University Of Tennessee Knoxville

NSF Awards · FY 2025 · 2025-05

A quantitative understanding of the flow of nutrients and energy in marine ecosystems is critical to understanding and predict the availability of the resources that support food webs and the capacity of the ocean to store carbon. Viruses play multiple and dynamic roles in the fate of organic matter and the flow of energy in the ocean. Arguably, the least studied of those roles is the direct transfer of nutrients and energy up the food web through grazing on virus particles — virovory. This study investigates how virovory impacts the cycling of organic matter and its contribution to grazers’ nutrition varies in time and space across distinct microbe groups. The work is timely and complementary to large-scale projects to create a predictive understanding of the ocean’s carbon cycle and transform our understanding of the impacts of viruses in the marine environment beyond their role as parasites. This project engages and trains early career scientists and students as scientific partners, providing professional skills critical for careers inside and outside academia, such as science communication and reporting to diverse audiences. The project also includes participation in STEM programs for middle and high school students. Virus particles and infections play a role in the biological cycling and sequestration of organic matter by increasing the flow of organic matter to the dissolved phase, fueling the microbial loop—‘viral shunt’ and releasing compounds during host cell lysis that enhance the formation of particle aggregates and the sinking of organic matter through the biological pump—‘viral shuttle.’ Quantifying virus decay and removal is critical to constrain infection dynamics, a first step to quantify the ‘shunt’ and ‘shuttle.’ Virovory is a potentially dominant virus loss process, a source of nutrition to grazers, and a significant food web pathway that redirects nutrients and energy to upper trophic levels. However, the magnitude of each of these virally-mediated processes of regeneration, sequestration, and trophic transfer remains largely unresolved. This research team uses laboratory incubations of natural marine microbial communities collected on different seasons from oligotrophic and eutrophic environments with isotope-labeled viral particles and mathematical ecosystem models to test the following hypotheses: H1. Virovory is a natural sink of marine viruses that rivals all other viral losses combined. H2. Nutrient transfer from large enveloped dsDNA eukaryotic viruses is higher than from smaller virus particles. H3. Virovory contributes more nutrition for heterotrophic protists in permanently or seasonally oligotrophic waters than in eutrophic marine ecosystems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-03

NON-TECHNICAL DESCRIPTION This program is inspired by opportunities to explore the different metastable phases of hafnia (HfO2) under external stimuli and to invest in the education of students at the University of Tennessee. Both initiatives merit broad support because they will advance the fundamental understanding of new states of matter in oxide dielectrics and contribute to important societal values and outcomes. A variety of different phases of hafnia will be studied to unravel mechanical and tribological properties, switching pathways, and the appearance of elusive or metastable phases driven by pressure. Structure-property relationships are also of interest. A broad range of educational, outreach, and service activities will also take place under the auspices of this National Science Foundation-funded program, especially in the areas of increasing the STEM workforce, conference and workshop organization, and service to various national laboratories. TECHNICAL DESCRIPTION The research outlined in this proposal focuses on the spectroscopic properties of hafnia and the application of pressure and electric field to drive phase transformations. The project combines synchrotron-based infrared absorption and Raman scattering with diamond anvil cell techniques, lattice dynamics calculations, symmetry arguments, and an analysis of energy landscapes with selected resonant x-ray, mechanical, and tribological properties work to (i) identify high pressure routes to new states of matter, (ii) reveal mode Gruneisen parameters along with mechanical and tribological properties, (iii) test how to create stabilizer-free single crystals of HfO2 using high pressure techniques rather than high temperature growth, (iv) search for evidence of soft mode instabilities, and (v) resolve controversy regarding the ferroelectric switching pathway in the polar orthorhombic material. The project is also interested in the structure-property relationships that can be unraveled in this system. What brings these efforts together is interest in light-matter interactions under extreme conditions and the spectroscopic techniques that are investigated. Findings from this program are advancing theoretical development and semiconductor chip applications. This program also supports the interdisciplinary education of young researchers for future employment in academics, government laboratories, and industry in the area of advanced materials. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-03

This award supports the travel of scientists, especially early-career scientists (students, postdocs, early career faculty), working at institutions in the United States to participate in the 25th Conference of the International Plant Growth Substances (IPGSA 2025), that will be held in Fort Collins, Colorado, 29 June through 3 July 2025. This conference brings together scientists studying a range of molecules that regulate plant growth. The conference promotes interactions and scientific exchange between researchers with scientific backgrounds and interests that cross disciplines and scales. Such interactions will expose participants to the latest advances in the field as well as to an international research community. This exposure will play an especially significant role in advancing the professional development of early-career scientists helping to accelerate the training of the next generation of researchers. This exchange of information is also critical to develop applications related to these molecules to increase crop yields, stress resistance, and improved post-harvest storage to improve food security. Novel information and ideas from this conference will be shared with other scientists via review and perspectives articles to broaden scientific research on plants. Diffusible chemical signals play critical roles in the growth, development, and stress responses of plants. These signals are known collectively as plant growth regulators or substances. IPGSA 2025 will bring together established scientists, early-career faculty, students, postdoctoral fellows, and those new to the plant growth substances field to discuss the latest advances in the regulation of plants by these chemical signals. The IPGSA meetings are unique because, unlike other conferences that focus on a single molecule or class of molecules (auxins, ethylene, etc.), the IPGSA conferences span all small molecules that regulate plant growth, thus promoting an integrated understanding of the regulation of plant growth, development, and responses to stresses. The science presented at IPGSA 2025 will involve integrating across scales, providing links between processes at the molecular and cellular levels to growth responses at the tissue and organismal levels. This will include systems-wide studies that have facilitated the development of predictive models for growth-regulator signaling and for signal integration between different growth regulators. Talks will include interdisciplinary areas including the use of mathematical modeling to explore the topology of gene regulatory networks, the use of chemical biology to understand and control hormone signaling, studies of the plant microbiome that integrate microbiological and plant genetic approaches, and the use of a combination of biology, biophysics, and computational approaches to model hormone receptor structure. Although the reference plant Arabidopsis thaliana is a focus of growth regulator research, many of the presentations will include studies conducted on non-model plant species. This award is co-funded by the Developmental Systems Cluster (DSC) and the Physiological Mechanisms and Biomechanics (PMB) Program within the Division of Integrative Organismal Systems (IOS). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-03

The "Current Developments in Geometric Group Theory Conference" will be held as part of the 53rd John and Lida Barrett Memorial Lectures at the Highland Manor Inn & Conference Center in Townsend, Tennessee, on May 22 - 25, 2025. The Barrett Lectures began in 1970 as a tribute to Drs. John H. and Lida Barrett, former faculty and department heads of the Mathematics Department at the University of Tennessee. The Barrett Lectures have been held annually since 1970 and are known as one of the oldest and most prestigious mathematics conferences in the southeastern United States. This event is expected to draw 40-50 participants and will include local and regional, national and international researchers and graduate students. One of the primary goals of the Barrett Lectures is to bring prominent researchers working in active areas to Knoxville, as a service to the southeastern region of the country as well as the national mathematics community. The conferences invite a range of mathematicians, from established experts to early career researchers and graduate students, to attack the biggest challenges in the area of mapping class groups and the newly emerged field of big mapping class groups. The topic of the 2025 Barrett Lectures has the advantage of a broad appeal to researchers at universities throughout the country who are exploring a range of problems and techniques in the current development of geometry and dynamics of non-positively curved groups. Participants will present and learn about breakthrough results in the area of low dimensional topology and geometric group theory, such as the first examples of purely pseudo-Anosov closed surface groups in a mapping class group. The topics covered will include large scale geometry of Teichmuller space, random walks in non-positively curved groups, surface subgroups of mapping class groups, algorithmic problems in Out(Fn) and coarse geometry of large mapping class groups. Juxtaposing discussions with different techniques has the potential to result in synergy and fresh ideas. More information about the conference can be found at: https://math.utk.edu/barrett/53rd-lectures/. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-02

Despite the tremendous accomplishments of machine learning and deep learning in the past decade, challenges remain for structurally complex and diverse data. For example, a single data point in a database used for drug design might have tens of thousands of internal degrees of freedom, and such a database may have tens of thousands of such data points. This feature of structural complexity is a major challenge to deep learning methods. Moreover, diverse data typically originate from sparse sampling of a huge space, and this sparsity is due, in particular, to the cost and time constraints in experimental data acquisition. This project will address the challenges of complex and diverse datasets with ideas that blend and integrate mathematical techniques from several subfields including algebraic topology, spectral graph theory and multiscale analysis. The methods developed will apply to data representation, advanced machine learning methods, and deep learning algorithms, and will be implemented into software packages available to the community. This project will train graduate and undergraduate students and engage underrepresented groups in data science research. This project will develop novel topology and graph theory-based approaches to revolutionize the current practice in data analysis and to deal with the challenge of structurally complex data and diverse data. First, the investigators will develop persistent combinatorial graph theory as a unified paradigm for simultaneous topological data analysis and spectral data analysis. In particular, they will develop systematic, scalable, accurate persistent combinatorial graph representations to extract rich topological and spectral information. Secondly, the investigators will develop multiscale graph models to create a family of nested submanifolds to handle the diverse data originated from sparsely sampled data points in a huge space. These methods will be integrated with advanced machine learning and deep learning algorithms for complex and diverse datasets. Thirdly, the proposed methods will be applied to a wide range of case studies in data science. User-friendly software packages and online servers will be developed using parallel and GPU architectures for researchers who are not formally trained in mathematics or machine learning. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-01

Intensifying heatwaves and rising temperatures pose unprecedented challenges – globally and throughout the United States – generating an urgent need to understand how at least some animals cope well with heat. Behavior is often key to resilience during environmental change, and yet we do not understand the capacity of behavior to resolve the problem of heat. To address this fundamental question, this research tests a ‘behavior-centric’ framework to generate critical data on behavioral responses to increased temperatures. We challenge free-living birds with increased temperatures, focusing on a species whose numbers are increasing in the hot and humid southeastern United States. This research has high potential to open new areas of inquiry. We will provide the basic research needed to inform future applied work, such as predictive models and conservation decisions. By focusing on behavior, we will build and test a framework that can be applied across species or across multiple anthropogenic insults that assail the natural world – wildfire smoke, endocrine disrupting chemicals, urban noise, and more. By coupling this research with outreach and training, we will build educational infrastructure on the problem of heat, improve STEM training, and broaden participation for groups under-represented in STEM. Outreach products will include new infographics, installations, and virtual reality/gaming experiences that build understanding on the role of behavior in a changing world. Altogether, results will give much-needed insight into how behavior does (or does not) buffer animals from the consequences of heat. Biologists have long considered behavior to be the first line of defense against environmental change, and yet we lack key behavioral parameters for predicting who persists or succumbs to the growing challenge of heat. Small endotherms are particularly vulnerable and their early life conditions set the stage for lifetime fitness, yet we do not know much about how heat affects their relatively helpless young, who have limited options for coping. To identify how behavior may buffer the effects of inescapable heat, this research will: (1) use cross-fostering to identify causes and consequences of among-individual variation in behavioral responses to heat, (2) determine how behavioral acclimation affects responses to subsequent heat, and (3) determine how populations vary in their behavioral capacity to mitigate heat. The study species is a cavity-nesting bird (Tachycineta bicolor), which is thriving in some warming environments. The experimental challenge uses air-activated heat-packs in their enclosed nest cavity. The working hypotheses are that: individuals and populations vary in the degree to which behavior is effective at mitigating heat; and, recent experience and evolutionary history will shape whether behavioral responses are sufficient for coping with heat. Together with analyses of the fitness-related consequence of heat, these experiments will identify the relevance of behavioral variation within an individual, among individuals, and among populations. In doing so, this research provides a cohesive test of the hypothesis that behavior truly is on the front line of solving the global challenge of heat. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-01

Project Summary Our long-term goal is to decipher the multifaceted role of five-carbon (C5) metabolism in cellular physiology and disease. Five-carbon metabolism derives from the central hub of the isoprenoid pathway, which is necessary for an array of critical bioactivities, including cell membrane integrity (e.g., cholesterol), glycoprotein synthesis (e.g., the dolichols), steroid hormone signaling (e.g., androgens, estrogens, and cortisol), and mitochondrial health (e.g., coenzyme Q). Human isoprenoids derive from the mevalonic acid (MVA) pathway, whereas many other organisms utilize the methyl erythritol phosphate (MEP) pathway. The MVA and MEP pathways both converge on the same two isomeric C5 metabolites, isopentenyl pyrophosphate (IPP) and dimethylallyl pyrophosphate (DMAPP). Therefore, IPP and DMAPP are the central five-carbon precursors for all isoprenoids in all organisms. Despite their importance, there are relatively few chemical and biological tools to directly study IPP and DMAPP and little is understood about their independent biological activity, and metabolic fate beyond incorporation into longer chain isoprenoids. Furthermore, no chemical probes or genetic tools have been developed to modulate the activity of human isopentenyl pyrophosphate isomerase (IPPI), which is necessary to produce DMAPP and maintain homeostasis of the C5 precursor pool. Levels of IPP and DMAPP are directly involved in cardiovascular disease and IPPI has recently been implicated in the progression of Alzheimer’s, and the development disorders Zellweger spectrum disorder and adrenoleukodystrophy. Extensive prior research efforts have focused on developing inhibitors for enzymes in the MVA pathway, but human IPPI has not been explored. Similarly, chemical tools developed for studying prenylation via the long-chain isoprenoids farnesyl pyrophosphate (C15) and geranylgeranyl pyrophosphate (C20) are well-established, but tools and approaches for interrogating C5 prenylation are completely lacking. The collective lack of tools and approaches for studying C5 metabolism is likely caused in part by the fact that IPP and DMAPP are cell impermeant and thus cannot be exogenously delivered to cells. We recently addressed this key barrier through the development of cell-permeant analogs of IPP and DMAPP and demonstrated their utility in human cancer cell lines and the model gram positive bacterium Bacillus subtilis. Motivated by our recent progress and proof-of-principle preliminary results supporting the research methodology, we will address unmet needs by: (1) creating the next generation cell-permeant C5 analogs and developing inhibitors and cellular tools targeting modulation of IPPI activity; (2) develop a high throughput assay for the quantification of IPP and DMAPP in cellular experiments; and (3) Combine the developed chemical biology tools with advanced analytical approaches to discover and characterize novel metabolites and biological functions of C5 metabolism. Overall, this research promises to provide versatile tools for detailed investigations of C5 metabolism, expand our scientific understanding of C5 prenylation, and shed light on potential therapeutic targets in the isoprenoid pathway.

NSF Awards · FY 2025 · 2025-01

As the global population grows, so does the need for food. As food demand grows, people are also becoming more particular about food quality. They want food that is ethically produced, sustainable, safe, nutritious, and tailored to special health needs or life stages. To meet these demands, we need innovative ways to develop, produce, and store food. This is where a global collaboration between the United States and New Zealand becomes crucial. New Zealand is known worldwide for its advanced food research capabilities. In this project, we will work with our colleagues at the University of Otago in New Zealand to train diverse US engineering students in food science and innovation. The IRES funding will support six demographically diverse US undergraduate engineering students each year for three years. The students will spend eight weeks every summer in New Zealand, gaining international research and cross-cultural educational experience that will boost their professional growth. Imagine students working on projects such as examining the nutritional value of novel protein sources, studying how processing affects plant-based foods, discovering and validating new food nutrients that help to manage diseases, and using chemical analysis to ensure food safety and quality. The experience will provide the students with new capabilities to address food challenges in the US. We will leverage the project to promote STEM education among K-12 students, particularly female and minority students. The project is about equipping future engineers in the US with the skills and experiences they need to innovate in the food industry, ensuring a sustainable and quality food supply for generations to come. The growing global population has heightened the demand for food, with consumers seeking ethically and sustainably sourced, safe, nutritious, and specialized food options. Innovations in food development, manufacturing, processing, and storage that leverage international research collaborations are essential for creating sustainable global food technologies. This project aims to establish a collaborative research program between the United States and New Zealand to train diverse US engineering students in interdisciplinary food science and innovation. New Zealand is globally recognized for its advanced food research and industry capabilities. We collaborate with our colleagues in the Department of Food Science at the University of Otago, a leader in food science, to provide the infrastructure and expertise to train the students. The IRES funding will support six diverse undergraduate engineering students each year for three years, providing them with an eight-week summer research training program in New Zealand. The IRES project will enable US engineering students to participate in food innovation research projects in New Zealand, equipping them with technical skills and practical knowledge. The projects will include nutrient profiling of novel protein sources, effects of food processing on plant-based foods, bioinformatics discovery of bioactive peptides, and chemical fingerprinting for food safety and traceability. The students gain hands-on experience with advanced food science concepts and techniques. The opportunity provides comprehensive international research and cross-cultural educational experience to enhance their professional and personal development. The project provides the future workforce of the US food industry with new capabilities in food innovation and sustainability. Additionally, it serves as a platform for K-12 outreach, promoting STEM education among female and minority students. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-01

The broader impact/commercial potential of this Partnerships for Innovation - Technology Translation (PFI-TT) project is to safely recycle materials from scrap cathodes generated in manufacturing facilities of lithium-ion batteries. This proposed innovation could lead to numerous socioeconomic benefits, such as creating new jobs, reducing the need for extraction of rare elements from mines, e.g. lithium, improving national security by decreasing reliance on imported battery materials, and decreasing the battery cost for electric vehicles and for renewable energy storage. In terms of broader educational outcomes, several graduate and undergraduate students will be directly trained in developing new technologies. Students will also learn about technology translation and entrepreneurship. Additionally, through summer camps offered in this project, STEM students will benefit from the leadership and entrepreneurship training, which will ultimately better prepare the STEM workforce to ultimately enhance and contribute to the U.S. technology-based economy. This project has the potential to enhance scientific and technological understanding of recycling energy materials while simultaneously contributing to a sustainable and environmentally friendly industry. The proposed project aims to address the unique challenges associated with the direct recycling of cathode active materials from lithium-ion battery manufacturing scrap, with the goal of returning the recycled materials to the supply chain. The project seeks to overcome two major technological hurdles. First, the project aims to achieve a formulation for solvent blends for different cathode active materials while considering solubility, toxicity, safety, recoverability, and cost constraints. Second, the project aims to demonstrate the performance of the scrap recycling machine, which will involve two discrete steps: "process and method identification" and "machine assembly, testing, and proof-of-concept demonstration." It is estimated that this machine can save 10-15% of the cathode material consumption of lithium-ion battery manufacturing facilities, thereby reducing the cost of domestic lithium-ion battery manufacturing by 4-6%. Through this project, the research team will advance the fundamental knowledge of polymer solvent blending formulation and explore the effect of the blend on possible damages to cathode active materials, as well as the recoverability, safety, and environmental impacts of the solvent. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-01

Microorganisms can turn organic waste into biogas, a renewable alternative to petroleum-derived natural gas. Biogas production is carried out by a microbial community consisting of organic-consuming bacteria and biogas-producing microorganisms known as methanogens. These microorganisms work together in a very complicated network of interactions, which makes the overall process of biogas production vulnerable to changes in the environment. The goal of this project is to improve biogas production by creating a special community of microorganisms that convert waste into biogas more efficiently by feeding on electricity. Research has shown that some organic-consuming and biogas-producing microorganisms can use electricity as their energy source to grow. Based on these studies, an innovative method is proposed for building the microbial community by continuously switching the direction of electricity. When the direction of electricity is switched, both the organic-consuming and biogas-producing microorganisms can gain energy to grow. As a result, the community can be made more resilient to changes in the environment, and biogas can be produced at a high rate. Successful completion of this research will improve our understanding of how these microorganisms work in nature and holds promise as a source of cleaner and cheaper renewable biogas energy. Additional benefits to society result from educational opportunities for high school and college students from underserved groups to diversify and enhance the Nation’s STEM workforce. Methanogenic microbial communities convert organic waste into methane biogas. Biogas production can be enhanced by building synthetic microbial communities capable of electro-methanogenesis. The goal of this project is to develop a novel approach to build electro-methanogenic communities as a model system to understand the mechanisms for microbial community assembly and extracellular electron uptake. The central hypothesis of this research is that electro-methanogenic communities can be readily assembled using alternating polarity. As the electrode potential is alternated, the electrode serves as an electron donor for electrotrophic methanogens as well as an electron acceptor for electroactive bacteria. Together, this process results in simultaneous selection of both populations. To test the central hypothesis, three interconnected research aims will be pursued to: i) build robust electro-methanogenic communities with alternating polarity, ii) quantify the contribution of different driving forces to community assembly, and iii) elucidate the metabolic pathways involved in extracellular electron uptake. Completion of this research will advance our understanding of the ecological role of electrotrophic microbial ecosystems, and potentially lead to new avenues for biogas production. Additional benefits of this project result from the training of high school, undergraduate, and graduate students from underserved groups by leveraging long-standing engagement between the research team and the Society of Women Engineers, the National Society of Black Engineers, and the Society of Hispanic Professional Engineers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-01

The project aims to tackle the pressing issue of behavioral health disorders in rural East Tennessee, where high rates of mental health and substance use disorders are compounded by a lack of healthcare resources and geographic isolation. Rural East Tennessee accounts for a significant portion of the state’s drug overdose deaths, highlighting the critical need for innovative healthcare solutions. By leveraging advanced, science-driven, and socially informed smart tools, this project seeks to bridge the gap between dispersed healthcare providers and rural residents in need. The broader significance of this project lies in its potential to enhance healthcare access and equity, particularly in underserved communities. By connecting traditionally isolated stakeholders and optimizing healthcare delivery through innovative technologies, this research advances health, safety, and well-being across communities. This project not only addresses critical health challenges but also sets the stage for transformative advancements in healthcare delivery, with implications that extend to other areas such as emergency response and food distribution. By involving community members in the research process, it aims to foster public scientific literacy and empower individuals to advocate for novel healthcare practices within their communities. This project will focus on four key research thrusts to achieve its goals. First, it will develop predictive models to assess risks, vulnerabilities, and healthcare service demands related to behavioral health disorders in rural communities. These data-driven models will help identify areas of greatest need and inform targeted interventions. Second, it will gather and analyze social perceptions and public concerns regarding novel healthcare delivery methods through comprehensive surveys, interviews, and focus group discussions. This aims to enhance the utilization of new healthcare services by understanding and addressing community concerns. Third, it will create new healthcare service paradigms by scheduling and coordinating mobile resources, such as mobile clinics and drones, to meet patient needs while considering operational and regulatory constraints. This innovative approach seeks to safely and efficiently deliver healthcare services, considering patients’ preferences and providers’ logistical limitations. Finally, these elements will be integrated into a Rural intEgrAtive Connected Healthcare (REACH) software platform, which will be piloted in collaboration with local community stakeholders. Through the multidisciplinary approach, the project aims to establish a robust foundation for groundbreaking mobile-connected delivery systems, thereby advancing health equity and public health outcomes and contributing to the creation of smart, connected, and inclusive communities that cater to the needs of vulnerable populations. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-01

This award is funded by NSF Global Centers program, an innovative partnership with funding agencies in Canada, Finland, Japan, Republic of Korea, and the United Kingdom, to jointly support use-inspired research addressing global challenges through the bioeconomy. These partnerships leverage resources to tackle challenges at a larger scale than would be possible for one funding agency alone. This Center is jointly supported by NSF, the Natural Sciences and Engineering Research Council and the Social Sciences and Humanities Research Council of Canada, the National Research Foundation of Korea, and UK Research and Innovation. One pressing challenge is the development of environmentally and economically sustainable bio-derived composites and plastics. The Global Center for Sustainable Bioproducts (GCSB) tackles this challenge. It leverages expertise from the US, Canada, Republic of Korea, and the UK. Scientists from Japan and Finland also participate to this effort, together with collaborators from the global industrial sectors. The international team fosters innovative approaches aiming at converting and utilizing waste biomass for bioplastics. The research focuses on four thrusts: (i) sustainable bio-utilization of high-volume bioresources; (ii) intrinsic carbon negativity of the conversion process; (iii) economic sustainability and development of products compatible with the environment; (iv) fundamental science and engineering of biorefining. The Center also promotes an innovative educational program, reaching out to a large body of students across borders, from K-12 to graduate students. The GCSB advances the chemistry of biomass pre-processing to reduce recalcitrance factors and genetically manipulate microbes to maximize polyhydroxyalkanoate (PHA) productivity and properties. PHA is incorporated into composites with biofillers such as nanocellulose and nanolignin, for 3D/4D printing. The program approach is guided by life cycle assessment (LCA) and techno-economic analysis (TEA) which validate the biorefinery platform approach. All components of the starting bioresources are fully utilized with consistent sustainability requirements. A targeted 3D/4D printing studies is directed toward preparing functional structures/sensors that respond to environmental pressures and are inspired by biodesign. The GCSB integrates these activities to achieve technological breakthroughs. It also provides a robust learning platform for future centers and traditional and non-traditional international students. Educational thrusts in biorefining and sustainability include: (a) hybrid STEM outreach programs for K-12 students with international experts for next-generation professionals; (b) research opportunities in biorefinery, biomanufacturing, genetic engineering, synthetic biology, modeling, and LCA and TEA at international collaborators’ institutions; (c) technical sessions at international conferences on the theme of GCSB; (d) summer research opportunities in STEM fields for underrepresented students; (e) an interdisciplinary bioeconomy course; (f) an educational book on bioeconomy and biorefining. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-12

As the deadliest U.S. mainland hurricane since Katrina, with over 230 fatalities, Hurricane Helene exposed significant vulnerabilities in hazard warning reception and response within mountain and inland communities in the U.S. Southeast. Risk perception, warning reception, and response in these communities have been largely understudied, leaving critical gaps in understanding how these populations perceive and react to hurricane-related threats, as most research has focused on coastal areas. This work contributes to reducing losses by improving the understanding of hurricane-related risks within mountain and inland communities, leading to improved and more equitable weather warning and response systems. The findings have the potential to benefit mountain and inland communities, National Weather Service forecasters, emergency management professionals, and especially under-resourced communities. Utilizing decision sciences that integrate social and behavioral sciences with weather hazard practices and policies, this project collects time-sensitive information to identify how households and weather stakeholders (forecasters, emergency managers) in mountain and inland communities received, perceived, and responded to risk information related to Hurricane Helene. The project then integrates social and behavioral science data with physical and built-environment characteristics using geographic information systems and multivariate modeling to explore how these contextual characteristics and factors may influence warning reception and protective decision making. The research advances fundamental knowledge in: (1) understanding the decision-making context among mountain and inland community households and weather hazard decision makers impacted by Hurricane Helene; and (2) identifying physical, social, and environmental factors that prevent or support hazard warning reception and protective decisions in mountain and inland communities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-11

This project examines the geomorphic imprint of extreme flooding and mass movements in Southern Appalachia associated with Hurricane Helene. These events represent a rare opportunity to consider how highly altered catchments episodically recruit and redistribute sediment and carbon. As a conceptual model, scientists expect that episodic mass movements formerly introduced large quantities of wood and sediment that created reach- to catchment-scale geomorphic and ecological heterogeneity. The persistence of these effects varied through time and space as transport capacity and the ability to rework mass movement materials increased downstream. The removal of mass movement materials in tandem with extensive land-use in these anthropogenically modified catchments has simplified river corridors in the region. Scientists consequently have limited understanding of how, how much, and where mass movement deposits once shaped catchments. This project involves an early career investigator and students. It will expand regional partnership and collaboration with conservation organizations that are working to restore stream function in the southern Appalachian Mountains. Little attention has been given within the scientific literature to the role of mass movements in recruiting and redistributing carbon and sediment in catchments in Southern Appalachia, largely because the rarity in these events, the transience of the outputs, and eventual removal of deposits by land managers. The few studies that do exist have mostly been limited to the Western United States, and their findings of limited applicability in more humid settings. The long return interval of recent events creates a unique opportunity for the principal investigator to start documenting the temporal persistence of wood and sediment redistribution at these locations. The objectives of this project are to: 1) quantify mass movement effects on recruitment and rapid redistribution of wood and sediment in catchments with varying morphologies in Southern Appalachia and 2) understand how those effects scale with stream order. The investigator hypothesizes that mass movement effects will scale with stream order where lower order streams will recruit more wood and sediment from mass movements, but rapid redistribution of carbon and sediment will occur at varying intervals downstream in higher order streams. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

AC motor drives are widely utilized in many on-the-move energy technologies (e.g., electric vehicles and industrial or medical robots) to control the speed or position of a mechanical scheme. The industry is constantly seeking lightweight, efficient, and reliable solutions for these high-performance AC motor drives. Recent advancements in semiconductor materials have enabled electrical engineers to design ultrafast switches and motor drive systems with higher efficiency and power density. However, the ultrafast switches can cause severe voltage stress on the motor stator winding insulation, reducing the motor lifetime and eventually leading to unexpected shutdowns. This collaborative research will address such reliability concerns through developing the technology of smart coils. Since the proposed technology avoids the conventional bulky and lossy filters, it will advance the compactness of high-performance motor drive systems. In this project, innovative educational modules will also be collaboratively developed to inspire prospective undergraduate and graduate students to pursue education and careers in applications of control theories in power electronics and motor drives. This project aims to develop the technology of smart coils for AC motor drives. The envisioned smart coil technology will make the surge impedance of the motor windings adaptively vary by the sharpness of the voltage pulses which are produced by a drive, travel along cables, and reach the motor terminals. The evolving technology of ultrafast wide bandgap semiconductor switches enhances the efficiency and power density of AC motor drives by minimizing the size of passive components and cooling apparatuses. However, the sharpness of the generated voltage pulses can induce reflected waves in the cable and overvoltages at the motor terminals. The smart coil technology can mitigate the overvoltage stress caused by the reflected wave phenomena regardless of the length of the power cables. Unlike conventional approaches for mitigating reflected wave phenomena that use bulky and lossy passive filters, the smart coil technology will enable AC motors much more compatible with the emerging wide bandgap-based fast-switching drives. This technology can also lead to more electric powertrains with high efficiency, high power density, and high reliability. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

The Research Data Management Education Summit brings together leading educators across domains to increase the quality of Research Data Management education. Research Data Management is a fundamental skill for today’s scientists with data central to new discoveries and the progress of science. The preservation, security, access, and reuse, of research data requires professionals equipped to facilitate the tasks to protect the investment of data collection and increase its value through better access. The Summit advances the field by reviewing existing courses and programs across disciplines and delivering a curricular roadmap focused on the most vital knowledge, skills, and abilities for Research Data Management. A more standardized education benefits all fields and society to best prepare the research data professionals who build, operate, and maintain the U.S. research cyberinfrastructure. The Summit participants include leading professionals and educators training the next generation of professionals supporting Research Data Management. Research Data Management focuses on all stages of the data lifecycle, including data planning, collection, description, access, use, preservation, secure destruction where required, sharing, and reuse of research data. These research data professionals are essential as funding agencies, publishers and industry move towards more open science and increased artificial intelligence readiness for data that aligns with the FAIR and CARE Data Principles. Workshop attendees actively participate in sessions throughout a day dedicated to improving the consistency and quality of Research Data Management education. The event includes activities related to a review of existing educational materials and approaches as well as the creation of a curricular roadmap, including courses and competencies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Solid state transformer (SST) is deemed as a revolutionary technology for future power systems. It is much more compact than the conventional electromagnetic transformer, with significant advantages of controllability both in power flow control and power quality regulation. However, one major technical barrier that constrains the practicality of SST is the low reliability compared to the conventional transformers. This is due to the large device count including semiconductor transistors, auxiliary circuits, and passive components. Currently, the reliability of SST has received little attention, which constrains their commercialization and adoption by industry. This project will develop data-driven digital twin models for SSTs that will facilitate prediction of component degradation and prevention of catastrophic failures. This is aimed to significantly improve the reliability of SSTs for safety-critical applications, such as future power systems and electrified transportation applications. The proposed modeling and design methods will result in new classes of power electronics design tools and will enable a fully integrated design process that will generate new topologies and save substantial design and implementation time. Further, these approaches will enhance reliability modeling where reliability can be accurately estimated from at design stage even for newly synthesized architectures. Regarding educational impact, this work presents an opportunity to apply artificial intelligence to power electronics engineering. Hence, the outcome of the project will upgrade power electronics teaching curricula and provide students with an effective skillset for future power engineering. To address the challenge of reliability of SSTs, this project will develop a comprehensive systematic framework of online health monitoring for SSTs to significantly improve the reliability in the face of electric faults. The proposed health monitoring framework will include online prognosis and diagnosis of potential electrical faults that SSTs could be subject to, targeting common semiconductor switching faults and health degradation in high-frequency transformers. Specifically, a portfolio of critical SST parameters will be monitored through a smart gate driver that will be integrated with the power electronic building blocks, so degradation in the semiconductor modules can be predicted and diagnosed during the fault inception stage. A novel data-driven digital twin approach is proposed to predict the behavior of the SST converter modules and it will compute health performance indices to make the technique more computationally efficient compared to full physical model computations. Fast online diagnostic algorithm will be developed and embedded in the SST microcontroller, so a fault can be identified and characterized, to minimize downtime cost and avoid cascading failures. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2024-09

Many individuals face multiple challenges to consistent desired contraceptive use. Inconsistent contraceptive use in the postpartum period is associated with unintended short interpregnancy intervals (SII). In fact, 70% of all SIIs are unintended and put families at higher risk of unintended SIIs. SIIs increase the risk of poor postpartum mental and physical health outcomes such as preterm birth, postpartum depression, and maternal and infant morbidity and mortality. Contraceptive education is one solution to improving consistent desired contraceptive use and decreasing the subsequent unintended outcomes. When provided prenatally, contraceptive education can increase contraceptive uptake and increase consistent utilization in the postpartum period. However, contraceptive education is not consistently provided due to time limitations and availability constraints of traditional prenatal appointments. Yet, when contraceptive education is provided, it frequently misses opportunities to simultaneously intervene on other important factors that might impact consistent contraceptive use like couple involvement, paying utilities, poor job training, and assistance finding information and healthcare resources needed to ensure consistent contraceptive use. Planning Together is a couple-based multi-level contraceptive education program to improve consistent desired contraceptive use postpartum via (a) harnessing existing support by including couples in the contraceptive education and optimize couple communication by teaching couple communication skills to improve joint contraceptive decision-making and planning process and (b) reducing transportation challenges and knowledge gaps. Additionally, Planning Together offers a flexible delivery method (asynchronous and synchronous components) that will increase availability of education. Specifically, we aim to develop the Planning Together protocol using community-engaged dyadic semi-structured interviews with pregnant couples who can get pregnant on their own and individual semi-structured interviews with health professionals to gain a variety of perspectives to ensure we meet the needs of all families. Second, we will test the acceptability, feasibility, and fidelity of the Planning Together protocol in a single-arm pilot test. Execution of these aims will provide the first demonstration of the feasibility and acceptability of the Planning Together protocol. This project will provide the necessary pilot data for future NIH funding (R01). Planning Together has the potential to redesign existing family planning education modes to improve consistently desired couple contraceptive usage, with the longer-term goal of reducing short interpregnancy intervals to improve families’ mental and physical health.

NSF Awards · FY 2024 · 2024-09

Data literacy is the ability to ask questions, analyze, interpret, and draw conclusions from data. As the world and the workplace become more data-driven, students need to have stronger data literacy across multiple disciplines, including science. This project uses an instructional framework, Data Puzzles, to investigate how to support middle grades teachers learning to include data literacy in their science teaching. Data Puzzles integrate mathematical and computational thinking with ambitious science teaching instructional practices and contemporary science topics. Students engaging with Data Puzzles resources can analyze real-world climate science data using web-based data analysis tools to make sense of science phenomena and develop data literacy. An emphasis across topics is on how uncertainty influences data analyses and the strategies and tools used to make sense of data. Teachers in the project will learn about data literacy, data analysis and data science tools, and how to integrate them with science content. The project builds on prior work to design the Data Puzzles instructional framework to develop teacher professional learning resources and models for supporting data literacy and sense making. A primary goal is helping teachers to learn how to confidently integrate data literacy and sensemaking in science teaching. The design-based research study includes mixed methods data to document the professional learning experience and students’ experience using the modules in classrooms. The study of teacher learning includes self-efficacy and teaching vision surveys, video of professional learning sessions, artifacts, and interviews. The study of students’ learning includes interviews and surveys with students. The project will develop resources for teacher and student learning that can be shared with researchers and educators. The Discovery Research preK-12 program (DRK-12) is an applied research program that seeks to significantly enhance the learning and teaching of science, technology, engineering, and mathematics (STEM) by preK-12 students and teachers. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for funded projects. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Public health and bioeconomics are two examples of fields that can benefit from the funded work. By developing a framework to study higher order interactions, i.e., simultaneous interactions, the funded work will provide novel tools to analyze complex systems. The COVID-19 pandemic was challenging to control because people could catch the disease from accumulating many short exposures to multiple infected people, i.e., from higher order interactions, which are rarely considered in epidemiological models. Similarly, the efficient transfer of goods was another casualty of the pandemic due to supply-chain disruptions. Higher order interactions, in which goods are exchanged simultaneously, can substantially expedite the transfer of goods and increase the robustness and resilience of supply-chains to disruptions. The general framework that will be developed in this grant will use a tractable biological system to develop mathematical tools to study the causes and consequences of higher order interactions. The mathematical models and tools developed will be general, to allow application to other systems, such as communication, disease transmission, and social learning. The work will be published in general journals with a wide interdisciplinary readership and the analysis code will be made publicly available. Both PIs have a strong track record of recruiting and facilitating the success of students from groups that are unrepresented in the sciences and this commitment to mentoring a diverse population of trainees in interdisciplinary work will continue. To further disseminate the work to the general public, podcast episodes will be produced and distributed widely. Collective outcomes, such as the social behavior of animals, emerge from interactions among system components. While substantial work has been devoted to examining the intricate network of interactions among animals, these interactions are described and analyzed as dyadic events. However, multiple individuals can interact simultaneously. For example, an alarm call is broadcast to multiple individuals at once rather than through multiple one-on-one interactions. Despite the important conceptual and functional differences between dyadic and higher order interactions, there are only few methodological approaches that emphasize the higher order nature of social interactions. The proposed work will examine the causes and consequences of higher order interactions, and the feedback between them, by adapting and implementing existing mathematical tools from algebraic topology, simplicial sets, in novel ways. Specifically, the aims include to determine the conditions under which higher order interactions emerge; to examine the consequences of higher order interactions; and to investigate feedback between causes and consequences of higher order interactions to uncover potential evolutionary pathways for their emergence. Social insects are an especially powerful system for examining the questions in the proposal because of the profound fitness consequences of interactions among individuals for the group. Therefore, the proposed work will use foraging and food transmission of Argentine ants (Linepithema humile) as a model system to examine the internal and external causes and consequences of higher order interactions. Project outcomes will enable innovative approaches to fundamental and generalizable questions which are currently beyond our reach. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

What can allow a few isolated cases of an infectious disease to blossom into an outbreak and further expand into a true pandemic? This is the driving question for the Center for Analysis and Prediction of Pandemic Expansion (APPEX). Biomedical and physical, ecological, socio-behavioral, economic, built and natural environmental, and information access factors are all likely to contribute to these perfect storm scenarios. In isolation, the contribution of each aspect may seem minor, or even overlooked, only leading to serious impacts when acting in synergy. This vastly complicates how to study, understand, and prepare to address pandemic risks. The APPEX Center is predicated on the idea that the greatest barriers to multidisciplinary insights in pandemic science exist when disciplinary researchers fail to appreciate, or even be aware of, the value of other fields in addressing complex research questions. The APPEX Center focuses on enabling multidisciplinary collaborations specifically focused on combinatorial risk scenarios that need simultaneous consideration by multiple domains and disciplines. In this way, APPEX provides for the development of a rigorous hierarchy of evidence for pandemic risk, leading to improved methodologies for scenario-to-scenario comparison, and creates and meets audacious challenges in multidisciplinary hypothesis generation, model/tool building, and information infrastructure. The APPEX Center assembles a core team of researchers and practitioners spanning many areas of expertise to foster participation from the entire science community. Bringing together and materially supporting diverse teams of experts and decision makers in pandemic science, APPEX seeks to tackle questions about pandemic expansion that can only be answered at the interface among disciplines and domains. Operationally, APPEX research groups employ a previously piloted Guided Self-Organizing Teaming Process (GSOTP) in which targeted research questions are inspired by proposals from individuals, but tackled by a multidisciplinary team that coalesces around the idea and collaboratively refines it into a clear, compelling challenge, motivating the engagement of all team members and their domains. APPEX goes beyond existing research on disciplinarily targeted factors affecting pandemic risks and instead provides an enabling framework for synergy, complementing domain-driven research efforts. As such, APPEX ensures that the vision of pandemic science is proactive, focusing on framing how to meet complex challenges, improving both our ability to respond to existing disease threats and to be flexible, nimble, and adaptable to the next emerging pathogen we cannot yet anticipate to increase health security regionally, nationally, and globally. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Nuclear physicists who seek to stay in academia aim for permanent positions as university faculty or lab scientists. Those positions require one to conduct and lead research, but also to supervise students/postdocs in their work. Most will draw on their experiences as students, but mentoring is more than just guiding a research project. Just as most physics faculty candidates come without any training in teaching, most physicists enter their permanent positions with no mentoring training. The PIs of this award will lead twenty-two (22) early career physicists in an 8-hour mentoring workshop that will precede the American Physical Society (APS) Division of Nuclear Physics (DNP) 2024 meeting in Boston, MA. The mentoring workshop will explore aspects that contribute to successful mentor/mentee relationships, help participants develop effective mentoring practices, and build a mentoring network. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2024 · 2024-09

ABSTRACT In utero, organized and predetermined patterns of auditory structural and neural pathway development set the stage for early language acquisition.15 The very low birth weight (VLBW) preterm infant, born at 24-30 weeks gestation is at a critical stage of structural and functional auditory development in a suboptimal environment.3, 15 The Neonatal Intensive Care Unit (NICU), vastly different from the protected uterine environment, is full of high pitched alarms and harsh mechanical sounds from lifesaving respiratory equipment positioned in close proximity to developing auditory structures,8 putting VLBW infants at significant risk for speech and language delays.2, 3 Compounding the suboptimal ambient auditory environment, NICU hospitalization leads to sparse exposure to directed speech,210, 211 which has been correlated with poorer neurocognitive outcomes on Bayley III testing at 18-36 months of age.2, 4 Preliminary data from our going longitudinal project with VLBW preterm infants form birth through 18 months suggest that speech input continues to be limited post NICU hospitalization. Further, delays in vocabulary growth are already observed by their first birthday, although large variability exists. The proposed project harnesses our existing VLBW preterm cohort to examine how gestational age, health and demographic factors, and initial language development trajectories, influenced by parent-child communication patterns, contribute to the rapid emergence of language typically observed in the second to third year of life. To capture this critical developmental phase, we will follow the current cohort of VLBW preterm infants through 36 months (corrected age), longitudinally collecting measures of quantitative (e.g., adult word count) and qualitative language input (e.g., proportion of infant- vs adult-directed speech, contingent responding) and language proficiency (i.e., vocabulary size, speech processing efficiency, online novel word learning, Bayley IV developmental scores), and compare their trajectories of language growth with those of age- matched full-term infants. Results from the proposed project will advance our understanding of factors that impact risk and resilience for language growth over time, both in full-term neurotypical infants and in an at-risk preterm population. Examining factors associated with variability and timing of language emergence within the VLBW preterm population compared to age-matched full-term infants will inform our understanding of why some infants struggle while others flourish. Early identification of infants at increased risk for language delays will provide opportunities for early and targeted interventions to ameliorate health through improved language outcomes.

NSF Awards · FY 2024 · 2024-09

Geometric flows are evolution equations that describe motions of surfaces, or their higher dimensional analogues, with speeds determined by their curvatures. Of significant interest in this research are the mean curvature flow and the Ricci flow, which are often likened to the diffusion of heat and the heat equation. These flows leverage the concept of diffusion to canonically deform geometric objects towards equilibrium states, which are significantly easier to characterize or analyze. Geometric flows have thus demonstrated valuable geometric applications, particularly in classification theorems and geometric inequalities. Notable examples include the utilization of Ricci flow to the resolution of the long-standing Poincare conjecture, and the application of inverse mean curvature flow in establishing the Riemannian Penrose inequality, a crucial statement in general relativity. Beyond geometry, geometric flows find extensive use in various physical problems. For instance, mean curvature flow plays a role in describing interface evolution in multiphase physical models. Likewise, it is employed in material science to model the growth of cells, grains, and bubbles. Additionally, a discrete version of Ricci flow is applied in data science, such as in community detection. The study of geometric flows and their diverse applications represents a vibrant and influential area of mathematics. This project aims to enhance the field's impact by involving graduate students in different facets of research and fostering collaborations among researchers across diverse disciplines and institutions. The forthcoming research will concentrate on ancient solutions to the mean curvature and Ricci flows. Ancient solutions refer to solutions that have existed for all times in the past. They are of particular interest due to their significance in studying singularities, which present challenges to the geometric applications of these flows. Understanding the geometry and behavior of ancient solutions is therefore crucial. Despite significant advances in this area in recent decades, there remain large classes of such solutions about which little is known. The proposed project seeks to offer classification results for ancient solutions of mean curvature, mean curvature type, and Ricci flow, without making noncollapsing or compactness assumptions. Our strategy involves developing a method to construct new collapsed ancient solutions and classify them based on specific symmetry assumptions. Drawing on our established methods for constructing and characterizing ancient convex solutions to mean curvature flow, which have proven successful and adaptable, we aim to explore the potential existence of a dichotomy theorem for Ricci flow akin to the one for mean curvature flow, by introducing a width concept for Ricci flow. Finally, by refining and enhancing these techniques, we aim to furnish a more comprehensive classification result for convex collapsed solutions of mean curvature flow. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Numerous small organisms that swim, fly, smell, or feed in flows at scales in which inertial and viscous forces are nearly balanced rely on using branched, bristled, and hairy body structures. Such structures have significant biological implications. In coral, they determine the success rate of catching prey through particle capture, and there are many other organisms which similarly rely on the transition of their body structures from solid surfaces to leaky/porous “rakes.” Active particles (e.g. swimming plankton and microorganisms) can also enhance or reduce capture through their own behaviors. Although flows around such organisms have been studied before, the fluid dynamic mechanisms underlying the leaky-rake to solid-plate transition and how it affects particle capture remain unclear. The goal of this project is the development of open-source numerical software to elucidate the fluid dynamics of such biological and bioinspired filtering arrays, including how the individual and collective behavior of the active particles affects filtering outcomes. In addition, the Investigators will design software training materials and complementary classroom modules. The Investigators will engage in public outreach for all ages through targeted modalities for different age demographics such as participating in the Skype A Scientist program for younger children and coral reef conservation courses aimed at older retirees which will incorporate math and physics. The natural world is replete with mesoscale filters that are significant to biological and biomedical applications. These are, however, challenging multiscale problems that require high accuracy to resolve the flow through complex structures that are sensitive to small perturbations. To understand these problems, the research team aims to 1) develop a Method of Regularized Oseenlets that can be employed as a gridless method to resolve flows through filtering structures for Reynolds numbers near unity, 2) develop and test force spreading operators that are independent of the grid size for the immersed boundary method, 3) develop and implement numerical techniques to efficiently describe the interactions of agents in flow with moving, complex 3D boundaries, and 4) implement tools from sensitivity analysis and uncertainty quantification to reveal which parameters are important for particle capture and to guide the development of more detailed agent and flow models. Upon doing so, the project will focus on the filter feeding of plankton by Cnidarians and will address the following (i) identifying small-scale flow patterns within rigid and flexible filtering structures at the leaky-to-solid transition, (ii) understanding how small-scale flow patterns affect the capture of Brownian swimmers, and (iii) determining the collective effect of fundamental behaviors in small organisms for capture and targeting in the presence of flow. The frameworks developed here can be broadly applied to other biological systems where mesoscale exchange occurs, e.g. the filtering structures of fish or the chemical sensors of insects and crabs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.