University of North Carolina at Charlotte

NSF Awards · FY 2026 · 2026-07

Fungi pose challenges and opportunities in both the field and hospital, where they can cause devastating diseases, create useful compounds, and promote the well-being of other organisms. The roles of fungi as pathogens, beneficial species, and nutrient cyclers within ecosystems are dramatically affected by their relationship with other microbes present in the same place. Bacteria can even directly inhabit fungi, living internally within their cells and communicating with them through unknown molecules. This project seeks to understand how endofungal bacteria communicate with and control the fungi that they inhabit. The long-term goal of this research is to inform new biotechnology applications to control fungi causing disease and promote fungi providing benefits. Complementary educational goals will integrate undergraduate students in course-based and laboratory-based research experiences early in their college journeys, to improve their training as new scientists. Additionally, visitors to the campus botanical gardens will learn through short courses, informational booths, and new signage about the role of microbes in nature and biotechnology. Though bacteria and fungi interact everywhere from soils to hosts, a lack of understanding how bacterial secretion systems facilitate cross-kingdom microbial interactions with fungi represents a barrier to our ability to predict and alter emergent properties of microbial communities. To gain a framework-level perspective, this project will interrogate bacterial-fungal interactions for two tractable organisms that occupy the endofungal niche but that exhibit vastly different relationship specificity and interaction mechanisms with their hosts. In aim 1, the focus will be on the effector protein repertoire of fungal-targeting Type III secretion systems, with a goal of molecular characterization of proteins transported by syringe-like secretion systems in Mycetohabitans spp. and other Burkholderia-related endobacteria that are highly coevolved with their host fungi and divergent from free-living species. The second aim is to discover the function of the harpoon-like, Type VI secretion system in Luteibacter mycovicinus, a newly described species that genetically resembles free-living relatives and can transiently colonize different fungi. This project will combine in silico prediction, transcriptomic sequencing, mutagenesis strategies, phenotyping assays, and reporter technologies to answer the central question at both cellular and organismal levels. 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 2026 · 2026-03

This project will contribute to the national need for well-educated scientists, mathematicians, engineers, and technicians by supporting the retention and graduation of high-achieving, low-income students with demonstrated financial need at University of North Carolina at Charlotte, Rowan-Cabarrus Community College, Cleveland Community College, Gaston College, and South Piedmont Community College. At least 120 scholars pursuing associate in science degrees and/or bachelor’s degrees in biology, data science, or computer science will receive scholarships of up to $15,000 per year depending on each scholar’s unmet need. Scholars will receive faculty mentoring and the project will build strong scholar cohorts through opportunities for shared courses, undergraduate research, and service-learning. Additional activities for scholars include tutoring, success coaching, and focused career services. The overall goal of this Track 3 S-STEM project is to increase STEM degree completion of academically talented, low-income undergraduates with demonstrated financial need. There is a significant national need to grow the STEM workforce and nurture key talent that will ensure economic competitiveness and provide domestic leadership across critical sectors. This project directly speaks to this need by supporting STEM student success, which will strengthen the workforce in computer science, data science, the biological sciences, and other key areas of need. The project will be assessed by an experienced evaluator and project research focuses on developing scholars’ transfer and science capital. Research findings and the data generated through project evaluation will contribute to the knowledge base regarding effective strategies to support talented, low-income students in STEM. This project is funded by NSF’s Scholarships in Science, Technology, Engineering, and Mathematics program, which seeks to increase the number of academically talented, low-income students with demonstrated financial need who earn degrees in STEM fields. It also aims to improve the education of future STEM workers, and to generate knowledge about academic success, retention, transfer, graduation, and academic/career pathways of low-income 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 2026 · 2026-03

Trusted hardware is the foundation of cybersecurity. The rapid proliferation of computing and communication systems with increasing computational power and connectivity into every sphere of modern life has brought security to the forefront of system design, test, and validation. The design, manufacturing and the distribution of microchips, printed circuit board, as well as other electronic components are becoming more sophisticated and globally distributed with a number of potential security vulnerabilities. Thus, hardware plays an increasingly important and integral role in system security with many emerging vulnerabilities and defense mechanisms relating to hardware. The International Symposium on Hardware Oriented Security and Trust (HOST) aims to facilitate the rapid growth of hardware-based security research and development. This award will support students to attend HOST, held in Washington, DC, May 4-7, 2026. The project's broader significance and importance include professional development for undergraduate and graduate students as well as continued growth of the symposium. This award will enable students to learn about the latest tools, design methods, architectures, circuits, and novel applications of secure hardware. Students will also receive ample opportunities for networking with researchers, interactions with industrial sponsors and exhibitors for internships and full-time positions, and opportunities to receive feedback on their own research. Selection criteria include presentation at the conference, being first-time attendees, financial need, and institutional and demographic diversity, with a goal of growing the talent pool of cybersecurity researchers. The hardware security research community itself will benefit by having a broader and larger audience at the event. 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 · 2025-12

Flow boiling and condensation are crucial to the efficient and safe operation of electronics cooling, power generation, refrigeration, water purification, chemical processing, and among others. Two-phase flows are also subject to a wide range of instabilities at the liquid-vapor interface. These instabilities can lead to significant thermal performance degradation, reducing heat transfer coefficient, increasing pressure drop, and causing overheating. To prevent process disruptions or thermal performance deterioration, it is of utmost importance to enhance the understanding of instability mechanisms and continually monitor them. This project seeks to probe the physical mechanisms that dominate flow instabilities in microgravity using wideband acoustic emission (AE) sensing that measures and analyzes dynamic behaviors through acoustic waves. Two-phase flows are complex phenomena where many physical mechanisms simultaneously contribute to the measured signals, resulting in overlapping acoustic signatures and intrinsic noises during ground tests. The long-term microgravity environment on the International Space Station (ISS) inherently decouples the acoustic signatures of the physical mechanisms during two-phase flows and enables the examination of the leading transport mechanisms. The project team will also organize outreach events and create educational materials such as posters, brochures, podcasts, and videos to explain the advantages of research brought by the microgravity environment on ISS. This project aims to advance the fundamental understanding of the transport mechanisms that govern liquid-vapor interfacial instabilities in flow boiling and condensation using wideband AE sensing, with a focus on both the critical heat flux (CHF), the maximum achievable heat flux during flow boiling, and the flow regime transition during flow condensation. The project will fill this broad knowledge gap with three specific aims. First, a self-contained AE sensing module will be developed and benchmarked for individual transport processes including bubble departure, turbulence, and capillary flows in lab-scale tests before its deployment on ISS. Second, the role of interfacial waves and turbulent diffusion in flow condensation will be probed using both ground-based and microgravity flow condensation tests. The latter will be performed using the flow boiling and condensation experiment (FBCE) facility on ISS with the deployed acoustic sensing module. Third, the dominant transport mechanism during flow boiling flow regime transition and CHF will be examined. This project will provide valuable insights into interfacial instabilities of flow boiling and condensation, which are critical to the design and optimization of condensers and boilers that maximize heat transfer and minimize energy consumption. This project will make an impact on power generation, semiconductor manufacturing, chemical processing, and decarbonization of transportation. 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 · 2025-12

This CAREER project aims to develop a miniature sensor capable of measuring how heat flow within living cells is affected by variations in thermal conductivity. Thermal conductivity – the ability of a material to conduct heat – is a fundamental material property, and variations in thermal conductivity inside a cell can provide valuable insights into biological processes such as metabolism, enzyme activity, and cell communication. This project will create a microdevice specifically designed to detect variations in thermal conductivity within single cells. The knowledge gained from this research has the potential to significantly enhance medical diagnostics and treatments. Understanding the thermal properties could lead to improved therapeutic techniques. Furthermore, insights from this work could benefit studies on disorders and diseases by elucidating how heat flow dynamics influence cellular health and disease progression. This project also includes initiatives to advance education in science, technology, engineering, and mathematics (STEM) and to promote diversity. Research findings will be incorporated into workshops and curriculum development, inspiring students and engaging the public. By tackling fundamental scientific questions and fostering educational growth, this project supports the national interest by advancing scientific knowledge and delivering societal benefits through technological innovation and improved health outcomes. This CAREER project aims to develop an innovative microelectromechanical systems biosensor to measure thermal conductivity at the subcellular level using the 3-omega method. Thermal conductivity is a key biophysical property that governs how heat is transferred. This project seeks to investigate localized thermal conductivity and its correlation with cellular functions such as metabolic activity, enzyme dynamics, and signal transduction pathways. The research involves the design, fabrication, and calibration of a biosensor, which will achieve precise measurements of thermal conductivity. Experimental studies will focus on various cell models. The findings are expected to advance understanding in cellular thermodynamics and contribute to the development of diagnostic tools and therapeutic interventions. In cancer therapy, for example, precise thermal conductivity data could optimize techniques such as hyperthermia treatments, thermal ablation, and cryotherapy. Additionally, this work may benefit research on metabolic disorders and neurodegenerative diseases by uncovering how heat transfer properties affect cellular function and disease progression. 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 · 2025-10

The ability to establish, confirm and protect an individual’s identity is essential to the function of our society. Biometrics uses physical measurements of the body to identify an individual. A secure biometric identity and secure processes that use identities allow individuals to function in our growing on-line society with reduced risk of identity theft and fraud. Establishing identity is critical for preventing and detecting crime, terrorism, fraud and human trafficking. Challenges facing the arena of identification include the use of Artificial Intelligence (AI) to create images, videos and recordings as a means to intentionally deceive, and the potential existence of preference within the identity systems. In Phase III, the Center for Identification Technology Research (CITeR) expands impact in generative AI, advanced computing, and digital identity management, along with fair, transparent and explainable biometrics to address challenges that both commercial and government sectors face in today's society. CITeR will conduct research to measure outcomes resulting from approaches to mitigate specialized loss functions in neural network models. Additionally, projects to ensure robust identity systems through comprehensive evaluation of challenge response and liveness methods to prevent replay attacks, as well as methods to recognize natural or synthetically added information will be explored. Clarkson University will focus research in the areas of spoofing biometrics, liveness to protect systems from spoofing attacks, biometric cryptosystems for protecting biometric templates, longitudinal biometrics in children. CITeR plays a critical role in addressing the challenges in the ability to establish, confirm and protect an individual’s identity in today’s modern society. CITeR will support opportunities for sharing and learning through the development of educational videos, STEM outreach efforts for public schools and the continued development and hosting of Challenge Problem workshops for industry and government organizations to address challenges in the problem space. Clarkson University will lead the efforts to establish a micro credential program for biometrics and continue discussion with external organizations to help develop content for a new Certified Biometric Professional (CBP) course. 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 · 2025-10

This project serves the national interest by transforming engineering education to enhance student retention and promote the success of learners with varied educational needs through the use of adaptive learning (AL) methodologies. This Level 3 Engaged Student Learning project utilizes innovative technologies to deliver personalized educational support and enhance faculty capacity across three institutions: North Carolina State University, the University of North Carolina at Charlotte, and North Carolina Agricultural and Technical State University. By addressing key challenges such as learning gaps, imbalances in instructional supports, and faculty adoption of new technologies, the project seeks to create a cohesive curricular spine of interconnected AL course modules in Statics, Dynamics I, and Dynamics II. The AL platform offers tailored content, assessments, and feedback, promoting deeper student engagement and enabling faculty to support the varied needs of learners better. These efforts aim to achieve measurable gains in student retention and academic outcomes through personalized support strategies that are automatically tailored to each learner's level of understanding. The project also develops readiness models and best practices to foster widespread institutional adoption and scalability, ensuring the sustainability of AL methodologies beyond the project period. The project has two primary goals: (1) enhancing student learning by implementing a curricular spine that interconnects key engineering courses and supports personalized, just-in-time learning interventions; and (2) empowering faculty and institutions to adopt and sustain AL practices through targeted training and resource development. The research evaluates the effectiveness of AL interventions in enhancing student retention and engagement, while providing insights into the faculty and institutional needs for successful implementation. A comprehensive evaluation plan tracks progress, assess learning outcomes, and refines interventions to ensure effective learning. Findings are disseminated widely to inform best practices and encourage the adoption of AL methodologies in engineering education and other STEM disciplines. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. 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 · 2025-10

City centers nationwide are rapidly evolving from a traditional downtown into a vibrant “Central Activity District.” Yet, city leaders, small businesses, and residents lack timely, trustworthy data on how people move through and experience these public spaces. This pilot project will convert existing security cameras into privacy-preserving “urban intelligence sensors.” Instead of transmitting recognizable faces, each camera’s video is processed on a small computer installed on-site, where people are represented only as anonymous motion heatmaps. The resulting insights, crowd-flow patterns, congested walkways, accessibility barriers, and potential safety risks will be shared in real-time with planners, shop owners, event venues, and the public through dashboards and mobile alerts. A strong partnership among UNC Charlotte, Charlotte Center City Partners, Central Piedmont Community College, Law Enforcement, and a network of local businesses ensures the work is co-designed with the very communities it serves. By demonstrating that advanced AI can be deployed ethically, transparently, and with measurable civic benefit, the pilot offers a replicable model for safer, more walkable downtowns nationwide. The pilot will make fundamental Artificial Intelligence and Computer Vision innovations that transform raw pixels into high-dimensional thermal “motion tokens,” enabling accurate detection of trajectories, dwell times, queue lengths, and anomalous behaviors without storing personally identifiable information. An online active-learning framework, reinforced by feedback from security staff and site managers, continuously adapts detection thresholds to the unique rhythms of college campuses, art venues, entertainment arenas, retail corridors, and nightlife districts. Real-time statistics are fused into spatial heatmaps, crowd-density graphs, and occupancy forecasts, which are served to stakeholders via a web dashboard and mobile app. Statistical modules aggregate foot traffic trends to guide lighting schedules, signage placement, staffing decisions, and public safety interventions. Research outcomes will include validated algorithms, open latent-motion datasets, and evidence-based policy recommendations, advancing urban informatics, responsible AI, and edge computing while establishing a scalable blueprint for AI-assisted city planning across the United States. 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 · 2025-10

Non-technical Abstract: This project aims to revolutionize the discovery of new solid-state materials that can precisely control the mobility of ions and electrons, an essential step toward building the next generation of energy storage systems, neuromorphic computers, and smart sensors. By leveraging advanced artificial intelligence (AI), machine learning (ML), and automated synthesis tools, the team will develop a transformative approach to design solid-state ion conductors using multi-element doping, enabling materials tailored for next-generation energy and electronic systems. A central goal is to establish a new data-driven approach to achieve an optimal balance of ion and electron conductivities for targeted applications while ensuring material stability during operation, a task difficult to achieve using traditional trial-and-error techniques. The project will also provide hands-on research and training opportunities in AI-driven materials discovery, fostering collaboration among U.S. and Canadian universities, national laboratories, and industry partners. Technical Abstract: This research will develop and apply a closed-loop, data-driven framework to design and optimize multi-element co-doping strategies in alkali-ion conductors. By integrating AI/ML-accelerated property prediction, high-throughput computational modeling, autonomous synthesis, and in-situ characterization, this project will systematically investigate how co-doping influences ionic transport, electronic structure, and lattice stability across bulk phases, grain boundaries, and interfaces. A fast, iterative inner loop will enable the screening of thousands of dopant combinations, while a slower outer loop will focus on extracting mechanistic insights and ensuring scalability, feeding knowledge back into the predictive models. Target systems include sodium- and lithium-ion based oxides and halides, where varying the balance of ionic and electronic conduction is critical for applications ranging from batteries to neuromorphic computing. The project will generate foundational design rules for tuning transport properties through co-doping, creating new pathways for energy-efficient materials innovation. 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 · 2025-10

The broader impact of this I-Corps project is based on the development of a wearable, wireless temperature sensor designed for laboratory animals, aiming to improve temperature monitoring in biomedical research and clinical applications. By providing a non-invasive, continuous, and stress-free method for monitoring body temperature, this device enhances animal welfare and improves the quality of research data. Accurate and reliable temperature data from laboratory animals leads to better results in drug testing and biomedical studies, ultimately accelerating the development of effective therapies and medical interventions. By minimizing physiological alterations caused by invasive methods or sedation, the sensor ensures that outcomes are more reflective of true biological responses. The device's wireless charging capability increases operational efficiency and reduces maintenance costs. Beyond animal research, the technology holds potential for human healthcare applications, such as non-invasive patient monitoring in intensive care units. The broader commercial potential includes advancing biomedical research practices, improving the drug development process, enhancing patient care, and setting new standards for temperature monitoring technologies across various industries. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. The solution is based on the prior development of a wearable, wireless temperature sensor utilizing advanced microfabrication techniques and Micro-Electro-Mechanical Systems (MEMS) technology. MEMS thermocouples leverage micromachining techniques to produce very small-scale thermocouples for precise and continuous temperature monitoring. The sensor features a minimally invasive microneedle design, enabling rapid and accurate detection of temperature changes in biological environments. This innovation addresses critical gaps in existing temperature monitoring methods by providing a non-invasive, continuous monitoring solution that preserves the physiological integrity of subjects. By improving the accuracy and reliability of physiological data from laboratory animals, the technology enhances the validity of experimental results, particularly in drug testing and biomedical research, thereby advancing scientific understanding and supporting the development of new therapies. 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 · 2025-10

Non-technical Description: "Chirality" refers to objects that cannot be superimposed onto their mirror image. At the molecular scale, spatial asymmetry in mirror-image molecules, known as enantiomers, gives rise to distinct biological, chemical and pharmacological properties. In a chiral mixture, enantiomers are typically identified based on chiral optical effects; however, the differential signals between enantiomers of opposite handedness are inherently weak. While nanophotonic platforms, such as metasurfaces, can enhance light–matter interactions, it remains a challenge to achieve strong chiral response in these media through nanostructure engineering. The overarching goal of this research is to develop a photonic optimization framework for freeform metasurfaces in which strong chiral near-fields can be created at specific molecular positions. This will enable enhanced chiral fields for direct interaction with analytes, thereby advancing chiral sensing and imaging with ultrahigh sensitivity. This framework will explore the limits of nanophotonic chiral sensing, uncover the underlying electrodynamic mechanisms, and develop prototypes of ultrasensitive sensors for enantioselective analysis. In addition, the proposed project will promote the adoption of open-source software packages and provide training opportunities for undergraduate students pursuing STEM careers. Technical Description: The research aims to optimize optical chirality in freeform metasurfaces through the development of a near-field topology optimization framework. This approach provides a direct pathway to enhancing chiral near-fields and customizing their spatial distributions in nanostructured media, allowing for direct overlap with analytes for enhanced chiral sensing. The specific goals are centered around three main thrusts: (1) exploring chiral enhancement limits in resonant metasurfaces, (2) studying chirality transfer dynamics between molecules and resonators, and (3) developing prototypes of nanophotonic sensors for enantioselective analysis. The project encompassing theory, design, and experiment offers a comprehensive workflow for developing ultrasensitive chiral sensing platforms. Furthermore, the project will promote the interdisciplinary adoption of photonic design tools and enhance STEM education through cutting-edge research. 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 · 2025-10

This research project aims to develop a groundbreaking instrument capable of measuring mass changes in live single cells with unparalleled precision and speed. The instrument uses small pipettes that capture the cells using gentle pressure and measure tiny weight changes in thousandths of a second. By enabling scientists to observe how cells regulate their mass during crucial processes such as migration and differentiation, this tool will fill a significant gap in biological research. Additionally, the project will benefit society by advancing scientific knowledge and fostering new technological innovations. The project will also include educational outreach activities (e.g., internships and mentoring) that are open and available to all participants to provide hands-on experience in scientific research and entrepreneurship. The goal of this project is to develop a transformative instrument for measuring cellular mass changes with picogram accuracy and millisecond temporal resolution. The instrument will utilize small pipettes that can precisely attach to individual cells using gentle pressure, eliminating the need for adhesion molecules that might alter cell behavior. This technology will enable mass measurements of mammalian cells and support high-throughput analysis using pipette arrays with embedded sensors. By integrating several technical innovations, the instrument will achieve accurate and frequency measurements in liquid environments. This innovative approach will allow continuous monitoring of cell mass changes, applicable to studies on cell division, metabolism, migration, and more. Collaboration with industry partners will facilitate the commercialization of the instrument, ensuring its broad application in biological research and potential therapeutic developments. The research outcomes, including device designs and data, will be disseminated through peer-reviewed publications. 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 · 2025-10

Semiconductors are foundational to the technologies that power modern life, from artificial intelligence and telecommunications to healthcare and the automotive industry. U.S. leadership in these sectors depends on advancing domestic semiconductor research and manufacturing. While the U.S. pioneered the field, it now produces only about 10% of the global semiconductor supply and relies heavily on Asia, especially Taiwan. Taiwan leads the world in semiconductor manufacturing, supported by top-tier research institutions, leading companies, a robust supply chain, and strong government investment. The International Research Experiences - Pathway for Research and Innovation in Semiconductor Manufacturing (IRES-PRISM) program creates a summer research opportunity for U.S. undergraduate and graduate students to engage in cutting-edge research on semiconductor devices and manufacturing in Taiwan. Over five years, the program will support 40 student researchers from the U.S. to gain hands-on experience, immerse themselves in Taiwan’s vibrant semiconductor ecosystem, and build lasting research partnerships. Working with mentors from both the U.S. and Taiwan, students will be well-positioned to advance U.S. innovation and global leadership in the semiconductor industry. Built on established partnerships with leading institutions in Taiwan across multiple engineering disciplines, the IRES-PRISM program advances frontier semiconductor research in thermal management, IoT sensors, and data-driven, sustainable manufacturing. Leveraging Taiwan’s global leadership in semiconductor manufacturing, the program positions participants at the forefront of U.S. semiconductor innovation. Students engage in undergraduate co-ops, graduate research, and dual master’s degrees in semiconductors, immersing themselves in a rich, industry-relevant research environment supported by Taiwan’s strong industrial base, advanced facilities, and supply chain. IRES-PRISM also fosters sustained collaboration through faculty exchanges, promoting long-term partnerships and transformative technological advancements. The program offers robust technical and professional skill development through workshops in research, leadership, career development, team building, and global awareness. Participants share their research findings to raise public awareness of advancements in semiconductor research and manufacturing. Leveraging the project team’s ongoing semiconductor workforce development initiatives, IRES-PRISM also generates educational materials to amplify its broader societal and technological impact. 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 · 2025-09

This I-Corps project investigates the commercial potential of an optical microscopy technology that enables real-time, label-free imaging of biological samples with high accuracy. Traditional imaging systems that measure cell morphology and dynamic behavior are often prohibitively expensive, limiting access to advanced imaging tools. This solution addresses the need across biological research and medical diagnostics for cost-effective, noninvasive imaging systems. By integrating the technology with conventional microscopes, the solution reduces both acquisition and operational costs, expanding usage to smaller laboratories, clinics, and educational settings. This technology has potential applications in disease diagnosis and cellular biology, offering a more affordable approach to visualize and analyze nanoscale structures. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of a compact, low-cost optical attachment that transforms existing microscopes into dynamic quantitative phase imaging systems capable of real-time, label-free, four-dimensional imaging. The system leverages inexpensive liquid crystal materials and custom-designed optics to achieve nanoscale precision in measuring cellular morphology. Unlike conventional systems that require costly optical components and sample staining, this approach preserves sample integrity while delivering high spatial and temporal resolution. Adoption of this innovation may improve health outcomes, accelerate biomedical research, and promote greater access to scientific tools, serving the national interest in improving healthcare, research, and educational infrastructure. 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 · 2025-09

The Charlotte Data Science Corps (Charlotte-DSC) project aims to expand regional and national data science capacity and education while bringing data science expertise to small community-serving organizations in the Greater Charlotte region. By forming student cohorts from three local institutions--UNC Charlotte, Johnson C. Smith University, and Central Piedmont Community College--this initiative will bring data science knowledge and skills to communities through hands-on collaborations with grassroots nonprofit and community-based organizations. These students will apply data-driven approaches to help local organizations make informed decisions that support economic mobility, public health, and community development. In turn, Charlotte-DSC will build a robust regional data science workforce by creating flexible and affordable pathways into the field for students from a variety of backgrounds. This project promotes the progress of science, enhances education and economic opportunity, and serves the national interest by increasing participation and capacity in data science--an increasingly vital domain for prosperity and societal wellbeing. The Charlotte Data Science Corps is a dual-focus initiative addressing community-based learning and flexible, affordable pathways to data science education. Through a partnership among two 4-year universities and a community college, the project will design and implement a Data Steward Program that places students in real-world data projects with small nonprofit organizations in the Greater Charlotte region. This hands-on, immersive model will offer students meaningful experience in applying data science to real challenges in sectors such as health and human services, while also providing partner organizations with much-needed data capacity. In parallel, the project will develop and enhance stackable and flexible academic pathways across the three institutions to support entry, transition, and completion of data science programs. Over the award period, Charlotte-DSC plans to support 54 undergraduate students with stipends and mentoring, while conducting outreach to approximately 150 high school and college students per year. The project will contribute to local and regional economic growth by empowering both students and community organizations with modern data skills and tools. This project is supported by the Data Science Corps program, which supports data science education and training to build a strong national data science infrastructure and workforce. 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 · 2025-09

Computer simulations have revolutionized materials discovery, allowing scientists to test thousands of possibilities digitally before conducting expensive laboratory experiments, which accelerates innovation while dramatically reducing costs. There are critical national challenges that require advanced materials that perform under extreme conditions. Examples include next-generation computer chips essential for AI and quantum computing, and nuclear energy infrastructure materials that can withstand extreme radiation and heat in reactors. This project develops new mathematical tools and simulation methods enabling more efficient, accurate, and reliable materials modeling, accelerating breakthroughs in national nanotechnologies, clean energy systems, and resilient infrastructure. In addition, the project strengthens the U.S. scientific workforce by training students in advanced mathematical techniques that span multiple disciplines. Through international collaboration with the University of Warwick in the UK, both graduate and undergraduate students will engage in hands-on research experiences, inspiring them to pursue careers in science, technology, engineering, and mathematics. Overall, this project bridges mathematics, engineering, and computing to address real-world challenges in designing advanced materials, while supporting federal priorities in technological leadership, energy security, infrastructure resilience, and fostering the next generation's STEM talent pipeline. This project establishes a new theoretical framework and methodologies for coarse-grained dynamics and numerical simulation to model materials defect evolution. The central intellectual merit lies in developing rigorous mathematical foundations for coarse-graining strategies that capture spatiotemporal correlations and in creating novel algorithms for efficient and robust computing. The research delivers three key contributions: (1) a robust theoretical framework for selecting coarse-graining variables, quantifying model deviations, and addressing non-Markovian effects while incorporating high-dimensional phase space geometry; (2) numerical methods ensuring stability and accuracy of large time-step integrators, investigating scheme ergodicity, and optimizing parameters to balance error sources; and (3) a software package applying these findings to real computational materials science problems. The proposed methods will improve accuracy and efficiency in modeling lattice vacancy generation, crystal solid annealing, and dislocation motion, benefiting materials science, mathematics, and education. This project will train students in challenging, multidisciplinary applied mathematics at the UNC Charlotte in the U.S. and the University of Warwick in the U.K. Moreover, the ability to travel will give the U.S.-based students access to beneficial interdisciplinary, international research networks, outreaches and training. 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 · 2025-09

In the deep ocean, primary producers and their viruses are understudied relative to microbes in the surface ocean. This study is using cutting-edge techniques to identify key viral players and the processes by which they affect microbial carbon cycling in the dark ocean. It advances understanding of ocean biogeochemistry and provides new insights relevant to marine biotechnology and ocean exploration. The investigators are mentoring postdoctoral and undergraduate students and integrating their scientific findings into media products such as podcasts to share discoveries about “viruses in the wild” to inspire public interest in deep-sea exploration and microbial oceanography. In this project, the researchers are studying the biodiversity, mechanisms, and rates of virus-induced carbon cycling in a deep-sea hydrothermal vent system. While chemoautotrophic microbes are known to contribute to these hotspots of primary productivity, the functional role and biogeochemical impacts of viruses that infect them remain critical gaps in our understanding of the dark ocean’s carbon cycle. The researchers combine metagenomics with stable isotope probing (SIP) to identify links between metagenomic diversity and ecological function. They combine carbon-13 stable isotope probing (13C-SIP) with metagenomics, nanoscale secondary ion mass spectrometry (NanoSIMS), and microscopy to reveal the diversity, activity, mechanisms, and rate of virus-induced carbon cycling, and they use targeted sequencing of both cellular and viral-particle samples, as well as quantitative SIP-metagenomics, to identify virus-host interactions underpinning key microbial processes regulating carbon cycling in the deep sea. 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 · 2025-09

Scientists have long been interested in the ways that populations organize themselves and change over time. Previous research demonstrates that people and groups make choices about systems of organization based on many variables, including availability of resources, environmental stability and fertility, established traditions, and newly emerging practices. This collaborative project conducts research to explore the impact of environment and resource use on long-term changes in social organization, including questions about if, when, how, and why groups developed stratified societies. The project findings advance knowledge and theory about what variables have predominant influence in the evolution of social organization. The study’s use of macro- and microbotanical analytical techniques (including phytolith analysis of soil samples, analyses of starch granules and phytoliths extracted from dental calculus, and integrative microbotanical and stable isotope analysis) advance administrative priorities for investments in understanding the adoption of biotechnological innovations in scientific research. The project also provides training for graduate students in these analytical and other archaeological methods. The team investigates how environmental conditions changed and influenced choices about social organization across thousands of years, examining whether different environments (i.e., cloud forest vs. dry grassland) may have promoted different choices and opportunities that led to different organizational structures and strategies. The team excavates key locations to collect evidence of site occupation and use, and to reconstruct the environmental legacy of a river valley through specialized analyses of human, animal, and plant remains and remote sensing of the valley. Through these methods, the team tests if the environment afforded more flexibility and options in the choices that people could make about resource acquisition and use, especially when compared with other sites from the same period. 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 · 2025-09

Laser based micro- and nano-manufacturing is a key component for the resurgence of American manufacturing. To achieve this goal requires laser manufacturing to have higher processing speed and higher patterning resolution over large areas. A recently discovered phenomenon that has the potential to transform femtosecond laser manufacturing is explored in this research. By overlaying a dielectric substrate with a single atomic layer of graphene, MoS2, or hBN as a sensitizer, a femtosecond pulse can ablate sapphire, glass, or quartz 10-25 times faster. This project seeks to generate fundamental knowledge of this process, determine its applicability and limitations for laser manufacturing, and develop strategies to mitigate these limitations. The knowledge gained from this project will advance the understanding of light-matter interaction in the extreme limit where an atomic-thick hot dense plasma could play a vital role. This new process can have direct impacts on laser manufacturing in high-precision surface texturing with higher throughput. Combined with recent advances in transferring large-area atomic layer materials, this process can enable large scale super-resolution patterning on flat or curved substrates. This project also supports the future workforce in this emerging area of advanced manufacturing through student training. This project will address the following scientific questions: What is the mechanism for such a significant rate enhancement with only one atomic layer? Can this enhancement break the diffraction limit in far-field patterning? Is this process universal in that it can be applied to other atomic layer materials and beyond transparent dielectrics? Is this process self-terminating as the solid sensitizer vanishes and how can this be mitigated? Motivated by the necessity to address these unresolved scientific issues and the potentially transformative opportunities offered by this process, this project will execute a comprehensive study plan and generate transferable fundamental knowledge to advance this new field. Firstly, this project will investigate the interaction between substrate atoms and an atomic layer warm dense matter. This knowledge will enable controlling the ablation rate using the laser pulse width and the number of atomic layers. Secondly, this project will demonstrate ablated features with acceptable sidewall angles. Combined with atomic layer materials with sub-wavelength features, this knowledge will enable super-resolution patterning in the far field and in air. Thirdly, this project will extend this process to a wide range of substrates and sensitizers, enabling other researchers to adopt this new process. Lastly, this project will demonstrate that this process is self-terminating and could be mitigated by a flat-top-shaped laser beam and/or a renewable sensitizer based on nanolayer water. This knowledge will enable this process to ablate deeper holes, lines, and areas, which are building blocks for surface texturing. 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 · 2025-08

Organisms rely on a diverse repertoire of immune pathways to detect and respond to microbes, thereby enabling mutualistic interactions and preventing infection. Variation in the number of genes composing the immune system varies widely across the tree of life and has been hypothesized to be important for interactions with the microbiome, including differential susceptibility to pathogens between individuals. Yet, its role in regulation and innovation for marine invertebrates remains poorly understood. The research team will utilize a coastal sea anemone to study the impact of copy number variation of key immune genes in the ecological and evolutionary dynamics of this symbiosis. Insights from this research will provide actionable information for translation into efforts to conserve species critical for aquaculture and ecosystem resilience. This project will provide mentoring and training for trainees across educational stages at the University of North Carolina at Charlotte to prepare them for careers in STEM, including biotechnology. Additional research and educational opportunities will be provided through course-based undergraduate research experience, outreach through a local science museum, and a new University of North Carolina at Charlotte center focused on the intersection of biology, computation, and environmental health. Knowledge of the environmental, genetic, and molecular factors involved in modulating expression of the innate immune system is essential to understand and predict how host species shape their microbiomes and respond to pathogens. The integrative research approach in this project will determine how variation in copy number of key immune genes among individuals of a cnidarian species relate with changes in the survival, physiology, associated microbial community, and molecular responses for this animal host. Nematostella vectensis has been utilized as a model for ecological and evolutionary genomics by the research team to understand the genetic variability of this invertebrate, the role for nucleotide variation in local adaptation, and heterogeneity of the microbiome. The proposed research will utilize (a) comparative genomics and transcriptomics to determine the extent and impact of copy number variation in populations of this species, (b) metagenomics and experimental infections to determine the dynamics of the microbial community, and (c) the diverse molecular and genomic toolkits including transgenesis for N. vectensis to test long-standing hypotheses concerning the impacts of gene duplications on host-microbe interactions. The team will integrate these data to connect genotype to phenotype to illustrate the phenotypic consequences of immune gene copy number variation and the evolutionary/regulatory mechanisms facilitating innovation and specialization of the innate immune system. 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 · 2025-08

This BRITE project explores how emerging quantum computing can enhance the design of high-performance engineering structures. As products such as aircraft components, automotive frames, and 3D-printed parts become more complex, engineers rely on computational tools to optimize material usage and performance. However, traditional methods struggle to keep up with the scale and complexity of modern design problems. This research seeks to develop a new hybrid computational approach that combines quantum and classical computing to improve design speed, efficiency, and quality. The project will also create educational materials to help students and professionals understand how quantum computing can be applied to real-world engineering challenges. This research introduces a hybrid quantum-classical approach to topology optimization that strategically applies quantum computing to the most computationally demanding steps in the design process. The project focuses on three main contributions, seeking to solving large, sparse linear systems using quantum methods; estimating design sensitivities via quantum gradient estimation without relying on adjoint solvers; and updating material distributions using variational quantum circuits optimized through quantum natural gradient descent. These research tasks are intended for near-term quantum hardware and will be implemented and tested on both simulators and available quantum processors. By targeting numerical bottlenecks of classical topology optimization, the proposed framework aims to improve solution efficiency, scalability, and robustness. The research outcomes will include a validated set of hybrid algorithms, performance benchmarks on relevant structural design problems, and accessible computational tools to support broader adoption in engineering and scientific 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 2025 · 2025-07

The Sub-national Nonstate Actor Governance (SNAG) project introduces a new measurement strategy and public dataset to measure territorial control at the local level within conflict zones, tracked over time. Understanding how groups gain or lose territorial control, and thus how conflicts begin, evolve, and end, is essential to national security and preparedness. Yet scholars, policymakers, and military strategists lack reliable and accessible techniques to measure and monitor territorial control within conflict zones. Existing empirical research is focused on a limited number of conflicts for which there happen to exist reliable measures of local-level territorial control over time. This limits ability to understand conflict more generally, and to apply knowledge to new threat environments. This research draws upon open-source information to ensure a transparent process that is easily replicated across contexts and adapted to new measurement challenges. The project uses machine learning and natural language processing (NLP) tools to automatically detect mentions of belligerent activity and control in a corpus of open-source texts, which are then used to produce spatially and temporally disaggregated estimates of rebel and government territorial control. The Subnational Nonstate Actor Governance (SNAG) project measures nonstate actors’ territorial control and governance at the local level, capturing temporal variation throughout conflict, comparable across contexts. This project makes both substantive and methodological contributions, generates new publicly available data capturing nonstate actors’ territorial control, uses an approach that translates across contexts to facilitate comparative analyses. The PIs annotate text from a corpus of news reports from conflict zones, identifying indicators of rebel and government territorial control with location and time information. These annotations are then used to train a new natural language processing pipeline, which is applied to the remainder of the corpus to automate the process of extracting relevant information from the full corpus. The information produced by this process is incorporated into a measurement model to produce fine-grained spatio-temporal data on conflict belligerents’ territorial control within conflict zones, facilitating systematic comparison of these phenomena within and across conflicts. The subnational territorial control data are used to investigate basic research questions related to the causes and consequences of territorial control and governance, fundamental to understanding the security risks in “differently governed” spaces, the efficacy of counterinsurgency aid, and the consequences for state-building after conflict. Methodologically, SNAG contributes new tools for generating geospatial data from text and for developing spatial latent variable models adaptable for additional social science applications. 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 · 2025-07

Mosquito-borne infectious diseases remains a major threat to health and prosperity across much of the world, causing nearly a quarter-billion illnesses each year. Stopping transmission of mosquito-borne diseases requires knowing exactly where infected mosquitoes and susceptible humans share the same space, yet most maps still only focus on coarser spatial scales like the villages or districts. This award integrates geospatial data like satellite imagery, population count data, and artificial intelligence (AI) to locate those high-risk micro-regions in Southern Africa. By revealing Potential Human-Vector Contact Zones (PHVCZ) that concentrate both human movement and mosquito activity, the work will guide bed-net distribution, indoor insecticide spraying, and community outreach to the places that save the most lives while reducing costs. Open-source software, training workshops, and publicly released risk maps will strengthen disease-control capacity in partner countries and provide a template for confronting other mosquito-borne threats such as dengue and Zika, thereby promoting national and global welfare. This award develops a novel, integrated geospatial framework that applies advanced machine learning techniques to map disease-transmission risk. High-resolution satellite imagery is processed with computer-vision methods and enriched with building information, road networks, land-cover classifications, community points of interest, and population data to generate seasonally stable maps of human activity zones encompassing residential areas, farms, commercial centers, and transportation corridors. These human-activity maps are combined with weather variables and mosquito-surveillance records from research centers in Southern and Central Africa to drive computational models that simulate vector-human contact patterns. A specialized statistical approach links the predicted density of these contact zones to ten years of regional malaria data, iteratively refining model parameters until outputs mirror observed disease patterns across diverse transmission settings. Annual probability maps, open-source software tools, and comprehensive documentation will be released to equip researchers worldwide with resources for detailed mapping of vector-borne disease risk. 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 · 2025-07

Bats are known to host more viruses than any other mammal species; understanding the spillover potential of these viruses, known as a zoonotic outbreak, has become increasingly important as humans encroach on the habitat of wild flora and fauna. At the same time, bats are essential to maintaining ecosystem health through seed dispersal, pollination, and insect control. This paradox emphasizes the urgent need to understand the disease ecology of bats in the interest of global health. Understanding how to monitor, characterize, and disseminate information about pathogen spillover is critical to global public health and Southeast Asian countries are at the highest risk of wildlife zoonotic outbreaks due to immense biodiversity found in this region. The urgency of these circumstances requires training of the future generation of scientists to connect and collaborate with scientists in high-need regions, where scientists, educators, and public health officials may lack the necessary training to monitor wildlife in a genomic and evolutionary framework. This IRES project trains U.S. student participants in fieldwork methods and analytical approaches for studying pathogens in wildlife reservoirs using affordable and portable biotechnology. The students are also trained in education and science communication techniques necessary for sharing information related to these topics. The program hosts up to 8 U.S. students per year at the Center for Biodiversity and Endangered Species (CBES) in Ho Chi Minh City, Vietnam. Students conduct sampling in a national park inventorying the bat biodiversity and microbes occurring within the region. To understand the diversity of microbes in the environment, how they circulate, and how they evolve within and between their hosts, scientists must sample the data directly from the environment, extract genetic material, sequence this genetic material, and characterize the microbes in the sample with computational methods to visualize the results. Students participating in this research are being trained in genomic surveillance techniques of zoonotic pathogens with low-cost “backpack laboratory” approaches. The project provides a high-quality international research experience for U.S. students that builds collaborative monitoring efforts with scientists in Vietnam while also establishing scientific communication training protocols to facilitate scientific discussion amongst disciplines and dissemination of appropriate information to policymakers and the public. Bats are used as a framework for teaching these protocols, as they are central to public health in the Indo-Pacific. The U.S. participants benefit from the experience by learning about the ecology, evolution, and immunology of many unique bat species distributed throughout Vietnam and Southeast Asia. However, these techniques are not unique to bats and can be extrapolated to any environmental monitoring and surveillance program. During the students’ research experience, they engage in data collection and analysis for two major projects. The first is a metagenomic surveillance project that involves collecting bat feces, comparing pathogens present at two sampling localities, and documenting in a library of pathogenic strains of bacteria with metadata documentation in a public repository. The second is a science communication project that includes writing a series of podcasts with local collaborators to be released throughout the year, a three-minute thesis style competition of the study abroad experience, and social media engagement to communicate the importance of bats to ecosystem health. Overall, the students are being trained in field-based genomic methods, data analysis techniques with an evolutionary perspective, and data visualization to be used in peer-reviewed publications and public dissemination of results. 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 · 2025-07

The “Wasserstein-1 metric”, also known as earth mover's metric, is a measurement of distance between probability distributions quantifying the least cost needed to transport the mass of one distribution onto the other. This metric appears not only in pure mathematics, but frequently in applied mathematics and computer science as well. For example, a digital image may be modeled abstractly as a probability distribution over a 2-dimensional region, and the Wasserstein distance provides a natural measurement of similarity of images under this model. Despite their pervasiveness, these metrics are often difficult to compute, and large aspects of their geometric properties remain poorly understood. This project aims to advance this theory, with a particular emphasis on approximations of Wasserstein metrics through simpler metrics, such as the classical p-metrics on Euclidean spaces. Conferences and seminars will be organized as part of the project. In calculating the Wasserstein distance between two distributions, the cost of transporting mass depends on the geometry of the underlying metric space on which the distributions are defined. A main goal of the project is to classify those metric spaces whose Wasserstein-1 metric admits a biLipschitz embedding into the Banach space L1. One side of this question will involve showing the nonexistence of L1-embeddings for certain metric spaces, and on this side the methodology to be used will largely be based on concepts from analysis on fractals. The other side of the challenge will be to show that L1-embeddings do exist for other metric spaces, and towards this end an incorporation of tools from geometric measure theory and metric geometry is planned. Finally, the current methods of proof for existing results rely heavily on the linear theory of Banach spaces. Another main goal of this project is to develop nonlinear methods that yield new insights into existing results as well as provide approaches toward solutions of questions unattainable via linear techniques. 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.