looping combustion, several other potential markets have been identified, with commercial interest already expressed, including characterization of the following: limestone for fluidized bed combustors, sorbents for carbon dioxide capture, catalysts for fluid catalytic cracking, and materials for thermal energy storage.
Agency: Department of Energy | Branch: | Program: STTR | Phase: Phase I | Award Amount: 149.97K | Year: 2016
Reactive absorption-based carbon dioxide capture processes using solvents is the preferred technology for large scale capture of carbon dioxide in flue gases from coal-fired power plants. This Small Business Innovation Research project targets the development of mitigation strategies to decrease the quantity of aerosols that are formed from such post-combustion capture systems in the presence of sulfur trioxide and other compounds. The key to our novel approach is to understand the source of these aerosols and to prevent/modify their formation within the existing combustion system. A second complementary approach we use is to remove the aerosols from the gas stream prior to entry into the carbon dioxide scrubber. Our technology platform is critical for the development of solvent-based carbon dioxide capture systems; with it, technology vendors will be able to effectively design and operate the carbon dioxide scrubbers to achieve high capture rates, minimize aerosols and volatile organic and particulate emissions, prevent equipment fouling, limit solvent degradation, and have an overall robust operating system. Commercial Application and Other Benefits The main benefit of the proposed work will be to facilitate the further development of solvent-based carbon dioxide capture technologies. With successful demonstration of the proposed work, emissions and solvent losses will be dramatically reduced, significantly decreasing the cost of capture and environmental concerns. The ultimate goal of the proposed work is to deliver an enabling technology for carbon dioxide capture, which is needed to sustain current fossil-fuel power generation while reaching greenhouse gas emissions reduction goals. Other potential applications have also been identified, such as in reduction of alkali aerosols that poison nitrogen oxide reduction catalysts, allowing their use in plants where it was not previously possible. Additionally, the reduction of fine particulate and aerosols is expected to reduce boiler fouling and corrosion issues and improve overall plant efficiency. Key Words: carbon dioxide capture, aerosols, alkali aerosols, sulfur trioxide aerosols, solvent-based post combustion carbon dioxide capture
Agency: Department of Energy | Branch: | Program: STTR | Phase: Phase II | Award Amount: 999.96K | Year: 2016
This Phase II Small Business Innovation Research project targets the development of a technology for segregating fuelbased contaminants (char and ash) from oxygen carrier material in the context of chemical looping combustion application. In chemical looping, the wellmixed solids that flow from the fuel reactor consisting of char, ash, and oxygen carrier particles cannot be completely separated into their constituents before they enter the air reactor. The slip of carbon leads to char oxidation in the wrong reactor and poor carbon dioxide separation efficiency. An efficient method to separate char and ash from oxygen carrier material is critical for the deployment of chemical looping technology. The proposed project will develop a novel method for char/ash separation from oxygen carrier that is specifically tailored to chemical looping combustion and its unique constraints and process conditions. The proposed segregation system consists of a novel combination of methodologies that together provide very high segregation efficiency, even under the extreme conditions of chemical looping systems. Following successful demonstration in Phase I at the labscale, the Phase II project will involve a significant scaleup and will include realistic chemical looping operating conditions. The components in the novel segregation system will be optimized through parametric evaluation of several process conditions. Following completion of testing, the conceptual level engineering design of a pilotscale system integrated within an actual chemical looping operating system will be prepared. Commercial Application and Other Benefits The proposed technology will facilitate the development of chemical looping technology which is a potentially attractive approach for carbon dioxide capture and emissions mitigation. Other potential applications exist such as: separation of volatile inorganic species from recycle char in gasification systems, in the separation of carbon from coalfired plant ash to generate pozzolanic material to replace cement in concrete; in the recovery of coal and valuable rare earth minerals from coal cleaning reject streams; and in postconsumer goods recycling/wastetoenergy based on fragmentation and separation. Key Words: Chemical looping, oxygen carrier, carbon dioxide capture, segregation, char, ash
Agency: Department of Energy | Branch: | Program: STTR | Phase: Phase I | Award Amount: 149.96K | Year: 2016
This SBIR/STTR project targets the development of a validated modeling/design tool for predicting the behavior of spouted fluidizied beds for chemical looping combustion/gasification applications of coal and biomass fuels and fuel blends. Chemical looping is an advanced energy conversion technology for generating a pure CO2 effluent, which can then be sequestered or utilized. A spouted fluidized bed has been proposed as a key component to overcome challenges related to achieving high CO2 separation efficiencies, to increase reliability, and to potentially lower attrition/agglomeration of the circulating solid oxygen carrier. Manipulating the design and operation of the fluid bed to achieve the desired outcomes for a large-scale power plant requires a validated modeling tool. As part of this project, we will bring together relevant experimental testing to obtain validation data and a modeling effort that will describe the primary hydrodynamic behavior, heat transfer, and fuel transformation reactions. Phase I will involve bench-scale testing of chemical looping combustion in a spouted fluid bed reactor. Modeling will be carried out employing an open source multiphase fluid dyanamic code (MFIX) with the addition of user-defined subroutines. Model calculations will be compared to relevant data to calibrate the overall model and the specific subroutines. Phase II work will likely involve the use of a scaled-up system for validation data collection and 3-D modeling. It is critical to have a validated modeling tool for fluid bed-based chemical looping combustion to develop scaled-up designs of equipment to reduce greenhouse gas emissions from coal and biomass fuels in power generation. The proposed work aims to develop such a modeling tool for widespread use in research and industry. Commercial Application and Other Benefits: The proposed technology will facilitate the development of a tool for designing full-scale chemical looping technology, a potentially attractive approach for carbon dioxide capture and emissions mitigation, and the use of fluidized beds in power generation and fuel conversion. It can be used in the optimization of other industrial applications that may deploy fluid beds: in various drying processes; in granulation such as with fertilizer (urea) production; in the pharmaceutical industry, with coatings for tablets; and in animal feed production to incorporate supplements such as fish oil and vitamins.
Agency: NSF | Branch: Standard Grant | Program: | Phase: PLANT GENOME RESEARCH PROJECT | Award Amount: 201.11K | Year: 2016
This action supports a research and training plan to broaden participation of Native American Indians in biology. The project will support Dale C. Brunelle to complete doctoral research at the University of North Dakota in the lab of sponsoring scientist Dr. William F. Sheridan. The goal of the research is to identify and characterize genes crucial for all aspects of maize embryo development using functional genomics as well as traditional genetics and molecular biology strategies.
Training objectives include genetics, developmental biology, and functional genomics. Broader impacts include broadening the participation of Native American Indians as independent investigators with Ph.D.s in the Biological Sciences.
Agency: NSF | Branch: Continuing grant | Program: | Phase: Integrative Ecologi Physiology | Award Amount: 819.84K | Year: 2016
Temperature-dependent gender determination was first reported nearly 50 years ago in an African lizard. It has since been shown that temperature determines gender in some fish and amphibians, many lizards, numerous turtles, and all crocodilians. Yet, the mechanism that converts temperature into a biological signal for male versus female development is not known. The Rhen lab has identified novel temperature sensitive genes that respond quickly to temperature change in snapping turtle embryos. These particular genes are known to turn on or turn off gene expression during embryonic development in other species by modifying chromosomal structure. Such factors are also known as epigenetic regulators and may play a role in gender determination. The proposed studies will test the hypothesis that epigenetic mechanisms regulate expression of genes required for testis or ovary development. Ultimately, this research will advance our understanding of temperature-dependent gender determination and provide insight into the role epigenetic mechanisms play in testis and ovary development in all vertebrates. Educational activities will enhance learning through semester long projects in the classroom, improve undergraduate research experiences through extended internships of 2-3 years, and increase the participation of women and underrepresented minorities in biology. Outreach activities will train Rhen lab members to communicate science more effectively to the public, disseminate findings to a wider audience through production of a mini-documentary about temperature-dependent gender determination, and target a demographic that is neglected in STEM outreach through an informal class for older Americans.
The Rhen lab has developed the common snapping turtle as a model to study unique and conserved mechanisms of gender determination in vertebrates. The overarching hypothesis is that temperature-dependent changes in histone methylation play a key role in regulating transcriptional programs for testis versus ovary development. Experiments test the specific hypothesis that Polycomb Repressive Complex 2 and lysine-specific demethylase 6B regulate methylation of histone H3 on lysine 27 (H3K27) in gonads from embryos incubated under male and female thermal regimes. Polycomb Repressive Complex 2 methylates histone H3 at lysine 27. Trimethylated histone H3 (H3K27me3) is a stable epigenetic mark that represses transcription. Conversely, lysine-specific demethylase 6B allows gene expression by demethylating H3K27me3 to H3K27me2 and H3K27me1. In Aim 1, chromatin immunoprecipitation (ChIP) and quantitative PCR will be used to analyze temperature effects on H3K27 methylation at conserved gender-determining loci. In Aim 2, ChIP-Sequencing will be used to analyze temperature effects on genome-wide patterns of H3K27 methylation in embryonic gonads. In Aim 3, experiments will test whether Polycomb Repressive Complex 2 and lysine-specific demethylase 6B are causally involved in gender determination by perturbing gene expression and/or using pharmacological inhibitors of these proteins. This research will clarify the molecular mechanisms underlying temperature-dependent expression of gender-determining genes. Findings will be presented in public databases, in peer-reviewed publications, and at national/international meetings.
Agency: NSF | Branch: Standard Grant | Program: | Phase: Systems and Synthetic Biology | Award Amount: 659.28K | Year: 2016
During development, cells differentiate to generate the diversity of cell types required to make a functional organism. In blood development, a single hematopoietic stem cell gives rise to about 12 distinct cell types. A hematopoietic cells decision to choose between alternative lineages depends on both the internal state of the cell, defined by networks of lineage-specifying transcription factors, as well as external signals provided by small molecules called cytokines. Furthermore, the two systems, cytokine signaling and transcription factor networks, do not function independently of each other. This project aims to use a combination of computation and experiment to understand how the interaction between signaling and transcription factor networks controls cell-fate choice. This study will advance our understanding of cell-fate choice during blood differentiation and the insights will be relevant to other tissues and organisms. The computational tools developed during the course of research will have broad applicability in developmental biology. Educational activities aim to promote the development of the quantitative and modeling skills of biology students at the undergraduate and graduate levels. This will be accomplished by 1) developing course modules based on the research activities and making them available to the teaching community and 2) mentoring undergraduate students in research projects.
Cell-autonomous gene regulatory networks and cell-extrinsic cytokine signaling have often times been viewed as competing and mutually-exclusive hypotheses for the specification of cell fate during hematopoiesis. The investigators propose instead that cell fate is an emergent property arising from interactions between cytokine signaling and gene regulatory networks. They will test this hypothesis with tightly coupled experimental and mathematical modeling activities. The research plan leverages a unique experimental tool; hematopoietic cells that can be inducibly differentiated along alternative lineages at a defined starting point to probe cytokine-transcription factor interactions in time. Aim 1 will infer the gene regulatory networks involved in the macrophage-neutrophil cell-fate decision de novo by measuring genome-wide expression at high temporal resolution and computing pair-wise mutual information. Aim 2 will build differential equation models of signaling effector/transcription factor networks to investigate how emergent dynamics are produced. The models will be predictive and allow the simulation of the effects of different cytokines and perturbations. While Aims 1 and 2 investigate the system dynamics at the network level, Aim 3 will determine how a core group of 13 transcription factor and cytokine receptor loci are regulated in time at the level of DNA sequence. Here, a novel experimental-computational approach for reverse engineering cis-regulatory module logic will be utilized to identify distal enhancers and silencers and determine how they are regulated. A comprehensive cis-regulatory module reporter library will be constructed and reporter activities will be measured in time. Time-resolved activity data will be used to constrain predictive sequence-based thermodynamic models of transcription to determine the transcription factors and protein-protein interactions regulating the modules. This study will use unique tools of the model system, time series data, and modeling to determine how gene regulatory networks process cytokine signals in a context-dependent manner. The models and reporter library will be a resource for a wide range of developmental biologists.
Agency: NSF | Branch: Standard Grant | Program: | Phase: BD Spokes -Big Data Regional I | Award Amount: 995.74K | Year: 2016
The Digital Agriculture Spoke of the Midwest Big Data Hub seeks to organize academic, industrial, and governmental sectors around the development of policies and best practices for data science and Big Data applications in agriculture, with a particular focus on automating the Big Data lifecycle for unmanned aircraft systems (UAS) and for plant sciences, phenomics, and genomics. This effort is necessitated by the projected growth in the global population (9.5 billion people by 2050), which will require the global agricultural workforce to produce 70% more food than our farmers do today. Historically, agricultural revolutions in cultivation, social organization, and industrialization have provided the means to increase food production. However, future revolutions must leverage the advantages provided by the modern information society. This project will serve as a catalyst for this data-driven revolution, which will be broad and societal in nature and address the triple-bottom line of being economically viable, socially acceptable, and environmentally sensible. Whereas the initial focus areas are specific, the resulting best practices and partnership-building will translate to and enable other areas such as remote sensing systems and farm management techniques. An expected outcome is improved and efficient use of UAS, imaging, and genomics in agricultural sciences, ultimately leading to a more sustainable global food and nutrition system. Coordination of these activities will be enhanced through a Digital Agriculture open web portal of data science resources, designed to integrate existing information silos, facilitate collaboration, and contribute to workforce development. Educational activities and tools will be leveraged from pre-existing traineeship programs and collaborative entities, and broadened with newly developed annual workshops. Special issue-teams of academic, industrial, and governmental representatives will be used to conduct deep-learning analysis of project educational activities to identify and refine mechanisms for broadening and diversifying participation. Through these efforts, the collaboration will improve access to data assets, train a workforce with relevant skills and expertise, and will contribute to solving the Sustainable Global Food and Nutrition Security challenge.
This project will focus on two knowledge domains important to agriculture, UAS, and Plant Sciences. These two themes of Intellectual Merit will be melded with cross-cutting activities designed to improve the management, accessibility, automation, and value of the lifecycle for data that are generated by multiple, high-throughput sensor and measurement platforms in contexts related to agriculture and agriculture production. Best practices for transport, storage, dissemination, and analysis of Big Data will be translatable and scalable to other areas such as farm management systems and precision agriculture, and will enable the access to and use of valuable data assets related to UAS and plant sciences, thereby accelerating progress toward sustainable agricultural production. Many of the ideas and methods developed under this project and the partnership-building activities that link multiple public institutions and private entities will be transferable to other disciplines that require Big Data, such as transportation, health sciences, and food, energy, and water, and will therefore generate innovation and discovery from many and complex data resources. One aspect of these partnerships is the desire to build a workforce with strong data science skillsets. To accomplish this, project activities include participation by undergraduate, graduate, and early career scientists in annual meetings, Zoom events, and webinars. Interested participants from the academic, industrial, and governmental sectors will be supported and encouraged to engage in cutting-edge research and development areas such as direct data collection of plant features by UAS, biological feature extraction through image analysis, Big Data processing pipelines, and techniques for data management and sharing. Diversity of innovation related to UAS and Plant Sciences will be encouraged through a suite of issue teams who analyze in-person and web-based trainings, goal-oriented Meetups, and conference events for diversity using deep learning techniques. These modalities for deep learning were selected for their scalability and improved access by underrepresented groups. The project has a heavy emphasis on workforce training and best practices. Workshops and webinars, including hackathons and datathons, will help both students and people already in the workforce expand their professional development.
University of North Dakota | Date: 2016-03-24
An aerial vehicle system includes a flight system configured to generate propulsive force and lift, a protective framework, and an attachment mechanism secured to the protective framework and configured to selectively attach to a structure to provide stable perching of the aerial vehicle system. The attachment mechanism is an electro-permanent magnet device or a talon-like grip. The flight system is at least partially enclosed by the protective framework.