University of Alabama Tuscaloosa

NSF Awards · FY 2025 · 2025-06

Cells release small particles called extracellular vesicles (EVs) to communicate with each other. Such EVs may be useful for drug delivery and for treating diseases. At present, it is difficult to manufacture high-quality EVs consistently. EVs produced in bioreactors vary greatly in size and composition. In medical applications, this variability makes it difficult to apply consistent EV dosages. This project will develop new biomanufacturing methods to manufacture EVs accurately, consistently, and in large quantities. This project will benefit society by making EVs a more reliable tool for disease treatment. Further benefit will result from training students in research, course development in biomanufacturing techniques, and outreach to pre-college students. This project aims to solve two key problems related to EVs: scalable production and consistent characterization. To achieve this, a combined approach that integrates flow filtration and size focusing will be adopted. This research will utilize multiple complementary techniques to analyze EVs and establish critical links between key characteristics, such as EV concentration and protein content. These insights will enable the development of more precise and standardized dosing strategies for future medical applications. In addition, the biological effects of the optimized EVs will be elucidated using drug-resistant breast cancer cells as model systems. These functional tests will validate the effectiveness of our production process, and also confirm that the improved dosing strategy enhances therapeutic reliability. By addressing key bottlenecks in EV production and analysis, this project will significantly improve the ability to produce and measure EVs in a scalable and consistent way and advance the use of EVs in drug delivery and regenerative medicine. Beyond scientific advancements, this project will also support education and workforce development in biotechnology and biomanufacturing through training graduate and undergraduate students in a collaborative, cross-disciplinary research environment. It will also engage younger students in STEM through mentoring science fair projects and developing a new interdisciplinary course on biomanufacturing to prepare the next generation of scientists and engineers. This Future Manufacturing award is co-funded by the Division of Materials Research (DMR) in the Directorate for Mathematical and Physical Sciences (MPS) and the Directorate of Social, Behavioral and Economic Sciences’ Office of Multidisciplinary Activities (SBE/SMA). 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 · 2025-05

The project TANDEM will advance Second Spine technology to enhance worker health, safety, and productivity. Second Spine is a bioinspired passive back-support exosuit that is lightweight, strong, and offers assistance without restricting mobility. The project will synergize product development, user engagement, and policy alignment to create a sustainable pathway for widespread adoption of Second Spine. It will ensure advanced exosuit technologies are accessible and affordable to all workers. Furthermore, it will enhance workforce access by enabling individuals with physical limitations to participate in labor-intensive jobs and foster a more variable and adaptable workforce. Specifically, TANDEM will profoundly impact aging workers as they will be able to continue contributing without compromising their well-being. The project will build trust by promoting transparency and public engagement via education and workforce development activities. The insights from the project will lead to an exosuit technology that can reduce the chance of occupational injuries in American workers performing demanding and/or repetitive tasks. Additionally, it will contribute to the standardization of exosuit design and performance metrics to help establish industry-wide benchmarks. This technology leverages the engineering principles of tensegrity to mimic the muscle-tendon-bone arrangement of the human spine. Key deliverables and milestones will include development of Second Spine product, its digital twin, and in-lab and in-field performance evaluations; exosuit adoption and safety best practices; exosuit risk assessment tool; supply chain management model; and policy and workforce outreach workshops. The project goals will broadly focus on (a) improving user comfort and biomechanical harmony by incorporating different design concepts; (b) improving personalization, task assistance, predictive maintenance, design and innovation, and achieving cost savings and sustainability; (c) assessing effectiveness of Second Spine by analyzing multiple factors including working performance, effectiveness in work environments; (d) engaging with key stakeholders to contribute to discussions on integrating new technologies, like exosuits and exoskeletons, within existing safety regulations; (e) organizing workshops to explore the use of emerging technologies in occupational safety and health. 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 · 2025-05

This doctoral dissertation research studies the impacts of integrated medicine on birth outcomes in hospital settings. The investigators specifically address several variables related to patient needs including emotional, physical and clinical support to test the ways that integrated support from both clinical and non-clinical experts improves maternal health outcomes. The research findings contribute to the understanding of how clinical and non-clinical experts can be integrated into obstetric models of medical care to meet patient needs and to coordinate maternal care. In addition to providing training in anthropological sciences to a graduate student, research findings will inform the expansion of public knowledge regarding access to integrated medical care and its associated benefits for maternal health. In order to study the impacts of integrated medical approaches, the investigators utilize a mixed-methods and community engaged research design including semi-structured interviews, quantitative survey instruments, and focus groups. Validity and reliability of the data will be tested using community-based participation. The research contributes to medical anthropology, participatory research methodologies, and the social scientific study of public health and medicine. 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 · 2025-05

Adolescent aggression has severe psychological, social, and economic repercussions. Maladaptive forms of anger regulation and hostile attributions often underlie aggression. This project examines the role of peer interaction in influencing anger regulation and hostile attributions in adolescence. This research aims to advance understanding of how individual and interpersonal factors may work together to predict increases or decreases in youth aggression. This project contributes to workforce development by providing research training opportunities for students. This project uses short-term longitudinal design and observational methods to address three research aims. The first aim is to describe variation in adolescents’ anger and their attributions during discussions of a focal problem between friends. The second aim is to examine how attributions and anger influence adolescents’ problem perceptions and preference for aggressive strategies for the focal problem. The third aim is to examine how observed attributions and patterns of reported anger during problem talk predict changes in anger regulation, attributions, and aggression over one year. Towards these aims, the research team conducts observations of conversations between friend dyads over the course of one year, and collects other relevant data using adolescent and parent surveys. The findings of this project are expected to advance theories about peer influence and peer emotional socialization as well as to inform programs designed to prevent aggression and promote healthy peer relationships in adolescence. This project is jointly funded by Developmental Sciences Program and the Established Program to Stimulate Competitive Research (EPSCoR). 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 · 2025-04

This three-year REU Site: Multidisciplinary Polymer Exploration for Undergraduate STEM Researchers is a multidisciplinary exploration of polymers and their range of applications. Polymers are crucial to current research and industrial innovations. The areas of additive manufacturing to biological engineering to soft robotics and so on require a foundation in polymer science and employ multidisciplinary collaborative efforts. Engaging students earlier in their academic preparation about the scope of polymer research and applications will help inspire and equip the next generation to investigate and contribute solutions to the complex global challenges that society faces. Ten undergraduate students each year will engage in research projects for 10 weeks. Participants will perform hands-on work in research laboratories with direct faculty mentorship and engage in a variety of social and professional development activities that foster a sense of belonging and support students’ career trajectories. This program will target recruiting students from communities and institutions where and for whom research opportunities are difficult to access. The program will culminate in presentations by students and poster presentations to give students opportunities to practice their scientific communication skills and to demonstrate their research to their peers. Fundamental knowledge acquisition, augmented by hands-on research experiences, interactions with experts, and opportunities to practice scientific communication will support REU students as they develop their skills and understanding about multidisciplinary approaches which drive discovery and innovation in polymer-related fields. Other important training and professional development includes educational workshops related to technology-transfer, information literacy and communication, entrepreneurship, research/STEM identity, and leadership, to bolster the impacts of this research experience. Undergraduates will learn about the tools, modern research techniques, problem solving approaches, and the expanse of research-based career opportunities which integrate polymers. REU students will participate in the University of Alabama Strategic Graduate Partnerships Initiative (SGPI) to give them unique opportunities to meet with students from other disciplines and learn about what research looks like and how it is performed. Participants will also have opportunities to present a poster at the relevant national research conference (such as the American Institute of Chemical Engineers annual meeting). 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 · 2025-04

NONTECHNICAL SUMMARY This award supports fundamental theoretical research and education on the transport of electric charges and heat in disordered materials. These systems contain scatterers, such as impurities or lattice imperfections, which can cause electrons to frequently change directions. The presence of disorder is often unavoidable in complex materials, including quantum materials. Conversely, disorder leads to fascinating phenomena, especially when quantum mechanical effects are important and interactions between the electrons are strong. The project focuses on two key systems: 1. The disordered electron liquid: The disordered electron liquid near where a metallic state transforms to an insulator in silicon-based transistors is a system for which the strength of interactions and disorder can be tuned by changing the density of electrons. Depending on the density, the material can either act like a metal at low temperatures, allowing electrons to flow freely, or like an insulator by blocking the electron flow. Despite much effort, the physical mechanisms causing this metal-insulator transition are still under debate. The aim of this project is to derive refined theoretical predictions for the transport of charges and heat on the metallic side of the metal-insulator transition with the goal to enable interpretation of experimental data that can advance understanding of this phenomenon. 2. Disordered quantum critical metals: The transport of heat in disordered quantum critical metals represents another focus of this project. In these systems, the interplay of disorder and the complex electron motion that arises from strong electron-electron interactions near a zero-temperature phase transition can cause anomalies in the flow of charge and heat through the material. This research aims to compare charge transport and heat transport in quantum critical metals and to contrast the findings with conventional metals. The proposed research will advance basic knowledge, and add to our understanding of semiconductors, a class of materials that are of great technological importance. In addition to its scientific merit, better knowledge of the fundamental mechanisms of charge and heat transport holds promise for improving energy efficiency in electronic devices. This project also includes educational initiatives, including the development a new mathematical physics course for undergraduates, and a K-12 outreach activity that will be associated with the University of Alabama high school physics contest. In addition, the project will provide research training for undergraduate and graduate students. TECHNICAL SUMMARY This award supports fundamental theoretical research and education on transport and thermodynamics in two paradigmatic disordered electron systems: the two-dimensional electron liquid, and quantum critical metals. The disordered electron liquid near the metal-insulator transition is an electron system close to a quantum phase transition, for which the strength of the two main factors, interaction and disorder, can be tuned externally. The physical mechanisms underlying the observed non-monotonic behavior of the resistance on the metallic side of the transition as well as the metal-insulator transition itself are under debate. Progress in the interpretation of the experimental data requires refined theoretical predictions. The aim of this project is to develop a comprehensive theory of transport and thermodynamics near the metal-insulator transition. Thermal transport in disordered quantum critical metals represents another backbone of the project. In these systems, the interplay of disorder and the effective long-range interaction mediated by collective bosonic modes can result in characteristic non-Fermi liquid behavior of transport properties. A goal of this project is to obtain results for the Lorenz ratio, the ratio of thermal and electric conductivities, which is often used to quantify deviations from Fermi-liquid theory observed in experiments. The main goals of the proposed research are: 1. Disordered electron liquid near the metal-insulator transition: to derive detailed theoretical predictions for the temperature dependence of the resistance, the thermopower, the specific heat and the spin susceptibility of the disordered two-dimensional electron liquid near the metal-insulator transition. An important aim of this project is the interpretation of experimental findings in silicon metal-oxide-semiconductor field effect transistors. 2. Thermal transport in strange metals: to explore thermal transport in a strange metal described by a two-dimensional generalization of the Sachdev-Ye-Kitaev model with potential disorder and spatially random Yukawa coupling. Both studies will be based on the nonlinear sigma-model formalism for disordered interacting systems. Deepening knowledge of fundamental mechanisms of thermal transport may help improve energy efficiency in electronic devices. In synergy with the scientific plan, this project includes an education and outreach effort. This includes the development of a new course on mathematical physics tailored to undergraduates, and a K12 outreach activity that will be associated with the University of Alabama high school physics contest. Further impact of this project will lie in research training of undergraduate and graduate 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 · 2025-03

This award funds planning activities for a proposed new Industry University Cooperative Research Center (IUCRC), the Center for Smart Manufacturing using AI-based Revolutionary Technologies (SMART). The SMART center is led by the University of Alabama (UA) in partnership with the University of Alabama in Huntsville (UAH). Advancements in machine learning (ML) and artificial intelligence (AI) have profoundly impacted numerous fields. However, the manufacturing sector has faced challenges in integrating AI at the same pace. The SMART center will leverage data collected through sensors and cameras during the manufacturing process to create and integrate AI technologies that transform the manufacturing sector, delivering enhanced productivity, product quality, factory sustainability, and workforce safety. The center aims to enhance the global strength and competitiveness of the U.S. manufacturing industry, which plays a critical role in economic stability and growth while sustaining technological leadership in key sectors including automotive, aerospace, electronics, and pharmaceuticals. The SMART center is also dedicated to workforce development through specialized training programs that will equip workers with the skillset essential for 21st-century industries. Through a collaborative approach involving universities, industry leaders, and government agencies, the SMART center aligns with national priorities to bolster economic resilience and advance technological innovation. The mission of the SMART center is to foster collaborations among stakeholders in advanced manufacturing to conduct and disseminate applied, pre-competitive research on AI-driven technologies, methodologies, and tools that enable the transformation of the manufacturing sector. The SMART center’s research focuses on four thrust areas: manufacturing productivity, product quality, factory sustainability, and workforce safety. By leveraging advanced AI and machine learning (ML) technologies, including deep learning, reinforcement learning, and large language models, these efforts aim to: (i) optimize various aspects of manufacturing processes, (ii) improve product quality through advanced defect detection systems utilizing analytics and deep neural networks, (iii) enhance resource sustainability by improving energy efficiency and reducing waste, and (iv) boost workplace safety through real-time monitoring and predictive analysis of potential hazards. The UA site will specifically focus on vision-based technologies for manufacturing productivity, product quality, and factory sustainability. Housing state-of-the-art facilities like the Alabama Initiative on Manufacturing Development and Education (Alabama IMaDE), UA provides a unique environment for generating training data, testing AI applications, and validating cutting-edge technologies, ensuring the center’s impactful contributions to the manufacturing industry. 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

Accurately predicting and backtracking pollutants in aquatic environments is an important component of ensuring public health and the sustainability of water resources. This project will develop innovative models that enhance our ability to trace the origins of reactive pollutants in aquifers, a process known as backward tracking (BWT). Traditional BWT methods typically assume standard, or the so-called “Fickian” diffusion, where the spread of pollutants in water is linear over time. However, real-world scenarios often involve “non-Fickian” diffusion, characterized by a more complex, nonlinear spread of pollutants in heterogeneous geological media. This project will address this gap with the ultimate goal of enhancing groundwater management and informing environmental protection policies. The broader impacts include advancing educational initiatives, such as K-12 education and undergraduate/graduate research, in collaboration with local schools and communities. This project will develop and validate a new theory for BWT by incorporating non-Fickian diffusion and reaction models. The primary activities include theory development, model predictability, and validation. The project will propose the adjoint of the tempered stable law to create new BWT models for reactive pollutants experiencing super- and sub-diffusion. Numerical simulations and machine learning techniques will be used to approximate key parameters of these models, enhancing their accuracy and applicability. The models will be validated through real-world applications, including calculating groundwater ages and assessing aquifer vulnerability. The expected outcomes are a robust backward probability theory with corresponding physical models, a comprehensive set of predictive parameters, and an upgraded and validated software suite for practical applications. These advancements are expected to improve the resolution of inverse problems in hydrology, environmental science, and engineering, contributing to better environmental management and policymaking. 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

Apparent inconsistencies between different geologic and geophysical datasets have resulted in decades of active debate about how western North America was formed. One of the longest-held models invokes a shallow subducting oceanic plate beneath the Mojave Desert to Wyoming to large-scale mountain building as far east as the Rocky Mountains. This study tests the viability of the flat slab model against alternative hypotheses, including the collision and translation of a far-traveled terrane, through detailed study of the Pelona-Orocopia-Rand schist. This suite of ancient metamorphic rocks span from California to Arizona, a critical location to distinguish between the tectonic models. The researchers will test predictions about the location, conditions, and timing of tectonic events derived from standard recycling of oceanic crust, flat slab subduction, and terrane collision by determining the age, pressure, and temperature recorded by the metamorphic mineral garnet in the Pelona-Orocopia-Rand schist. The project will promote the development of two early-career women in STEM, foster new collaborations across R1, R2, and PUI campuses, facilitate the training of graduate and undergraduate students from underrepresented groups, and support the development of analytical facilities. The proposed contribution provides a crucial test of conflicting models for the tectonic evolution of the western North American Cordillera by re-evaluating the metamorphic history of the Pelona-Orocopia-Rand schist using modern techniques. The researchers will estimate the conditions of metamorphism using high resolution analytical methods and a variety of modern modeling techniques, including Raman spectroscopy, bulk chemical analysis, and P-T modeling. The timing of events will be evaluated using garnet Sm-Nd and monazite U-(Th)-Pb geochronology. They will provide a unifying regional dataset by sampling across the full extent of documented outcrops rather than using a site-specific approach. The work will support two graduate students from Northern Illinois University and the University of Alabama as well as undergraduate student research at Occidental College. 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 Ham radio Science Citizen Investigation (HamSCI) network is a Distributed Array of Small Instruments (DASI) designed for the study of space weather impacts. The Personal Space Weather Station (PSWS) platform was previously developed through DASI Track 1 program in 2019. PSWS stations have one or more instruments, each capable of sensing a different aspect of the geospace environment. Several stations were deployed as proof-of-concept including those by amateur Ham radio operators and today, the PSWS network consists of over thirty-five stations located primarily in the continental US, but some also in Canada, Alaska, and Europe. It is used to study the ionospheric impacts of solar flares, solar eclipses, geomagnetic storms, traveling ionospheric disturbances, and other small-scale ionospheric variability. This project will provide the backbone for the HamSCI PSWS network to enable a range of scientific investigations by deploying thirty standardized stations capable of observing high frequency (HF) Doppler shifts, HF amateur radio transmissions, Very Low Frequency transmissions and natural radio emissions, and the geomagnetic field. Ten fully automated, Global Positioning System (GPS) disciplined amateur radio transmitters will be also deployed to serve as a new source of GPS-stabilized HF beacon signals. Once deployed, this enhanced network will enable researchers to investigate both local and continental space weather effects, including those caused by traveling ionospheric disturbances, solar flares, and geomagnetic storms. The network has been developed as a collaboration between the professional scientific and amateur radio communities. It thus provides a unique opportunity for participation by and outreach to over 730,000 licensed US amateurs and about 3 million worldwide. This work will improve synergies between professional scientific and amateur radio communities, develop open technologies and observation networks that can be used in conjunction with existing geospace infrastructure, and develop materials that can be used in formal and informal educational institutions to teach space and radio science. HamSCI has a large online presence and following within the amateur radio community. This translates to the potential for extensive public relations and large outreach. This project will also support several undergraduate students’ participation and include major participation of both a Minority Serving Institution and an emerging (non-R1) academic institution. This project is funded by the Geospace Facilities program with co-funding from the Aeronomy program in the Division of Atmospheric and Geospace Sciences. 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

With escalating extreme weather events, aging homes especially those in lower income groups and rural regions face severe energy burdens. Advancements in the field of building energy auditing have been propelled by the integration of sophisticated technologies, such as Unmanned Aerial Vehicles (UAVs), Infrared Thermography (IRT), Computer Vision (CV), Artificial Intelligence (AI), and data-driven Building Energy Modeling (BEM). However, barriers remain in the integrative and effective management and analysis of the data collected by these innovative technologies in real-world practices, particularly in those underserved communities that often lack access to expert technicians, financial resources, and essential technological infrastructure. This project studies the community-engaged, participatory design of an innovative Digital Twin (DT) platform to synthesize advanced aerial imaging, AI analytics, energy modeling, and expert knowledge to pinpoint exactly where and how homes can be improved for energy efficiency. By improving accessibility and efficiency in energy auditing, the project seeks to enhance building sustainability and resiliency in underserved communities. Partnering with civic agencies, technical experts, and local communities in the southeastern United States, this research will explore and overcome barriers to adopting these technologies, contributing to better living conditions and environmental sustainability. This project aims to engage civic agencies and technical experts to participatory design and develop an AI-assisted DT platform that seamlessly integrates cutting-edge auditing technologies, providing effortless access to multi-scale analytics for the efficient auditing and retrofitting decision-making. To achieve this, the planning project seeks to build partnerships within the U.S. southeastern low-income communities, to study three major questions: 1) What are the critical needs and challenges of weatherization for underserved communities. 2) How to overcome the barriers and enhance the adoption of advanced auditing technologies in underserved communities without overwhelming local resources? 3) How can stakeholders conduct appropriate analytics to support their needs in energy performance evaluation and retrofitting decision making? The objectives of the research are: 1) identifying challenges and needs for weatherization in low-income houses, 2) designing DT platform to support advanced technology implementation, and 3) empowering the DT with advanced AI to assist with multi-scale retrofit decision-making. By facilitating the DT platform with user-friendly access to functional tools, alongside exploring the socio-technical dynamics of their implementation, this research seeks to develop actionable strategies that ensure equitable improvements in building energy efficiency and resiliency across all communities. This project is in response to the Civic Innovation Challenge program’s Track A. Climate and Environmental Instability - Building Resilient Communities through Co-Design, Adaption, and Mitigation and is a collaboration between NSF, the Department of Homeland Security, and the Department of Energy. 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

This project develops theory about confrontation initiation, escalation, and termination. It generates new data to assess predictions from this theory. This involves the use of state-of-the-art advancements in artificial intelligence (AI) to train a model that uses a large text corpus to identify events and to describe a range of characteristics for each event. The project will shed new light on how confrontations begin, why some minor confrontations become major conflicts, and what can be done to end conflicts. The data allows real-time descriptions of characteristics as confrontations unfold, which will be use for analysis and pedagogy. This project contributes new theory and data to the study of militarized interstate confrontations. It introduces new theory about the conditions under which confrontations emerge, why they increase in intensity, and how they end. To create a new dataset on confrontations, it first develops and cleans a large text corpora. Each element of the corpora with relevant text is attributed a feature or feature of the dataset. This labelled dataset is then used to fine-tune a BERT classifier, which allows the artificial intelligence model to identify and code subsequent entries automatically. The dataset allows testing of propositions derived from the theory developed in the project, can also be used by other scholars to investigate additional hypotheses, and can be updated in real-time for analysis. 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

The National Science Foundation (NSF) Graduate Research Fellowship Program (GRFP) is a highly competitive, federal fellowship program. GRFP helps ensure the vitality and diversity of the scientific and engineering workforce of the United States. The program recognizes and supports outstanding graduate students who are pursuing research-based master's and doctoral degrees in science, technology, engineering, and mathematics (STEM) and in STEM education. The GRFP provides three years of financial support for the graduate education of individuals who have demonstrated their potential for significant research achievements in STEM and STEM education. This award supports the NSF Graduate Fellows pursuing graduate education at this GRFP institution. 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

This incubation project will advance integrated approaches to artificial intelligence (AI) ethics education in undergraduate science, technology, engineering, and mathematics (STEM) programs. The research team will seek to transform materials from the ethics bowl competition, which is traditionally an extracurricular activity focused on research, consultation, collaboration, and debate, into structured classroom tools. This will help instructors to improve the understanding that students have of AI ethics. The project aims to build a strong community foundation and develop capacity for larger educational initiatives. The project will create and evaluate instructional resources like case studies, instructor guides, and active learning assignments. These tools will provide practical, scenario-based learning experiences to enhance student skills in ethical reasoning, teamwork, and communication. The team will develop and pilot sample resources with participants during a professional conference, workshop the resources at a two-day meeting, and refine and disseminate the resources after the workshop. The project focuses on STEM ethics education, specifically AI ethics. Project goals are to (1) recalibrate STEM education to incorporate ethical reasoning with professional competencies like teamwork, research, and communication, addressing a critical gap in AI education; (2) equip STEM faculty with a new pedagogy to engage students in ethical discourse and analysis; and (3) set new benchmarks in AI ethics education by providing a replicable model for integrating ethical decision-making into STEM disciplines. The impacts of the project include enhancing AI ethics understanding among students, expanding the reach and inclusivity of ethics education by co-creating materials with a broad collection of institutions, and producing deliverables like pedagogical materials, online resources, and community engagement platforms. The project will involve a collaboration with government, industry, and community partners. The curriculum produced will address current ethical challenges in AI and equip students with relevant skills for various professional settings. This project is funded through the ER2 program by the Directorate for Social, Behavioral and Economic Sciences. 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

With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, Professor Pan's group at the University of Alabama - Tuscaloosa is developing technology for rapid analysis and imaging of microscopic motions and interactions of nanomaterials in electrochemical systems. The approach seeks ultrasensitive chemical imaging of particles and their interactions with light to spur chemical transformations. Students working on this interdisciplinary project are trained in both electrochemistry and material science. Educational and outreach activities target recruiting and retention of Alabama students underrepresented in STEM. The project also features community engagement featuring science activities including chemistry demonstration and training modules prepared and disseminated in partnership with Tuscaloosa middle school science teachers. Mechanistic studies show that electrocatalytic activities of electrode materials formed from nanoparticles are highly dependent on structural heterogeneities, electronic and geometric factors, and particle shapes. Catalytic properties of these nanostructured electrode materials are often studied using bulk films. The nature of catalytic reactivity dependence can be obscured during such conventional ensemble-averaging measurements. The Pan lab is working to advance our understanding of these structure-dependent details by developing quantitative analysis methods to reveal the roles of single catalytic nanoparticles in electro- and photocatalytic reactions. Their approach fully integrates light-scattering imaging with microelectrodes to quantify local electro(photo)catalytic activities enabled by plasmonic nanorods while rapidly resolving translational and rotational diffusion, nanorod-enabled chemical transformations, and collision dynamics. The kinetics of catalyzed redox reactions by single nanorods and photoelectrochemical reactions are being investigated to provide insights into single nanorod-mediated (photo)electrochemical activities. 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

This IRES project entitled "Portugal Undergraduate Research Experience in Biotechnology and Life Sciences (PURE BLISS)" provides an intensive international summer research experience for undergraduate students through high-impact interdisciplinary training in biotechnology, biomanufacturing, and bioengineering research that applies basic sciences to pharmaceutical, food, and health applications. There are unmet workforce needs in these fields as recently recognized by the Presidential Executive Order on Advancing Biotechnology and Biomanufacturing Innovation for a Sustainable, Safe, and Secure American Bioeconomy. The IRES PURE BLISS project directly addresses this national need by providing bioengineering-focused undergraduate research training, especially to students from groups traditionally under-represented in STEM. Uniquely, this training is being provided by internationally renowned scientists at the Instituto de Bióloga Experimental e Tecnológica (iBET) in Oeiras, Portugal (a suburb of Lisbon, the capital city of Portugal). The specific objectives of this IRES project include: (1) introduction of bioengineering to undergraduate students and developing related technical skills, (2) increasing student interest in bioengineering careers and research, (3) increasing the students' intercultural maturity via interactions with international scientists and researchers, and (4) expanding the diversity of the undergraduate student researchers with a special emphasis of recruiting from under-represented groups in STEM. The host institution, iBET, is uniquely positioned to provide a full bench-to-scale research environment for both upstream and downstream bioprocessing research at a single site. The student participants' access to such an integrated and comprehensive research environment is poised to catalyze the development of the future U.S. workforce. Furthermore, they are involved in highly relevant and societally important research projects, such as biomanufacturing therapeutic vesicles, regenerative medicine tissue products, and natural bioactive compounds, and thus are addressing current scientific needs in biomanufacturing. The effectiveness of these professional development activities and the achievements of the project objectives are being measured and assessed through a variety of quantitative and qualitative data collection and evaluation surveys. 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

The use of environmental DNA (eDNA, or genetic material shed by organisms) to measure biodiversity is a revolutionary approach that transforms the ability of biologists to observe biodiversity on Earth. In freshwater environments, eDNA in just a liter of water can indicate what fish, insects, and bacteria are present. Despite the rapid advances and adoption of this approach, very little is known about how long eDNA lasts and how fast it disintegrates in nature. Understanding the fate of eDNA in streams and rivers presents a major challenge for interpreting an eDNA “hit”. This NSF award, known as the "DISTANCE" project, will address this knowledge gap by studying the environmental factors that promote or inhibit eDNA movement and degradation in U.S. streams, especially those that are part of the National Ecological Observatory Network (NEON). Infrastructure of the NSF-funded Emerge training program, which broadens undergraduate and graduate student participation in freshwater science, will be expanded as part of the DISTANCE project. Opportunities for student and postdoctoral training will be integrated into the research studies. The term “eDNA spiraling” has been used to describe the fate of eDNA as it flows downstream, where it can be degraded by microbes, deposited in streambed sediments, resuspended from the streambed, and transported further downstream. Hypotheses will be tested that relate water chemistry, microbial communities, and hydrogeomorphology to the three major processes driving eDNA fate: degradation, deposition, and transport. NEON infrastructure will be leveraged by conducting eDNA spiraling experiments at NEON stream sites. Replicated eDNA spiraling experiments will be conducted in two NEON streams and one Critical Zone Observatory site to determine how the type of eDNA (i.e., originating species) and eDNA particle size distribution (determined through sequential filtering) influence eDNA spiraling metrics. Fish and macroinvertebrate biodiversity assessments will be paired at NEON sites with eDNA metabarcoding to investigate whether eDNA spiraling metrics can predict the congruence of community data generated by eDNA metabarcoding compared to traditional methods. DISTANCE has three broader impacts. First, infrastructure of the NSF-funded Emerge program, which broadens participation in freshwater science, will be expanded. Emerge trains undergraduate, graduate, and early career scientists from underrepresented groups in data analysis and visualization (using R software) and in collaborative science. Training in data analysis and visualization for Emerge alumni will be expanded by offering in-person workshops on “Introduction to bioinformatics of eDNA and DNA metabarcoding data.” Workshops will follow The Carpentries pedagogy and be made open access for other Data Carpentries instructors to teach. Second, we will extend NEON infrastructure by generating new, open-access eDNA datasets for NEON sites. Third, this work will provide training experiences for undergraduate students, graduate students, and one postdoc funded by the project, giving them opportunities to practice teaching and mentorship themselves, as implemented in a hierarchical mentoring plan. 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

Earth’s core-mantle boundary (CMB), where the solid silicate mantle meets the molten iron-rich outer core, is associated with a variety of anomalous structures, including ultra-low velocity zones (ULVZs). Typically, ULVZs are associated with reduced seismic wave velocities and sometimes increased density, but the wide range of ULVZ characteristics reported by previous studies and limited seismic coverage of the lowermost mantle have led to many questions regarding ULVZ origins. Using data recorded by stations in Antarctica, the study will examine a variety of core-reflected seismic waves that sample the CMB beneath the southern hemisphere. This region is a unique portion of the lowermost mantle that is located away from large-scale mantle upwellings and downwellings. The researchers will also perform laboratory experiments and develop numerical models of mantle flow to evaluate what ULVZ characteristics would be expected from different potential sources and how those characteristics may vary both in time and space. By combining results from these complementary investigations, they will determine consistent models of ULVZ structure, which will be used to determine the origins of these deep Earth anomalies and the role they play in the evolution of our planet. Both participating universities are Minority-Serving Institutions, and through collaborations with the American Geophysical Union and the EarthScope Consortium, the project will provide multi-mentored research opportunities for students underrepresented in the geoscience. By working with scientists from different fields, who are collaborating to solve geologic problems, the students will gain valuable training that will help prepare them for their future careers. Ultra-low velocity zones (ULVZs) are anomalous structures along the Earth’s core-mantle boundary (CMB) that are characterized by significantly reduced seismic velocities and, in some cases, increases in density. Given limited geographic sampling of the lowermost mantle as well as modeling trade-offs between different ULVZ properties, many questions persist regarding ULVZ origins, their distribution, and the role they play in the evolution of our planet. Using seismic data recorded by stations in Antarctica, the study will provide the first multi-phase, frequency-dependent assessment of ULVZ characteristics, with a focus on the lowermost mantle beneath the southern hemisphere. This portion of the CMB is unique because it is located away from current subduction systems and from the Large Low Velocity Provinces beneath Africa and the Pacific. Mineral physics analyses and geodynamic simulations will also be performed to evaluate what lowermost mantle properties would result from different potential ULVZ sources and how those properties would vary in both time and space. The complementary approaches will be used to create new, internally consistent maps of ULVZ structure beneath the southern hemisphere, thereby allowing the researchers to determine which lowermost mantle processes critically contribute to ULVZ origins. Additionally, through collaborations with the American Geophysical Union and the EarthScope Consortium, they will provide education and research opportunities for students underrepresented in the geosciences. By working with scientists in different Geology disciplines, who are collaborating to solve Earth structure problems, the students will gain valuable training that will help prepare them for their future careers. This project is jointly funded by Cooperative Studies of the Earth’s Deep Interior (CSEDI), the Established Program to Stimulate Competitive Research (EPSCoR), and Office of Polar Programs. 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 · 2024-08

With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, and co-funding from the Advanced Manufacturing Program in the Division of Civil, Mechanical, and Manufacturing Innovation, plus the Established Program to Stimulate Competitive Research, the research groups of Shane Street and Marco Bonizzoni at the University of Alabama, Tuscaloosa, are developing a new way to address a key analytical challenge. Namely, this collaborative team is focused on a new approach to the detection of “forever chemicals,” such as per- and polyfluoroalkyl substances (PFAS). Researchers will first identify conditions under which the targeted PFAS molecules demonstrably influence the growth of metal nanoparticles in water. Measured physical and chemical properties of these particles will then be fed to sophisticated machine learning methods to derive a unique signature associated with each contaminant. The technique is designed to improve environmental monitoring technologies, and, if successful, to potential contribute to fundamental understanding of how these nanoparticles behave. The work will provide interdisciplinary researach opportunities for students from groups underrepresented in STEM (science, technology, engineering and mathematics). Under this award, the U. Alabama researchers will focus on creating pattern-based chemosensors from metal nanoparticles to qualitatively detect specific anionic contaminants in water. The project will combine chemical synthesis, electron microscopy, and electrochemical measurements with machine-learning data analysis methods. It builds on existing expertise in synthesizing metal nanoparticles encapsulated in cationic hyperbranched polymers (Street) and simple yet powerful machine-learning algorithms to achieve chemical selectivity (Bonizzoni). Poly(ethylene)imine (PEI), a commercially available water-soluble cationic polyelectrolyte, supports the growth of encapsulated metal nanoparticles during chemical reduction of the polymer-coordinated metal ion precursors. The cationic polymer also attracts anionic contaminants to the immediate environment of the growing nanoparticles. Particle morphology is therefore expected to be influenced by the presence of target contaminants. The electrochemical signals associated with nanoparticle oxidation could then provide a unique signature for each PFAS contaminant. This information could be used to train a machine-learning classification algorithm to identify anionic contaminants in aqueous solution. 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 · 2024-07

The broader impact of this Partnerships for Innovation - Research Partnerships (PFI-RP) project is the development of a technology that will improve building energy systems and reduce carbon dioxide (CO2) emissions stemming from building energy use. This project will also lower the cost and implementation barriers for widespread adoption of thermal energy storage (TES) technologies. The project focuses on developing a technology called CenoPCM, a new low-cost, fire-resistant phase change material (PCM) microcapsule. This material can seamlessly integrate with existing building energy systems like heating, ventilation and air conditioning (HVAC) and heat pumps for efficient thermal energy storage. The unique properties of CenoPCM will overcome the limitations of current encapsulated PCM technologies, such as high costs, PCM leakage, weak structural integrity, and potential fire hazards. Beyond its technical innovation, the project also places a strong emphasis on cultivating a diverse group of students and providing them with valuable knowledge and skills necessary for entrepreneurship. Participants will have the opportunity to engage in business plan competitions, fostering entrepreneurial thinking and preparation for start-up endeavors. Through this multifaceted approach, the project aims to make a transformative impact on both the building energy sector and the professional development of future innovators and entrepreneurs. This project advances practical applications of microencapsulated PCM in building thermal energy storage to increase energy savings by developing a novel PCM microcapsule, CenoPCM. This novel technology overcomes several weaknesses of the existing products for building applications: high cost, flammability, and PCM leakage. To this end, two novel technologies will be developed to substantially reduce the cost of the PCM microcapsule: a low-cost PCM and a novel microencapsulation method. A method will be developed to upcycle soapstock, an underutilized byproduct of the green diesel industry, into high quality PCM. This PCM will be encapsulated with cenospheres through an “etching-loading-sealing” process. The resulting product, CenoPCM microcapsules, can be used in high volume applications because it is safe and economically feasible. Thermal energy storage units can be made with CenoPCM, which can be integrated with HVAC to achieve higher energy efficiencies. A database of energy saving potential of CenoPCM used in different building types situated in various climate zones will also be built through a scoping study. This project is jointly funded by Partnerships for Innovation Program (PFI) and the Established Program to Stimulate Competitive Research (EPSCoR). 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 · 2024-07

Seawater desalination is the process of removing salts and dissolved solids from seawater. Energy-efficient seawater desalination offers many societal benefits such as accessible fresh water for drinking and agricultural irrigation and mitigating the environmental and human health impacts associated with regional water scarcity. Polyamide reverse osmosis (PARO) membranes are the workhorse technology of the seawater desalination industry. PARO membranes are fabricated using a chemical reaction called interfacial polymerization (IP) that occurs at the interface between a two-phase liquid system (e.g., oil and water). However, the IP technique lacks the control and precision needed to produce highly selective PARO membranes that can remove small organic contaminants from water. Surfactant molecules can be used within the IP process to improve PARO membrane selectivity. However, it is unclear how the surfactants change the molecular-level mechanisms of the IP process and which surfactants work best. A combined computational-experimental approach will be used to understand the effect of the surfactant molecular structure on the IP reaction and resultant membrane performance properties. This knowledge can be applied to produce PARO membranes with enhanced performance abilities. Graduate and undergraduate students will collaboratively execute research plans and participate in new courses related to water treatment and membranes. This project aims to enhance PARO membrane selectivity by investigating the structure-property relationships of monomeric and gemini surfactants and their effects on the IP reaction to create fully aromatic PARO membranes. Gemini surfactants are composed of at least two hydrophilic/functional head groups and two hydrophobic tails linked by a spacer at or near the head group. The investigators hypothesize that by understanding surfactant behavior during the surfactant-assisted IP reaction, it is possible to achieve a homogenous polyamide layer with sharp selectivity without sacrificing water permeance, particularly for challenging separations. This hypothesis will be tested through experiments informed by molecular dynamics simulations and machine learning methods. This project seeks to advance knowledge on the effects of monomer and gemini surfactant properties on m-phenylenediamine diffusion, the minimum area per surfactant, PARO membrane selectivity, and polyamide layer free volume hole and pore size distribution, all of which are needed for the fabrication of selective membranes. 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 · 2024-07

With the rapid adoption of electric vehicles (EVs) on the road, there will be numerous new job opportunities for EV maintenance and repairs for the next several decades. However, there is a significant shortage of adequately trained automotive technicians in the United States who are well-prepared to maintain and repair EVs. The existing automotive technicians have limited career development opportunities due to the fact that they have full-time jobs and limited time and resources to acquire the knowledge and skills needed for maintaining and repairing EVs. In addition, EV maintenance and repair require professional knowledge from multiple domains, which makes it challenging for existing training methods to create immersive and effective learning experiences for automotive technicians. The broader impacts of this project include the development of a globally competitive EV workforce, broadening the full participation of minorities and underrepresented populations in the EV industry, promoting future EV adoption to achieve global sustainable goals, and enhancing the future designs of EVs through the partnerships between academia, industry, local communities, and public agencies. In this project, an interdisciplinary team of researchers will work with multiple industry and educational partners to explore and test the practical foundations of an experiential learning approach for helping existing automotive technicians upskill their knowledge and skills for future EV technologies. This project will: (1) Understand existing EV training workflow and identify automotive technicians’ training needs through co-design and survey; (2) Develop a multi-stage experiential learning pipeline for existing automotive technicians; (3) Propose an effective and scalable experiential learning curriculum for automotive technicians to identify and solve real-world EV problems via online learning, hands-on learning, factory visits, and co-op/internship. This project aligns with the NSF ExLENT Program as it seeks to support experiential learning opportunities which range from fundamental theory to hands-on applications of EV diagnosis, maintenance, and repair. These opportunities exist for individuals from diverse professional and educational backgrounds, and seek to increase their interest in, and their access to, career pathways in emerging EV technology fields. 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 · 2024-07

This project concerns two areas within the field of mathematical analysis, namely harmonic analysis and partial differential equations. Both have proved to be very effective in understanding a variety of physical phenomena and have wide applications in engineering and the natural sciences. Partial differential equations are a natural way to model dynamic processes (that is, processes that evolve or change in some way). Harmonic analysis provides both a firm theoretical foundation on which to construct these models and effective tools for analyzing their behavior. One of the main goals of this research is to expand our knowledge of harmonic analysis and its applications to the study of partial differential equations. Significant parts of this project include education and mentoring of graduate students, particularly women and under-represented minorities, and the development of new international research collaborations. The principal investigator (PI) is working on two projects in harmonic analysis and partial differential equations. In the first, the PI is studying matrix weighted estimates for singular and fractional integrals. He is proving generalizations of the Rubio de Francia extrapolation theorem in this setting and developing a theory of matrix weighted Hardy spaces and matrix weighted variable Lebesgue spaces. These results generalize the extensive literature on scalar weighted inequalities and highlight the differences between scalar and matrix weights. New techniques involving convex-set valued functions are used to overcome various technical obstacles that arise in the passage from scalar to matrix weights. In the second project, the PI is studying the existence, uniqueness, and regularity properties of solutions of second order, degenerate elliptic equations with lower order terms. The goal is to construct a theory on as general an equation as possible with the fewest assumptions on the coefficients and the region. These assumptions are expressed in terms of the existence of matrix weighted Sobolev and Poincare ́ inequalities. This approach unites and extends a number of results that are already in the literature. The PI is also studying the existence of such Sobolev and Poincare ́ inequalities by applying the theory of matrix weighted norm inequalities. 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.