Auburn University

NSF Awards · FY 2024 · 2024-10

Static Random Access Memory (SRAM) used in computing systems is subject to data imprinting, where information stored in the memory persists even beyond the lifetime of system use. Data imprinting effects on commercial SRAM pose a significant security risk for modern computing systems. These effects can cause the persistence of sensitive information in memory beyond its intended use. For instance, when electronic systems are discarded, there is a noteworthy chance that the SRAM memory remains operational, creating a risk of leaking previously stored sensitive information and leading to unauthorized access and compromise. This underscores the critical necessity for implementing robust sanitization measures to securely dispose of electronic systems and mitigate the potential risks associated with the persistence of sensitive information in SRAM memory. This research project investigates the potential of data retrieval from used SRAM chips that have been discarded without awareness of the threat of sensitive information recovery. The team has demonstrated that the information imprinted on these chips is long lasting, underscoring the need for thorough data sanitization to prevent unauthorized access. Additionally, the project develops a novel data sanitization technique for SRAM memories that will benefit consumers, industry, and government alike by ensuring that deleted data is not recoverable at any time during the product’s life cycle. A direct outcome of this project is training two graduate students in the important area of hardware-oriented security and radiation effects on microelectronics. Recent studies have demonstrated that data imprinting effects influence the power-up state of an uninitialized SRAM array, potentially enabling adversaries to recover sensitive information. The project focuses on an in-depth analysis of the security threats posed by SRAM data imprinting effects. The team focuses on the real-world scenarios where attackers could exploit these vulnerabilities to gain unauthorized access, manipulate sensitive data, or launch other malicious activities. Additionally, the project explores new, cost-effective data sanitization techniques tailored for SRAM memories. Overall, the project characterizes the effectiveness of data recovery from SRAM memory under various usage conditions. The team evaluates the efficiency of data recovery techniques on different types of SRAM memories across diverse technology nodes and develops cost-effective techniques for data sanitization utilizing high-energy irradiation. Experimental assessment is performed to examine the effectiveness and resilience of these techniques against resourceful malicious data recovery efforts across a range of operating conditions. 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

Permafrost, the permanently frozen ground found in cold regions, is rapidly thawing due to climate change, posing significant risks to buildings, roads, and ecosystems in Arctic and sub-Arctic regions. Despite its importance, scientists still struggle to predict how permafrost will respond to warming temperatures over time. This research project aims to bridge that knowledge gap by examining permafrost at multiple scales - from tiny ice crystals to vast frozen landscapes. Using advanced imaging techniques, innovative laboratory experiments, and powerful computer simulations, the team will uncover how the internal structure of frozen soil influences its behavior as it thaws. The project will also engage students and the public through educational programs about permafrost in both southern states and alpine regions, helping to raise awareness about this critical but often overlooked component of our changing climate. The specific goal of the research is to enhance our understanding of the temporal interactions between climatic temperatures and the physical processes that influence permafrost dynamics and stability. This project seeks to answer three fundamental questions: (1) How do microstructural features like grain size, ice content, and void structure affect permafrost's macroscale mechanical properties? (2) How do different environmental conditions (temperature, degree of saturation) and loading parameters (mechanical load, strain rate) affect the thermo-mechanical behavior of permafrost and frozen soil? (3) How do long-term climate changes impact permafrost stability and deformation? To address these questions, the research will employ a multiscale approach combining X-ray computed tomography (CT) scanning, geotechnical centrifuge testing, and integrated discrete element-finite element (DEM-FEM) modeling. CT scanning will provide detailed imaging and analysis of frozen soil microstructure. Geotechnical centrifuge testing at the Natural Hazard Engineering Research Infrastructure (NHERI) UC Davis Center for Geotechnical Modeling will simulate long-term climate change impacts on permafrost at an accelerated timescale. The coupled Discrete Element Modeling (DEM) and Finite Element Modeling (FEM) will bridge microscale and macroscale behaviors, integrating data from both imaging and physical experiments. This comprehensive approach will yield high-quality data for developing and validating multiscale numerical models to predict permafrost thaw trajectories and impacts on infrastructure in cold regions. The project will advance the knowledge base in frozen soil mechanics, physical modeling, and multiscale computational methods while training the next generation of researchers in cold region engineering. 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

Variation in diversity of organisms across geographical regions has captured the attention of biologists for decades. Such patterns of diversity are driven by a combination of biogeography and ecological differences among species. The fish family Leuciscidae (minnows) presents an excellent opportunity to study the interplay of biogeography and ecology. Following migration to North America, these minnows have diversified extensively. This minnow diversity is often overlooked, even though species of Leuciscidae occur in freshwater streams across the continent. This research will test the origins and drivers of biodiversity in Leuciscidae. It will elucidate present-day biodiversity of these minnows, and will improve our general understanding of patterns of diversity across North America and globally. The project will train undergraduate and graduate students, and postdoctoral researchers. The research team will develop a public website on minnow diversity, will collaborate with grade school teachers to develop and implement lesson plans on biodiversity and museums, and will support outreach through traveling science museum programs. An improved understanding of diversification of the family Leuciscidae requires a robust understanding of the evolutionary relationships, information on ecological differences among species, and data on species ranges. This project will reconstruct the phylogeny of Leuciscidae using new genome sequencing data, with broad sampling across the family. Researchers will use the phylogeny to determine timing and number of migrations to North America, and to investigate the biogeography of species and how species distributions have changed over time. They will compile ecological and morphological data, reconstruct how traits have evolved, and use comparative approaches to study adaptation and its role in diversification. This integrative approach using multiple lines of data will yield valuable insights into evolution of this important group of fishes. 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

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 a consortium of six academic institutions in Alabama and Michigan: Tuskegee University, Auburn University, Auburn University Montgomery, Oakland University, Southern Union State Community College, and Troy University. This institutional consortium represents a HBCU, private and public 4-year institutions, a 2-year community college, two predominantly undergraduate institutions, and three doctoral-granting institutions. Over its 5-year duration, this Track 3 Collaborative project will fund scholarships to 72 unique full-time students who are pursuing associate’s, bachelor’s, and master’s degrees associated with Sciences (Physics, Chemistry, Mathematical, Computer) and Engineering (Materials, Mechanical, Software, Electrical, Computer). First-year students will receive up to four years of scholarship support, while transfer and graduate students will receive up to two years of scholarship support. The project aims to increase student persistence in STEM and promote their workforce readiness by linking scholarships with supporting activities, including mentoring, research experiences, graduate school preparation, participation in conferences, professional advising, career planning, and hands-on experience with cutting-edge technologies. Project activities will synergize to promote students’ sense of belonging in the college environment and help them identify as future STEM professionals in high-demand fields. The partnership institutions serve a large number of students from underrepresented racial, ethnic, and economic minorities; thus, this project has the potential to broaden participation in STEM areas of critical need, and advance understanding of how the proposed activities foster academic and professional success in this student population. The overall goal of this project is to increase STEM degree completion of low-income, high-achieving undergraduates with demonstrated financial need. The specific aims are to increase students’ academic skills for college success and professional skills for STEM careers in critical need areas and investigate the impact of its activities on retention and graduation of low-income students. This project will analyze the institutional and personal factors that foster sense of belonging in low-, mid-, and high-income students, and fill a gap in the knowledge base by investigating sense of belonging in connection to a salient professional identity. The project will analyze the support needs of low-, mid-, and high-income students, the extent to which academic advisors’ and professors’ views of student needs coincide with students’ perceived needs, and the role of personal relationships on preventing isolation and strengthening professional identity. A rigorous mixed-methods evaluation will determine the extent to which the project is achieving its goals by assessing student participation in project activities, perceived gains, persistence in the major, and professional outcomes. Results of this project will be disseminated through a website, digital newsletters, data briefs, explainer videos, presentations, and journal publications. This project is funded by NSF’s Scholarships in Science, Technology, Engineering, and Mathematics program, which seeks to increase the number of low-income academically talented 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-to-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 2024 · 2024-10

Current physics teaching focuses on content and practicing well-defined procedures, a focus which may leave students ill-prepared to solve problems for which there is no known solution. Similarly, physics instructors, though expert scientists themselves, aren’t trained in how to support students in learning these real-world problem-solving processes. This project will serve the national interest by addressing a critical gap in our understanding of how to effectively teach physics students how to solve the real-world problems. In the process of conducting this project, the principal investigator and a graduate student researcher will also build capacity in qualitative physics education research, particularly longitudinal case-study methodologies. The project will simultaneously investigate how students’ problem-solving skills develop across undergraduate and graduate physics education and how instructors’ knowledge of how to teach problem-solving develops during their careers. The work is expected to provide a better understanding of how to teach problem-solving more effectively, thus preparing the next generation of physicists for solving the grand challenges that will face the world in the future. This project, housed at Auburn University, will use longitudinal, case-based qualitative methods to understand how students’ problem-solving-skills develop over time. It will also examine how students’ and instructors’ epistemologies regarding problem-solving develop and interact with the construction of content knowledge. This project is rooted in empirical theories of scientific problem-solving as decision-making with limited information, as well as activity theory, which emphasizes the context-dependence of knowledge and knowledge construction. This project will utilize videos of students solving real-world problems both in the classroom and in the laboratory setting, as well as simulated recall interviews with the students and instructors. The project team will track a cohort of students and instructors over a period of three years to understand the longitudinal development of the students’ knowledge and epistemologies, and the instructors’ pedagogical knowledge and epistemologies. This proposal will contribute to the understanding of the novice-expert transition in problem-solving, which is an open and fundamental problem in physics education. This will lay the foundation for theory-building through more extensive experiments and the development of educational interventions in physics. Future work will extend this framework across disciplinary boundaries and investigate additional contextual factors that affect the development of problem-solving expertise. The results of this work are also expected aid the development of faculty training programs in physics. The results of this study will be disseminated through scholarly publication and conference presentations. The project is supported by NSF’s EDU Core Research Building Capacity in STEM Education Research (ECR: BCSER) program, which is designed to build investigators’ capacity to carry out high-quality STEM education 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 2024 · 2024-10

This project aims to serve the national interest by improving manufacturing education and learning for diverse learners. Leveraging a 4,000 square-foot manufacturing facility at Auburn University, this project will implement evidence-based teaching practices to develop accessible and experiential video-based learning modules that can benefit remote and in-person learners. This state-of-the-art facility simulates high-volume automotive manufacturing environments, such as those of Toyota and Honda, providing students with significant experiential learning in Lean Manufacturing. Lean Manufacturing is the third generation of industrial manufacturing, following the Job Shop and Henry Ford's Mass Production System, and is the primary focus of this project. As the reshoring of American manufacturing increases, experience-based knowledge in Lean Manufacturing is crucial for the nation's industrial competitiveness. Practical learning experiences gained by students in Lean Manufacturing equip them to support the growing manufacturing sector in the U.S. and improve student mindsets and persistence in STEM. This project will not only lead to the development of new instructional materials but also deliver knowledge pertinent to students' learning during these practical and experiential learning experiences. The primary goal of this project is to develop comprehensive experiential learning modules in Lean Manufacturing and to leverage state-of-the-art manufacturing facilities to enhance learning outcomes beyond traditional classroom instruction. Some of the targeted Lean Manufacturing learning topics include (1) 5S, a systematic approach to creating an organized manufacturing environment with robust visual management, and (2) Value Stream Mapping, a methodology that identifies waste within a manufacturing system and that is often overlooked due to its complexity. By developing a web-based platform that offers online students and instructors interactive video access to state-of-the-art manufacturing facilities, the project will allow a more diverse set of students and educators to engage with a real production system and collaborate with on-campus students. This initiative aims to be scalable, extending its scope to a broad academic and industrial learner network. A team composed of manufacturing engineering educators and an educational psychologist will enable knowledge generation pertinent to gains in learning outcomes (e.g., critical thinking skills, attitudes towards engineering practice, cognitive gains), with comparisons of online and on-campus students. The findings will be disseminated through scientific and educational professional conferences and peer-reviewed academic publications. 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 2024 · 2024-09

This award funds an effort to create a database from historical records on consumer expenditures linked to publicly available records from the Census Bureau. The data will be widely available to researchers and the public at no cost. The research team will use these data themselves for several studies that will examine the evolution of living standards during the post WWII period. This is a period where the U.S. experienced growth in household incomes and a decrease in income inequality, but we do not know if these changes in the income distribution across different groups of Americans resulted in more equality in consumption and living standards. Modern micro data on consumer expenditures has proven to be enormously valuable over a wide variety of fields in economics. This new data set will allow researchers to extend the time period under study. The project will also contribute to research on how to best construct price indices, since the results will help us understand how consumption patterns have diverged across demographic groups over time. The data will be valuable to economists, social scientists, statisticians, and policymakers interested in the measurement of living standards. 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

In this project, funded by the Chemical Structure, Dynamics & Mechanisms B Program of the Chemistry Division, Professor Christian R. Goldsmith of the Department of Chemistry at Auburn University is developing new coordination complexes that functionally mimic the antioxidant enzyme catalase. Catalases have a prominent role in the detoxification of hydrogen peroxide within the body. Functional small molecule mimics of catalase enzymes have the potential to supplement the body’s defenses against oxidative stress, which is believed to be a component of many neurological, cardiovascular, and inflammatory disorders. The proposed catalase mimics are manganese, iron, and zinc complexes with redox-active organic ligands; correspondingly, the research lies at the interface of biochemistry, organic chemistry, and inorganic chemistry. The interdisciplinary nature of the work makes it well suited for the education of scientists at all levels. The outreach portion of the project will encourage and enable more undergraduate students in the East Alabama/West Georgia area to participate in scientific research through interactions with a recently established local chemistry symposium and a pre-existing Research Experiences for Undergraduates program. Manganese, iron, and zinc complexes with cyclams with appended quinol groups have proven to be highly water-stable and highly active catalysts for the dismutation of hydrogen peroxide to water and oxygen. More efficient catalase activity is hypothesized to result when the quinol portion of the organic ligand is in the second-sphere, rather than the inner-sphere, of the metal ion. The proposed compounds will test this hypothesis by featuring synthetic modifications that should weaken the binding affinities of the quinols to the metal ions while keeping them close enough to react with metal-bound molecules of hydrogen peroxide. Specific modifications that will be investigated include A) lengthening the linker between the quinol and the macrocycle, B) installing steric bulk near the metal-binding oxygen atom on the quinol, C) replacing the cyclam with a macrocycle that will tilt the quinols farther away from the metal, and D) installing electron-donating substituents on the quinol. Successful catalase mimics will be mechanistic probed through spectroscopic experiments and calculations to determine the relative contribution of metal- and ligand-based redox couples to the reactivity. 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

Nearly two-thirds of the world faces water scarcity due to growing populations and pollution. Membrane-based separations, such as reverse osmosis (RO), use up to 90% less energy than thermal methods like distillation and evaporation. This makes them an efficient way to increase freshwater supplies through desalination while minimizing environmental impact. Although current commercial RO polyamide membranes effectively remove salt from water, they are prone to biofouling, where bacteria form biofilms that reduce water production rates. Chlorine-based treatments can remove the biofilms, but the membrane will eventually disintegrate because the chlorinated chemicals break down the membrane's molecular structure. This research aims to better understand why RO polyamide membranes remove salt so effectively and use this knowledge to develop a new type of RO membrane that performs as well as current commercial membranes and resists chlorine damage. Additionally, this research's connection to real-world problems will be leveraged to inspire young students to pursue engineering careers and tackle challenges in their communities and worldwide. This research aims to investigate the hypothesis that weak intermolecular interactions play key roles in the performance of polyamide RO membranes. The effects of crosslinking, amide, benzyl, and carboxyl density will be explored by producing a highly tailorable, novel polyamide membrane comprised of a dense layer of brush polymers. This platform will incorporate proportions and densities of functional groups that mimic polyamide structures and properties through well-controlled, bottom-up synthesis using surface-initiated atom-transfer radical polymerization (SI-ATRP). Membrane performance will be assessed by measuring salt and water permeability and molecular weight cutoff while targeting selectivity comparable with commercial RO membranes. The control over membrane thickness and grafting density will also be exploited to hone membrane transport models. The findings will be used to develop an effective RO membrane that avoids the aromatic polyamide functional group, improving its resistance to chlorine. With the ability of SI-ATRP to sequentially produce block copolymers, other dense, uniformly distributed top layers will be considered for performance enhancement, including antifouling polyelectrolytes. The themes of this work will be incorporated into undergraduate chemical engineering courses and activities for science camps and workshops for high schoolers considering science, technology, and engineering fields. Further, the outcomes of this work have implications for designing defect-free biomimetic membranes for solute-solute separations, such as those used to recover valuable species like lithium for sustainable energy solutions. 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 research project will computationally characterize the production and generation of the cations CO+, N2+, and CO2+ in cometary atmospheres as a proxy for the parent neutral molecules O2, N2, and CO2 which are difficult or impossible to observe from Earth. The work will thus yield new volatile diagnostics for ground-based astronomy, and the results of the project will allow astronomers to understand the role of these ions in cometary atmospheres. This project will train graduate students and early career scientists in methods of advanced computational spectroscopy and chemical modeling important in astrophysics. The investigators will characterize the production and emission mechanisms of the cations using three complementary methods. First, they will compute the electronic structure and spectroscopic constants of the cations. Second, they will use these constants and existing literature to develop a fluorescence model to predict the emission spectra of the cations in the infrared, visible, and ultraviolet wavelength regions. Finally, they will use chemical reaction networks to quantify the location and strength of the emission in cometary atmospheres. The project will also promote K-12 STEM engagement by introducing local scout groups to astronomical topics including comets, planets, and asteroids through stargazing events. 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

An award is made to Kansas State University (in collaboration with USDA Agricultural Research Service and Harvey Mudd College) to design, build, and test a digital AC-DC electropenetrograph to study the real-time feeding behaviors of blood-feeding arthropods, using ticks as the model system. Ticks and other blood-feeding arthropods transmit a wide array of medically- and veterinary-important pathogens, many of these increasingly exacerbated by climate change. An important obstacle to basic research on tick feeding behavior is the inability to capture observations and statistically analyze details of tick feeding behavior because it is masked below the surface of the host’s skin. The challenge is further compounded by the incredibly long durations over which ticks feed (~7 to 10 days for adult ticks). To address this methodological deficit, this project will develop a user- and application-friendly digital AC-DC electropenetrograph which will enable researchers to readily investigate these hidden behaviors in unprecedented detail. This project brings together a transdisciplinary team of scientists that will collectively support the training of 12 to 20 undergraduates and a postdoctoral researcher, giving them opportunities to explore this burgeoning area of research interest from diverse perspectives of engineering, computer science, and biology. Project undergraduates and the postdoctoral researcher will work in teams mentored and guided by project scientists. Trainees, recruited as broadly as possible, will interact with scientists from academia, government, and industry, affording them opportunities to investigate future career paths. Trainees will be involved in both intellectual and physical aspects of this research and will participate in the iterative evaluation of their designs tested using a combination of arthropod species: ticks (project model blood-feeding arthropod) and aphids (gold standard insect for electropenetrography research). Project scientists and trainees will also have opportunity to share project goals with broader audiences through development and delivery of related content and experiential opportunities through community and science communication engagement platforms and events (e.g. Kansas Science Fair). Electropenetrography (EPG) is a transformational technology that has been used for nearly 65 years to study the masked feeding behaviors of piercing-sucking, plant-feeding insects. However, such a means of studying the basic behaviors of blood-feeding arthropods in real time, including ticks that feed for extreme durations (days to weeks), has eluded biologists for decades. Despite initial success with tick and mosquito feeding recordings using the existing analog AC-DC electropenetrograph, this instrumentation presents notable physical limitations for working with blood-feeding arthropods on vertebrate hosts. Developing a more user- and application-friendly digital AC-DC electropenetrograph will solve this challenge and enable ground-breaking investigations to detect, characterize, and quantify the progressive and highly coordinated feeding behaviors performed by ticks and other blood-feeding arthropods. Hypothesis-driven studies can then be performed to study basic feeding biology and investigate how host factors, vector characteristics, pathogens, and chemical interventions specifically modify hidden arthropod blood-feeding behaviors. In this project, the digital AC-DC electropenetrograph will be evaluated over the course of three scientific objectives: (i) Design and build a prototype digital AC-DC electropenetrograph and associated software to record tick feeding on an unsedated live host; (ii) Iteratively evaluate versions of the prototype instrument with live ticks and live host, and modify prototype as needed; and, (iii) Demonstrate the usability of the digital AC-DC electropenetrograph to record and statistically compare tick feeding behaviors upon applications of a behavior-interdicting compound. Successful completion of this research will deliver a user-friendly, commercializable instrument and associated software that will: 1) accelerate expansion of electropenetrography from plant-feeding insects into blood-feeding arthropods, 2) ensure the continued availability of this crucial infrastructure through an evolved digital instrument design, and 3) allow faster high-throughput uses through development-associated machine learning software. Project outcomes will include development of a user-friendly, digital AC-DC electropenetrograph and supporting ‘arthropod species flexible’ software. This novel research instrument will spur new opportunity for a broad community of researchers interested in improving the resiliency of animal and plant agriculture from blood-feeding and plant feeding arthropods. 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

Monolayered 2D materials have a thickness of less than 1 nanometer. When they are stacked to form homogeneous junctions and heterogeneous junctions with various twist angles, new exotic properties and functionalities will arise. Relevant applications include microelectronics and sensor development. Although computer modeling has uncovered very strong twist angle effect on the interlayer thermal conductance at homo- and heterojunctions, no experimental work has been reported yet. This is due to the extreme experimental challenges in measuring the temperature difference and heat flux across a homo- or heterojunction. The project is designed to overcome these extreme challenges and provide the first-time experimental understanding of twist angle effect on interfacial thermal conductance of homo- and heterojunctions. New Raman techniques with specifically designed energy transport states will be used. The overall project will involve extensive training of graduate and undergraduate students and feature tight integration with education and outreach to K-12 graders. The goal of the project is to investigate how the twist angle affects the interlayer thermal conductance and junction-substrate interfacial thermal conductance of 2D homo- and heterojunctions, investigate the effect of temperature, and provide deep physics understanding about the twist angle effect via atomistic modeling and machine learning. This project represents the first high-accuracy investigation about the twist angle effect on the thermal conductance of homo- and heterojunctions of 2D monolayers. The outcome will significantly advance current knowledge that is solely developed by modeling and theoretical analysis. It will uncover how the twist angle influences the interfacial thermal conductance, identify the angles that give the highest and lowest thermal conductance, and unravel how temperature variation will change this effect. The knowledge to be developed in this project will substantially advance the scientific understanding and provide the critical knowledge for material and device design in 2D material-related microelectronics and sensors. The broad impact activities are designed to significantly expand undergraduates' view of modern science, stimulate their interests in research, and expose K-12 graders to nanoscience and technology, especially in energy transport and control. 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

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 · 2024-08

The climatic and anthropogenic controls of fire in the eastern United States (US) are understudied relative to other areas of the US. Despite recent fire events and suggestions that anthropogenic climate change will drive longer, more intense fire seasons, the understanding of long-term fire-climate relationships in eastern US forests remains limited. The project will inform broader scientific understanding of the future fire risks of the region. Wildfire events and seasons in the eastern US are increasingly affecting people, ecology, and land management, so this project will provide direct societal benefits by generating new science to inform wildfire-related climate adaptation efforts. The project will work with US Geological Survey Climate Adaptation Science Centers to communicate findings to regional scientists, stakeholders and policymakers. The project also includes education and training of graduate and undergraduate students, as well as educational outreach with middle and high school students. The goal of this project is to better resolve regional fire-climate relationships through the development and analysis of Holocene (last ~12,000 years) paleofire records and to better define controls on current and projected fire potential. By analyzing particulate and molecular by-products of wildfires preserved in sediment records (e.g., lakes, wetlands) spanning the Holocene, the project will compare fire and climate histories prior to the onset of human impacts to landscapes as a means of understanding baseline fire-climate relationships in the region. In addition to collecting new empirical data, the project will also leverage existing paleoclimate datasets to better resolve regional fire-climate relationships and better define controls on future fire potential. Empirical data will be compared to transient paleoclimate model simulations to enable quantitative characterization of region-specific fire activity and relationships to past and future climate changes based on trend analysis, statistical modeling, and application of select fire indices. 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

This project investigates novel chemotaxis phenomena governing the directed movement of mobile agents in response to various types of stimuli. Chemotaxis is an important mechanism which enables biospecies, such as bacteria, cells, and other organisms to migrate, spread or localize within complex media. This mechanism is ubiquitous in nature as it facilitates a wide variety of fundamental processes including transport of immune cells to infected regions, movement of embryonic cells, tumor growth, and migration of biospecies toward food sources. The focus of this project is on the chemotaxis model and dynamics of organisms spatially confined to multiconnected networks such as, for example, fibers of dermal tissues, arteries in the vascular systems, or natural river systems. The principal objective is to provide new analytical insights into long-term dynamics and spreading phenomena of mobile agents on several types of networks. This goal is achieved through mathematical analysis of a system of partial differential equations on metric graphs. In addition, the PI will organize a research seminar at Auburn University and a summer school adjacent to the fourth Joint Alabama-Florida DEDS conference. These activities will provide ample opportunities for students to enter mathematical research in a paced and guided fashion. Furthermore, this project provides unique educational experience for students in Alabama and Florida and facilitates their entry into advanced-degree programs. The study of nonlinear waves and other coherent structures on graphs is a novel, rapidly developing, and intriguing field of research in applied dynamical systems and partial differential equations. This project concerns nonlinear waves arising in population dynamics driven by chemotaxis. The main focus is on the reaction-diffusion Fisher-KPP model and the reaction-advection-diffusion Keller-Segel model posed on metric graphs. Employing operator semigroup methods, a priori estimates for solutions of heat equation on graphs, and comparison principles, the principal investigator studies global well-posedness of relevant partial differential equations on unbounded networks and determines spatial spreading properties of biologically relevant solutions. In addition, the PI investigates, via the Maslov index, stability of traveling wave solutions for the Fisher-KPP equation in the moving environment. Located at the interface of applied dynamical systems and partial differential equations this proposal addresses several models originated in bio-engineering, ecology, and sociology. 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 Faculty Early Career Development (CAREER) award supports research that increases the availability of rehabilitation for people with movement disorders, thereby advancing the national health, promoting the progress of science, and advancing prosperity and welfare. Specifically, this project will increase access to rehabilitation by developing a deep learning-based control framework that reduces the cost of home-based hybrid exoskeletons, which combine functional electrical stimulation with actuated robots. Traditional telerobotic frameworks consist of a leader system remotely generating and sending a desired trajectory to a follower system and the follower generating its own control commands. In this project, the costs of each follower hybrid exoskeleton will be reduced by having the leader computer (located at a medical facility) generate the control commands for the hybrid exoskeletons (located at each individual's home) based on local state information shared by the exoskeletons, which moves the computational demand from each follower to the single leader. However, the communication between the computer and exoskeletons will be delayed due to communication limitations, which could destabilize the control system. Another challenge is that the dynamics of a hybrid exoskeleton are inherently uncertain and nonlinear. This project will solve these challenges by enabling the remote control of hybrid exoskeletons based on deep neural networks (DNNs) despite the existence of communication delays and uncertainty in the robot dynamics. Through education and outreach activities focused on controls and rehabilitation engineering, this project will also increase the interest of K-12 and undergraduate students in science and engineering. This research aims to make fundamental contributions to Lyapunov-based delay-compensating control frameworks that guarantee system performance for uncertain telerehabilitation and telerobotic systems, despite the dynamic models being nonlinear, uncertain, and delayed. DNNs can potentially compensate for system uncertainty by adaptively approximating the uncertain system dynamics. Through the Lyapunov-based stability analysis, adaptive update laws for the DNNs will be developed to improve the DNN learning performance in real-time. Beyond compensating for model uncertainty, the DNN-based control system has an added bonus of personalizing the control system for each individual. Successful completion of this project could transform the rehabilitation industry by significantly increasing the availability and affordability of personalized rehabilitation for millions throughout the nation. Novel DNN-based control frameworks will be developed for uncertain general telerobotic systems with known and unknown input delays, and for uncertain home-based hybrid exoskeletons with unknown input delays. Transformative classes of DNN-based observers and controllers will be developed to enable uncertain general telerobotic systems with known and unknown input and output delays, and uncertain home-based hybrid exoskeletons with unknown input and output delays. This project is jointly funded by the Dynamics, Control and Systems Diagnostics (DCSD) 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 2024 · 2024-07

Topological wave insulators are a specialized material for transporting wave energy in various applications in modern science and engineering. This project will develop computational methods for several classes of inverse and optimal problems arising from the mathematical studies of partial differential equation (PDE) models for topological wave insulators. The goals of this project are to provide efficient computational algorithms that address several theoretical open questions in this area. Successful completion of this project should stimulate the mathematical research for topological insulators and beyond. The developed computational frameworks will also provide physical experimentalists and engineers with the computational tools to improve the performance and functionalities of topological materials. The project will also integrate students into the research team as part of their professional training. The project will address several key scientific challenges arising from the inverse and optimal design of the spectrum of the PDE operators in topological wave insulators. First, based on the spectral analysis of the PDE operators in periodic media, a new optimization framework through the enforcement of parity for the eigenfunctions will be built to solve for wave insulators that attain Dirac points at desired Bloch wave vectors and eigenfrequencies. Numerical algorithms based on the construction of wave propagators in periodic media and the design of the spectral indicator function will be developed to efficiently identify the interface parameters that allow for the existence of edge modes in joint topological wave insulators. Finally, efficient convex semidefinite programming based numerical methods will be developed for solving the optimization problems that arise from maximizing the band gaps of the PDE operators for topological wave insulators in order to enlarge the spectral bandwidth of edge modes. This project is jointly funded by the Computational Mathematics 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

Non-technical Description This research addresses the properties of a new class of ultra-thin quasi-two-dimensional semiconductors with intrinsic magnetic properties. The exotic properties of this new class of semiconductors make them particularly interesting for fundamental science research and practical applications. The investigators will explore the electronic, magnetic, and thermal properties of these unique materials with thicknesses of a few-atomic layers only. The PIs will also investigate the potential of these materials for use in devices with novel functionality that operate at high speed with low-energy dissipation. This research aligns with the Nation’s need for the development and research of novel semiconductor materials and devices under the recent CHIPS and Science Act. The interdisciplinary nature of the project will facilitate the involvement of students in the proposed research and contribute to undergraduate and graduate STEM education. The project team has developed a detailed Broadening Participation Plan that will impact the K-12, undergraduate, and graduate education of minorities underrepresented in STEM fields. Technical Description Transition-metal phospho-trichalcogenides span a wide variety of compounds with different electronic, magnetic, and phonon properties. These materials are one of a few van der Waals layered structures which can have intrinsic antiferromagnetism, even at mono-layer thickness. The band gap of these materials varies from ~1.3 eV to ~3.5 eV based on the type of its transition- metal element. Theory suggests that the application of gate bias and strain can induce phase transitions in these materials, changing their properties. While electrical insulators and conductors with AFM spin order have been studied extensively, little is known experimentally about antiferromagnetic layered semiconductors. This project aims to investigate the electron, phonon, and magnon properties of these unique materials at single- and few-layer structures, and to assess the possibilities of controlling their properties for enabling novel device functionalities. To achieve these goals, various types of these compounds will be synthesized and characterized using cryogenic micro – Brillouin – Raman spectroscopy, and electrical and thermal transport measurements. The results of this interdisciplinary research will add to the core knowledge in several areas of material science and electrical engineering, thereby delivering a transformative impact for applications of antiferromagnetic layered semiconductors. The intellectual merit of this project include knowledge of phonon and magnon band structures, and their modification with the thickness, strain, and electric bias; experimental data for controlling the Néel temperature in two- dimensional antiferromagnetic semiconductor films; mechanisms and methods for tuning the phase transitions in AFM semiconductors under the action of gate and strain; innovative approaches for enabling novel device functionalities via control of the electron, phonon, and magnon states in two-dimensional antiferromagnetic semiconductors. 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.