Texas A&M University

NSF Awards · FY 2025 · 2025-09

With the support of the Chemical Catalysis program in the Division of Chemistry, Professor David Powers of Texas A&M University is studying new metal-free catalyst platforms for fine chemical synthesis. The use of metal-based catalysts in fine-chemical settings, such as pharmaceutical synthesis, is often expensive and imposes laborious purification processes to remove metal contaminants. The project will advance our understanding of the fundamental design elements that enable main group elements, such as iodine, to engage in efficient bond-forming processes. These insights will be used to design metal-free catalysts for an array of chemical transformations important in the preparation of functional organic small molecules. The results of the project will broadly impact the rational design and deployment of metal-free catalysts. Further, as the project investigates chemistry at the border or organic, inorganic, and main group chemistry, the project will provide training and educational opportunities to students at all education levels. With the support of the Chemical Catalysis program in the Division of Chemistry, Professor David Powers of Texas A&M University is studying iodanyl radical catalysis as a platform for metal-free oxidation catalysis that is complementary to the chemistry of diamagnetic hypervalent iodine compounds. This project will define the elementary chemical steps that are available to iodanyl radical intermediates and utilize those mechanistic insights to rationally target new catalysts and catalytic transformations. The project will advance novel catalyst design concepts based on sigma-delocalization and sigma-aromaticity of heavy main-group elements to facilitate catalyst re-oxidation and to control catalyst activity and selectivity. The project will broadly impact the design and application of metal-free catalysts and catalysis with heavy main group compounds. Because the project investigates catalyst concepts at the interface of organic, inorganic, and main group chemistry, valuable educational and outreach opportunities will impact students from all levels of scientific training. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

As research workflows become more data-intensive and complex, there is a need for greater acceleration, and GPUs are a popular choice. Federated GPU-heavy systems are fully subscribed, and this practice is costly in terms of energy and hardware. However, innovation that employs next-generation arithmetic, CXL, and RISC-V technologies can produce greater precision with fewer bits, tackling both energy and storage challenges for AI/ML workflows, while paving the way for quantum computing, which will rely on next-generation math and standards. The efforts in this area will support the nation’s leadership in AI and quantum, and strengthen the cyberinfrastructure ecosystem. This project, in collaboration with STEM-Trek Nonprofit and the Conference on Next-Generation Arithmetic (CoNGA), will host the TANGO workshop ahead of the Supercomputing Conference, SC25, in St. Louis, Missouri November 16-22, 2025. Participants will learn how Compute eXpress Link (CXL), RISC-V, and Next-Gen Math drive the revolution toward more energy-efficient supercomputers. With such tools, it is possible to render artificial intelligence and machine learning (AI/ML) workflows with greater precision and fewer bits. A greater understanding of next-gen math is also essential for those who develop embedded systems and quantum arithmetic circuits. This is the 6th workshop in the series and co-funded by industrial support. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Modern science and engineering increasingly rely on extracting meaningful information from large and noisy datasets, such as those arising in medical imaging, environmental monitoring, telecommunications, and numerous other disciplines. This project develops advanced statistical methods that improve signal recovery and noise reduction through innovative shrinkage and thresholding techniques applied in multiscale domains like wavelets. In addition to classical computational tools, the project explores emerging directions involving quantum computing simulators to prototype quantum-inspired shrinkage methods, aligning with growing national and institutional emphasis on quantum technologies. These approaches simplify complex data by selectively attenuating noise while preserving essential features, leading to more accurate and interpretable results. The project integrates education by mentoring students at multiple levels, incorporating findings into graduate and undergraduate courses, and creating open-source software tools that promote reproducible research and broad access to cutting-edge statistical techniques. This research advances the theory and application of shrinkage estimation in multiscale settings, with a particular emphasis on quantum-inspired methodologies that complement classical Bayesian and frequentist frameworks. It develops adaptive block-shrinkage procedures employing priors that capture dependence among wavelet coefficients and introduces absolutely continuous shrinkage priors that maintain computational tractability without relying on spike-and-slab or point-mass priors. The project also devises novel thresholding strategies informed by refined extreme-value approximations and Bayesian decision rules based on Bayes factors. Computational implementation includes efficient posterior simulation algorithms and exploratory shrinkage techniques using quantum computing simulators. These innovations will contribute to foundational methodology for nonparametric regression, signal processing, and scalable high-dimensional inference. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

In the early Universe, all matter and radiation was concentrated in an extremely hot and dense fireball that expanded and cooled rapidly. During this evolution, several phenomena occurred that fundamentally shaped the world around us. In particular, during the first few microseconds, a plasma of elementary particles called quarks and gluons prevailed before converting into bound states called hadrons, which ultimately made up the atomic nuclei as we know them today. In this transition, at around two trillion degrees Kelvin, the quarks and gluons were permanently confined into hadrons, thereby generating about 98% of the visible mass in the Universe. The theoretical description of the confinement of quarks and gluons and the generation of hadronic mass remains an outstanding challenge in modern elementary-particle and nuclear physics. High-energy collisions of atomic nuclei can recreate the quark-gluon plasma (QGP) for a short moment in the laboratory, before it decays back into hadrons that can be measured in large detectors. In this project, rigorous theoretical analyses are carried out to deduce the properties of the QGP and its hadronization by analyzing the observed particle spectra. The goal of this project is to unravel microscopic mechanisms of the QGP-to-hadron transition by evaluating in-medium correlation functions. First-principle information on these is available from the theory of the strong interaction, Quantum Chromodynamics (QCD), using lattice-discretized computer simulations. However, these results are not readily applicable to experiment. This gap is bridged by utilizing the concept of spectral functions, which characterize the structure of matter. Spectral functions are calculated in both QGP and hadronic matter using quantum many-body theory, which can cope with the large interactions rates in the system. By focusing on spectral functions in the vector channel, a direct connection between lattice-QCD results (for correlation functions) and experimental data (for di-lepton spectra) is established. On the QGP side, novel techniques are developed to calculate quark-antiquark correlators at finite momentum and constrain them by lattice QCD. On the hadronic side, existing calculations of the vector spectral function are improved to incorporate mass degeneracies as predicted by QCD. A smooth matching of these calculations around the transition temperature and subsequent tests against experimental data are carried out. This project provides opportunities for students to carry out cutting-edge research, and involves outreach to high-school 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 · 2025-09

The primary goal of this project is to establish a CyberTraining Network for Geospatial Artificial Intelligence (GeoAI) in Disaster Management. Through the proposed CyberTraining activities, the project will enable disaster management students, researchers, and professionals, to strengthen their capabilities in cyberinfrastructure and GeoAI. By broadening access to GeoAI and cyberinfrastructure, the project will support research workforce development across various disciplines, including disaster science, geosciences, transportation, and engineering. The team will collaborate with academia, industry, non-profit organizations, and government agencies to provide open access to disaster-related data, training materials, and cyberinfrastructure resources. To ensure scalability and sustainability, the project will be supported by core partner organizations and integrated with National Science Foundation funded cyberinfrastructure, disaster data providers, professional societies, and industry stakeholders. Students and educators will be actively engaged through a participant award program, expanding educational and career development opportunities. Furthermore, this project will enable disaster researchers to advance their use of cyberinfrastructure and GeoAI in disaster management, enhance computational skills, and improve data-driven decision-making for increased disaster resilience. The project is designed to significantly improve the well-being of populations affected by natural hazards and disasters. This project will establish a CyberTraining Network for Geospatial Artificial Intelligence in Disaster Management (GeoAIDM), and provide training to disaster research communities (researcher, students, and professional) on Cyberinfrastructure (CI) and GeoAI skills. The project will 1) establish a GeoAIDM research network that connects institutions, government agencies, hazard research centers, industry, and educational organizations to advance training materials for preparing the current and next-generation workforce; 2) develop a GeoAIDM curriculum for summer schools, webinars, and workshops that utilize GeoAI techniques for effective disaster management; 3) integrate training materials into educational programs, 4) introduce GeoAI to train participants in analyzing and interpreting spatial patterns of disasters and their associated impacts. The proposed project will train 2,000 students and educators. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

At the end of their lives, massive stars undergo highly energetic supernova explosions, which enrich the interstellar medium with heavy elements that then go on to become the building blocks for new stars, planets, and even life. Although the basic physical processes that drive supernova explosions are generally understood, a detailed description of the explosion dynamics and the properties of the matter created under the extreme conditions of density and temperature remain elusive. These properties are crucial for a precise understanding of elemental production in supernovae and the chemical evolution of our galaxy. To probe more deeply into the physics of supernova explosions, neutrinos play a pivotal role. Neutrinos are abundantly produced during supernovae, and since they interact weakly with the surrounding matter, they can carry information about the deep microphysical environments in which they are produced. Understanding neutrino physics in supernovae therefore remains a key challenge in both astrophysics and nuclear physics. This project investigates the role of nuclear many-body correlations and mean fields in modifying neutrino absorption and scattering rates in supernova environments, starting from microscopic models of nuclear two-body and three-body forces. The work develops new statistical inference tools for propagating uncertainties in the nuclear force to observable properties of the neutrinos created in supernovae. A significant outcome of the project will be a set of consistent equations of state and neutrino opacities for homogeneous nuclear matter across a range of densities, temperatures, and proton fractions that are important for astrophysical simulations. These will be tabulated in a form that is usable by the astrophysics simulation community in order to make more reliable predictions for the neutrino signals from galactic core-collapse supernovae that may be observed through ground-based neutrino detectors. The microscopic calculations carried out in this project are computationally intensive but made tractable through the use of new generative machine learning models also developed during the course of the project. This project advances the objectives of "Windows on the Universe: the Era of Multi-Messenger Astrophysics", one of the 10 Big Ideas for Future NSF Investments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

This award supports research to improve collaboration between humans and robots in dynamic industrial environments such as construction and manufacturing settings. Environmental factors such as temperature, lighting, and noise can affect each worker's performance and reaction time differently, depending on their unique physical and mental characteristics. These variations can impact on the overall effectiveness and safety of human-robot collaboration, particularly in scenarios where the robot assists without taking over control. Current robotic systems do not adequately account for such differences, limiting their ability to adapt to changing environments or individual workers’ needs. This research will create a new generation of human-centered robotic systems that monitor both environmental conditions and human well-being in real time and adjust their behavior to support smoother and more efficient teamwork. The robots will interpret indicators of workers’ mental states and use that information to adjust how they interact. They will also communicate their status to human partners intuitively. These innovations are expected to enhance workplace safety, task accuracy, and worker satisfaction, especially in labor-intensive jobs. Broader impacts of the project include the integration of research outcomes into university curricula and outreach programs aimed at inspiring and educating students from high school through graduate levels. This research aims to develop an adaptive human-robot collaboration framework. The approach integrates real-time human state with adaptive robot control, allowing the robot to respond intelligently to changes in human and environmental conditions. Human states are inferred through physiological sensing methods and used within a closed-loop system to guide collaborative behaviors. The robot communicates its internal state and intentions through intuitive multimodal feedback, promoting seamless coordination and reducing cognitive effort for the human operator. The control strategy leverages deep reinforcement learning techniques to optimize decision-making in complex, high-dimensional environments. The system will be tested in both laboratory and real-world settings to evaluate its robustness and effectiveness. Results from this work are expected to contribute to the advancement of control, perception, and learning in human-centered robotics, with broad implications for future collaborative systems across various industries. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Major consequences of thermal changes in oceans globally include species movement into previously unoccupied regions and the proliferation of species that can tolerate a broad range of environments. In the oceans, jellyfish populations are increasing and expanding into new regions, which can have dramatic impacts on fisheries, tourism due to stings, and how nutrients are cycled in coastal ecosystems. However, the ability to understand how, why, and if jellyfish populations are increasing and the downstream consequences, is hindered by the lack of understanding of jellyfish basic biology and what contributes to their survival, reproduction, and movement patterns. The proposed research will track and study the upside-down jellyfish, which is expanding their range northward along both coasts of Florida. Genetics, epigenetics, and thermal tolerance of range expanding northern Florida populations will be compared to original founding populations in the Florida Keys, ultimately revealing how these jellyfish adapt, move, and establish new populations. This work involves strong collaboration with community scientist programs in Florida, who will help track these newly established populations. The research goals will also be integrated into the classroom at Texas A&M University through development of a Course-based Undergraduate Research Experience (CURE), where clonal jellyfish propagated in the lab will be used to study how different aspects of the environment promote reproduction and survival. This course will focus on developing students’ critical thinking and problem-solving skills as they tackle broad questions in the fields of ocean sciences, genomics, and molecular biology. As a consequence of rapid global environmental fluctuations, some organisms are suffering dramatic declines in populations sizes, while others are expanding their ranges into previously uninhabited regions. Range expanding populations often show evidence of adaptation and acclimation, thus providing an ideal system to ask questions about the relative roles of adaptation and plasticity in response to rapid change, and the molecular mechanisms underlying them. Prior work has documented the northward expansion of the tropical coastal jellyfish, Cassiopea xamachana, that is occurring along parallel coasts in Florida. The proposed work will examine interpopulation differences in physiological and molecular responses to thermal stress that may be driving their expansion, as well as how symbiosis and host genetic and epigenetic variation may shape evolutionary processes occurring during range expansion. Additionally, C. xamachana exhibits clonal and sexual phases of their life cycle, thus allowing experiments to tease apart mechanistic epigenetic effects from genetic background in the context of phenotypic plasticity. While well known in plants, the role of epigenetic marks on adaptive and plastic processes is not fully understood in animal systems, especially ones that are becoming invasive under global change. Therefore, population-specific clonal lines will be utilized to execute a long-term evolution experiment to understand fitness impacts of mutation accumulation and epigenetic change. Research will be directly integrated with educational aims through promotion of community science to track range expansion, and analysis of long-term clonal fitness and molecular data performed through a course-based undergraduate research experience (CURE). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

With the support of the Macromolecular, Supramolecular and Nanochemistry Program of the Division of Chemistry, Professors François Gabbaï and Saranya Pullanchery of the Department of Chemistry at Texas A&M University will explore the potential of a novel group of compounds as anion transporters. The project will investigate how the accessibility of the anion binding sites in these compounds, their positioning, and their electronic characteristics influence anion transport across artificial models of biological lipidic membranes. Optical measurements will clarify how these transporters behave in the lipid membranes, both in the presence and absence of the anionic cargo. This interdisciplinary project will contribute to the education of graduate students while also providing opportunities for various outreach activities. Owing to their low steric profile and easily accessible binding sites, telluronium cations have emerged as promising platforms for anion binding chemistry. Aiming to establish the use of these systems for transporting anions across phospholipid bilayers, this project will first seek to understand the structural and electronic variations that influence transport, particularly in cases of chloride and trifluoracetate anions. In addition to monofunctional systems, the project will explore bis(tellurium) cations as bifunctional platforms adapted to the complexation and thus transport of the polyatomic trifluoracetate anion. The new telluronium-based transporters will be characterized, and their activity will be evaluated using vesicle assays. A clearer mechanistic picture will be gained from second-order nonlinear optical techniques, which will shed light on the precise behavior of the transporters in the lipid membranes and how this behavior is altered when an anionic cargo interacts with the tellurium center. These various approaches will paint a comprehensive picture of the supramolecular behavior of these telluronium cations and their potential as anion transporters. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

The Strong Nuclear Force, one of the four fundamental forces in the universe, is being studied at particle collider facilities around the world, such as the Large Hadron Collider (LHC) at the European Center for Nuclear Research (CERN), the Relativistic Heavy-Ion Collider (RHIC) at Brookhaven National Laboratory (BNL), and the planned Electron Ion Collider (EIC) at BNL. In these facilities, protons, nuclei, or electrons collide at high energies to investigate the structure of protons and the behavior of nuclear matter in extreme conditions. A full theoretical understanding of the Strong Force, by solving Quantum Chromodynamics (QCD), has still not been achieved. To connect such theoretical calculations to experimental data from collider facilities, large scale computer simulations are needed. Utilizing advanced statistical methods, it is then possible to extract fundamental properties of QCD from data. This team, a multi-disciplinary collaboration of physicists, computer scientists, and statisticians, is developing a software framework, the Comprehensive Event Generator for Chromodynamics with a Statistically and Computationally Advanced Program Envelope (C-SCAPE), to bridge theory and experiment. As a software framework, C-SCAPE utilizes a strategy of breaking complicated processes into subprocesses with their own simulation codes, or modules, that can work together seamlessly. C-SCAPE builds on the success of previous frameworks with more limited capabilities. C-SCAPE can simulate more collision systems and more observable processes than its predecessors, with more flexibility for the user. The project will also provide training for a workforce of young scientists in modern computational, statistical, and physics methods. C-SCAPE will expand the scope of previous task-based frameworks to support the increasing complexity of the relevant physics questions. It will allow physics to be steered in a modular and transparent approach, through more fine-grained sub-task entities. Key physics modules and part of the framework will be optimized to support parallel execution, which will allow the use of GPUs and multicore CPUs on exascale computing resources. The framework enhancements will allow the inclusion of numerous new physics modules, e.g. for processes induced by photons and electrons, and processes in which the spin of quarks and gluons is traced. In addition, existing capabilities for proton-nucleus and nucleus-nucleus simulations will be expanded, in particular those with cross-relevance for the EIC. The unique strength of C-SCAPE will be in the connections it offers when unifying computational schemes between different branches of QCD, thus enabling bridges between communities in high energy nuclear physics. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Physics at the Information Frontier (PIF) Program in the Division of Physics within the Directorate for Mathematical and Physical 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 2025 · 2025-09

Viruses are the most abundant biological organisms on our planet. While all microbial populations are impacted by viral infections, little is known about the impact of viral infections on specific microbial populations. The consequences of virus–microbe interactions on biogeochemical cycles are also poorly understood. This project focuses on sulfate reduction, a key process that links the global elemental cycles of carbon and sulfur. The research aims to understand the relationships between viruses and sulfate reducing bacteria and how these interactions contribute to carbon cycling. This project also supports STEM workforce development through experiential learning activities at K-12, undergraduate, and graduate levels. The training activities highlight research on the Gulf coast and how the Gulf is a unique environment. In addition, the education activities emphasize the importance of sulfate reduction and other geochemical processes and showcase the importance of microorganisms in coastal ecosystems. The project aims to change the negative view of viruses as agents of diseases by highlighting the essential roles of viruses in ecosystem processes. The project uses a multidisciplinary approach to investigate the relationship between viral activity and sediment microbial metabolism, specifically sulfate reduction, through environmental observations, process-oriented biogeochemical incubations and modeling. This research provides novel insight into the interactions between viruses and microorganisms, and how they control early diagenetic processes by (i) determining the impact of viruses on sediment metabolism in general, (ii) quantifying the influence of viruses on microbial sulfate reduction rates, (ii) elucidating the interactions of sulfate reducing microorganisms and viruses. These results are being incorporated into a reactive transport model to describe viral dynamics and their interactions with the C, S, and Fe cycles. The model forms a framework to integrate the observational data and provides a tool for estimating the broader implications of the targeted virus-microorganism interactions quantified in the sulfate reduction zone. This project is jointly funded by the Biological Oceanography and Chemical Oceanography 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.

NIH Research Projects · FY 2025 · 2025-09

Project Summary/Abstract: While it is well established that phenotypes can be influenced by epigenetics and the microbiome, emerging evidence shows that microbes can directly influence the host epigenome and vice versa, contributing an additional axis of variation affecting phenotypes. While the individual impacts of the microbiome on the host phenotypes are thoroughly studied, there remains a critical gap in knowledge as to how microbes and host epigenetics influence each other, and more broadly, how this additional axis of variation can influence larger scale processes of adaptation and phenotypic plasticity. The purple sea urchin, Strongylocentrotus purpuratus, has large range spanning Baja, Mexico to Alaska, with limited population structure due to the long dispersal distances of their planktonic larvae, but evidence of local adaptation to pH. Further, they exhibit one of the best studied examples of adaptive phenotypic plasticity, morphological extension of the arms in response to low food availability. In addition to being a well poised model to study adaptive processes in the face of high gene flow and phenotypic plasticity, S. purpuratus has been used for decades as a model organism due to its unique evolutionary position as a deuterostome invertebrate, a highly characterized immune response that is homologous to vertebrates, well described genomic resources, and a transparent larval stage that enables easily trackable cell biology. Our goal for this five-year project is to use S. purpuratus to study the relative roles of microbes and the epigenome on molecular and morphological phenotypes and how they contribute to adaptive processes and phenotypic plasticity. In this project, we will profile natural microbial communities in the seawater across a latitudinal range and run controlled experiments on early embryos to reveal how natural microbial communities in the water, external to larvae, influence the development of the larval immune system and epigenome. Embryos collected from sites spanning >1000 miles will be reared in the presence or absence of natural microbial communities, and we will quantify the development of key immune cells and responses to known pathogens. In concert, we will profile genome-wide changes in gene expression, DNA methylation, and chromatin accessibility. We will integrate this dataset through novel analytical approaches to reveal core mechanisms underlying immune development in wild populations and the role of adaptive processes and genetic background in shaping these patterns. Additionally, we will test the role of internal gut microbes on adaptive phenotypic plasticity through modulation of the host epigenome using targeted pharmacological agents. The proposed work will encompass the core research in my lab and connect to our other investigations of mechanisms underlying phenotypic plasticity in other marine invertebrate models. Our innovative approach to connect interactions between the microbiome and the host epigenome to larger scale processes of adaptation and plasticity will lay the foundation for my highly integrative research program.

NIH Research Projects · FY 2025 · 2025-09

Physiological processes such as the sleep-wake cycle, metabolism, hormone secretion,neuro transmitter release, sensory capabilities, and a variety of behaviors including sleep, aggression, and mating are controlled by a circadian rhythm adapted to 24h day-night periodicity. The suprachiasmatic nucleus (SCN), which is in the anterior hypothalamus, controls the physiological responses in vertebrates. The peripheral tissues such as liver, heart, kidney, and mammary glands contain functional endogenous glands. SCN influences both the peripheral clock (which regulates numerous physiological processes including proliferation and apoptosis) as well as the central clock via a combination of neural and hormonal signals. Several epidemiological studies revealed that circadian rhythm disruption (CRD) impacts human health and increases the risk of developing metabolic disorders, cardiovascular diseases, and mood disorders. As the exact molecular mechanisms by which CRD alters mammary microenvironment are not known, therefore, in this study we propose to leverage the strength of next-generation sequencing and statistical bioinformatics approaches by performing single–cell spatial proteomics of the studied samples. We hypothesize using this high throughput technique will not only give an unbiased global and complete view of the cellular activities but will also provide pivotal insights about the affected cellular pathways. Using spatial transcriptomics, we will measure gene expressions at the single cell level along with the information of spatial locations of these cells in the tissue. In spatial transcriptomics, the gene expression data, along with spatial co- ordinates of the single cells, provides information on both gene expression significance and cell spatial dependencies. We propose flexible Bayesian approaches to investigate how CRD affects cell composition of a tissue by using spatial clustering algorithms to the spatial transcriptomic data. Next, after obtaining the cell types we will identify the cell-type-specific spatially varying genes. These will be utilized to see the effect of CRD disorder in gene and cell levels. The proposed research is targeted to single cell spatial transcriptomics; however, the derived methods and the results will have deep impact on the research fields of Bioinformatics and data science. Finally, computationally efficient, and tractable software (R/Python) packages will be developed, will be delivered and will be regularly updated to maximize impact across both statistics and medicine. The proposed research has immense transformative potential in the areas of basic cell and development biology, and single cell bioinformatics. It will bring together researchers from multiple disciplinary areas to conduct research on these fundamental themes. RELEVANCE (See instructions): The proposed research will provide critical answers as to whether circadian disruption via shift-work or traveling across the zones can impact mammary gland development and set the stage for further investigation of the underlying mechanisms. This study will lead to a better understanding of how circadian rhythm disruption (CRD) interrupts cell- cell interaction during different developmental stages using the data from single cell transcriptomic technique and will identify the key genes.

NSF Awards · FY 2025 · 2025-08

Numerous industrial and societal sectors depend heavily on the algorithmic automation that has emerged from Artificial Intelligence and Machine Learning. However, many algorithms were originally conceived to work approximately well most of the time, which does not fit the standards for areas critically important to the United States, such as defense, medicine, and transportation, where slight failure, however infrequent, is not an option. The purpose of the project is to further develop a mathematical framework called Optimal Recovery, which provides guarantees for function learning and recovery under realistic modeling assumptions. The results are expected to have implications in any field of science where average-case guarantees are not sufficient and worst-case guarantees are sought. The project also involves training early career mathematicians in computational and data-related topics that lay at the foundation of timely developments in Artificial Intelligence. The planned investigations are intended to widen the scope and applicability of Optimal Recovery on three selected topics. In the first topic, the theory and practice usually centered on functions with single real-valued outputs will be extended to functions with more complicated outputs. In the second topic, common assumptions of convexity on the quantities of interest and on the model sets will be generalized, allowing the results to apply to non-convex models including those utilizing neural networks. In the third topic, the recovery of dynamical objects will be studied, in particular graphs, that extend to timely and more complex models that can deal with data such as destructive observations. State-of-the-art Optimization Theory will naturally play a prominent role throughout. Some parts of the project are inspired by challenges raised at Los Alamos National Laboratory, where novel numerical methods will be tested in these application-oriented settings, which will in turn provide fresh mathematical insight. The computational outcomes will be made publicly available to the scientific community. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

The base of the marine food web consists of phytoplankton, or microscopic plants that need to be fertilized by the elements nitrogen (N), phosphorus (P), and iron (Fe), to grow and sustain global fisheries. The ultimate source of N to the ocean, and thus to marine phytoplankton, is provided by marine microbes that carry out a process known as N fixation. While N is an essential component of phytoplankton biomass, we do not have good estimates of the locations, times, or magnitudes when N fixation occurs in the ocean. Without knowing where and how much N phytoplankton obtain from N fixation we cannot accurately predict the capacity of the ocean to support fish stocks and their ability to withstand environmental changes. The southwest Pacific Ocean has some of the highest rates of N fixation in the global ocean, but we don’t have a complete understanding of the fate of newly fixed N, or how it may change depending on which microbes carry out N fixation. This project seeks to track the fate of N from N fixation using geochemical tools in a collaboration with French scientists. French colleagues will collect samples to be sent to Texas A&M University for analysis. The French scientists will also share data that will be used to interpret the geochemical measurements made as part of this study. Together, this information will be used to understand the fate of newly fixed N. Specifically, the study will examine whether newly fixed N is retained in the surface ocean in a form that phytoplankton can use, or whether it sinks to the deep ocean to be recycled by microbes, and whether the fate changes depending on which microbes carry out N fixation. A graduate student, undergraduate student, and technician will be supported by this award and trained in cutting-edge biogeochemical techniques. The proposed work will analyze the dissolved organic nutrient concentration and the nitrogen and oxygen isotopic composition of dissolved nitrogen species in samples currently being collected by French colleagues in the tropical southwest Pacific. These data will be used to evaluate the rates and fates of biologically-mediated di-nitrogen (N2) fixation and specifically, the contribution of N2 fixation to export production using seasonal “delta 15N budgets”. Additionally, this project will evaluate whether newly fixed nitrogen (N) is accumulating in the dissolved organic nitrogen (DON) pool. Variation in the partitioning of newly fixed N between the sinking flux and the surface DON pool will be compared with diazotroph community composition evaluated by French colleagues. Finally, changes in the stoichiometry of dissolved organic nutrients (i.e., DON:DOP concentration ratios) will be used to further track their production and consumption in these regions where inorganic nutrients are scarce, and especially the importance of DOP for supporting N2 fixation. The results will be evaluated in the context of rich complementary data, including sediment trap and water column geochemical and molecular biological as well as physical oceanographic data, collected by French collaborators as part of their “HOPE” project. This collaboration represents significant cost savings to NSF as ship time, sample collection, and all complementary analyses will be funded by the French collaboration. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

With the support of the Chemical Measurement and Imaging Program in the Division of Chemistry, Professor Lane A. Baker of Texas A&M University will develop new instrumentation and tools for measuring chemical and biological species at electrode surfaces. Specifically, reactions and processes where ions or electrons are involved in electrochemical reactions will be studied at nanometer length scales. To meet this challenge, new instrumentation will be constructed that enables the combination of multiple imaging modalities to be carried out at the same time. Specifically, hardware and protocols to enable integrated electrochemical imaging and optical imaging (e.g., bright field, dark field, fluorescence) will be developed. Methods to efficiently analyze and process data from newly developed instruments with statistical and machine learning approaches will also be pursued. This research project will help to advance the fundamental understanding of chemical and biochemical processes related to neuronal communication, wound healing. This research advances the understanding of molecular biology, and in turn informs efforts to improve human health and the treatment of disease. Additionally, this research project will study catalytic reactions at nanoparticle catalysts, which will aid in developing efficient and selective chemical transformations of interest in applications related to energy and materials. Students trained in this project will learn state-of-the-art fabrication, measurement and characterization protocols, which will add to their high-level technical skills and contribute to the STEM workforce upon their graduation. In addition, a web resource to disseminate information to other scientists working in the area will be developed. An annual meeting of undergraduate students, graduate students and postdoctoral associates engaged in electroanalytical chemistry will also be coordinated through the auspices of this project. This project will develop Optically Guided-Nanoscale Electrochemical Imaging (OG-NEI) as a generalizable platform for integrating optical and scanned probe electrochemical imaging. We will quantify improvements in data collection, statistical analysis and high-throughput measurements. Machine learning approaches for data analysis will be developed to align data from complementary imaging modes. We will demonstrate incorporation of OG-NEI in scanning electrochemical microscopy, scanning electrochemical cell microscopy and scanning ion conductance microscopy platforms. Samples to be studied include neuronal cells, monometallic and mutlimetallic nanoparticle catalysts and epithelial cell monolayers. Success in these aims will advance knowledge by resulting in new instrumentation for electrochemical measurement and imaging with greatly expanded utility and applicability for modern nanoelectrochemical imaging. Results will be widely disseminated to the community as a functional OG-NEI imaging platform. Outreach efforts and impact in graduate electrochemical education will be continued through the Society for Electroanalytical Chemistry Student Group Meeting. The broader impacts of this project that will benefit society include contribution to the education of students trained in state-of-the-art instrument design and construction. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

Variability in weather can have strong effects on ecological communities, especially near geographic range limits. Mangroves (salt tolerant trees) and salt marsh plants (mostly grasses) both live on the coast, but mangroves cannot tolerate hard freezes and so are more common in the tropics. A hard freeze will kill most mangroves, leaving behind bare sediment. In the following years, these areas of bare mud may become occupied by either marsh plants or mangroves, or remain bare mud. Because people rely on coastal wetlands for many “services”, such as protection from storms, a better understanding of which plants recover after a freeze, and how quickly they recover, will help coastal communities understand if mangroves near their high-latitude range limits are reliable “green infrastructure” that can be counted on to protect coastlines from storms and erosion. This knowledge will help guide the design and management of wetland restoration and green infrastructure projects. More generally, this project will provide new insights into how ecological systems respond to and recover from severe weather events. The project builds on more than ten years of research on the Texas coast at an experimental site (ten, 24 x 42 m plots) in which mangroves were thinned to create plots ranging from zero to 100 percent mangrove cover, and at several survey sites dominated by either mangroves or marsh plants. A hard freeze in 2021 killed most of the mangroves at these sites. This research will document the “successional sequence”, which plant species recover after a hard freeze, and how quickly they reestablish, This will be done by continuing to sample existing experimental and survey sites. Additionally, the research will manipulate the successional sequence at the experimental site to find out how different types of vegetation (marsh plants versus mangroves) affect sediment loss versus gain. This will be done by removing mangrove seedlings in some experimental plots to create some plots that are dominated by marsh plants and others that are dominated by mangroves, and measuring how this vegetation manipulation affects elevation change and intertidal sediment dynamics. Last, the research will document how higher trophic levels, especially crabs and snails, influence the dynamic interactions between wetland plants and intertidal sediment loss or gain. This will be done with a combination of monitoring and laboratory experiments. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

Geometric approachs often provide an effective framework to study a great variety of problems, ranging from modeling the interactions of elementary particles to practical problems such as computer vision. Networks such as social networks or telecommunication networks can naturally be seen as a geometric object by considering the number of edges of the shortest path connecting two nodes in the network as a quantity measuring their proximity. A graph equipped with its shortest path distance is an example of what mathematicians call a metric space. This extremely useful abstract concept generalizes the classical notion of distance and plays a pivotal role in mathematical models for optimization problems in networks. Understanding whether a graph, which is a nonlinear object, can be faithfully represented in a linear space allows one to leverage a wealth of geometric tools to gain insight. This project will also provide training to graduate students and junior researchers. In this project, the Principal Investigator will use various curvature-like inequalities to measure the distortion of a geometric structure when it is mapped into curved space using non-standard probabilistic framework. The study of curvature-like inequalities and metric embeddings is strongly connected to a central aspect of the Ribe program. The Kalton program consists in the discovery of metric invariants that capture the geometry of graphs and characterize local and asymptotic properties of Banach spaces. On a conceptual level, the project helps to explain how problems in the Kalton program can be seen as limits of problems in the Ribe program. At the same time, the new probabilistic intuition should provide new approaches to attack long-standing open problems in the Kalton program. The project concentrates on new metrics invariants capturing the geometry of countably branching diamond graphs and trees and to formulate an asymptotic Enflo problem that is central to the study of the geometry of countably branching Hamming graphs. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

NONTECHNICAL SUMMARY This award supports theoretical research and associated education on the dynamics of quantum systems. Recent experimental breakthroughs in a variety of quantum systems have made it possible to isolate and control many interacting quantum particles over extended periods of time. Due to interactions among the particles, these systems often appear to settle into equilibrium and remain static, a process known as thermalization. However, unlike in classical systems, the underlying quantum state continues to evolve in time, even when the system looks static on the surface. The quantum state contains complete information about the system. The time evolution of the quantum state can give rise to universal quantum phenomena with no classical counterpart. Building on recent developments in quantum many-body physics and quantum information science, this research explores the rich, hidden dynamics of quantum states that persist even after local equilibrium is reached, aiming to uncover universal behavior - properties that are independent of the details of a quantum many-body system, and to harness the complex quantum states for novel quantum technologies, such as new quantum error correction codes. This project incorporates educational activities aimed to train undergraduate and graduate students and disseminate quantum science to broader audiences. The research team will make a quantum booth showcasing interactive demos and games at public events and on social media to illustrate the core concepts and ideas of quantum mechanics. Additionally, the PI will work with local high school teachers through workshops focused on developing strategies to introduce quantum concepts into their curricula. TECHNICAL SUMMARY Integrating tools from quantum many-body physics and quantum information science, this research combines analytical and numerical approaches to study quantum many-body dynamics along three main thrusts: (i) revealing how unitary dynamics scramble local information into non-local entanglement and developing a general decoding protocol using the Petz recovery map; (ii) investigating how symmetries constrain and enable control over scrambling through the transport of conserved quantities; and (iii) characterizing the largely unexplored long-time behavior of many-body unitary dynamics using higher-order Green’s functions on multi-folded Keldysh contours to uncover new dynamical regimes. The overarching goal is to understand universal many-body dynamics beyond thermalization across different time scales and to harness the entanglement and complexity of the time-dependent quantum states for novel quantum technologies. For instance, insights into how unitary dynamics scramble information could lead to new quantum many-body teleportation protocol and new quantum error correction codes that store and protect quantum information beyond the stabilizer formalism; understanding the role of symmetries may enable manipulation of stored quantum information via conserved quantities; and exploring the post-scrambling regime after local information is fully scrambled may reveal new time scales of quantum many-body dynamics and new ways to exploit the complex structure of quantum states. This project incorporates educational activities aimed to train undergraduate and graduate students and disseminate quantum science to broader audiences. The research team will make a quantum booth showcasing interactive demos and games at public events and on social media to illustrate the core concepts and ideas of quantum mechanics. Additionally, the PI will work with local high school teachers through workshops focused on developing strategies to introduce quantum concepts into their curricula. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

This project is centered at the interface of geometric topology and quantum topology, with an influence of the recent developments in mathematical physics and probability theory. The research builds on the primary investigator's (PI) prior work, and will be partially conducted with collaborators, who bring in relevant expertise. In addition to the research itself, the project includes an educational component, integrated within the research project, which aims at enhancing the training of young mathematicians in this general area of mathematics. This aspect of the project involves the development and expansion of a strong geometric topology group at Texas A&M University, and the nurturing of a community of young mathematicians interested in quantum topology and low-dimensional geometry through conferences and other activities. The project is articulated along two inter-connected research directions related to the asymptotics of quantum invariants and their relationship with hyperbolic geometry. (1) The PI plans to study a family of Turaev-Viro type 3-manifold invariants constructed from the Virasoro TQFT and their asymptotic behavior. This builds on recent joint work of the PI where a one-parameter family of Turaev-Viro type invariants was defined for a hyperbolic 3-manifold with totally geodesic boundary and it was proved that this family of invariants decays exponentially with a rate given by the hyperbolic volume of the manifold. This research will be developed in collaboration with Xin Sun, Baojun Wu, Tianyue Liu and Shuang Ming. (2) As a crucial step towards the Volume Conjecture for the Reshetikhin-Turaev invariants, the PI aims to study various properties of the fundamental shadow link complements. This research will be conducted in collaboration with the PI's Ph.D. student Inyoung Ryu. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

With support of the Chemical Mechanism, Function, and Properties Program of the Division of Chemistry, Professor François Gabbaï of the Department of Chemistry at Texas A&M University is investigating the ability of specific types of acid-base complexes to interconvert between two forms: namely, an inner form where the two components are bonded in a traditional sense and a more loosely held outer form that resembles an early stage in bond-forming processes. Studying these complexes can support a better fundamental understanding of chemical reactions and bonds. In addition to these objectives, this project aims to leverage this phenomenon for the discovery of next-generation catalysts, including photocatalysts. This multifaceted project will support catalyst development, produce knowledge in physical organic and inorganic chemistry, and contribute to the education and training of future scientists. Encounter complexes, also referred to as outer complexes, are typically intermediates invoked in various reactions, including Lewis acid-base adduct formation. This project will specifically target adducts of Lewis acidic carbenium ions that can isomerize between their datively bound inner form and their more elusive outer form, where the donor-acceptor interaction is non-covalent. By tethering the Lewis-opposite functionalities, the work will show how the nature of the carbenium unit, the donor properties of the Lewis base, and the backbone structure can be used to adjust the respective energies of the inner and outer forms, which is a prerequisite for dynamic inner/outer isomerism. The project will also explore how such a phenomenon may be harnessed for the reversible masking of reactive carbenium ions and for their possible use in photoredox catalysis. Another aim will employ this inner/outer isomerism as a tool to adjust the redox properties of the main group functionality acting as the Lewis base, with the objective of increasing two-electron redox cycling at chalcogen and pnictogen centers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

This project investigates the geologic controls on economic mineralization. The work will be conducted near a known mining region in Ouray, Colorado. This area was mined for gold in the late 1800s and early 1900s. Today, critical minerals and rare earth elements are important to the global economy. This work will take a new look at this gold mining district and see if there is evidence for critical minerals. The study area is within the Colorado Mineral Belt. The project will investigate when and how igneous activity occurred. This work will conduct chemical analyses of the rocks in the area to see if critical minerals are present. This project will analyze the faults and fractures surrounding the area. The work will conduct a teacher training module for 5-12 grade educators. This project will train undergraduate and graduate STEM students. The geologic research will improve understanding of the controls on critical mineral deposits. This will help improve how geoscientists explore and assess potential mineral resources. This project will investigate the interplay between structures, magma source, and thermal history at the previously mined Ouray stock and surrounding alteration halo. This location was selected because of its presence within the Colorado Mineral Belt and next to the Ancestral Rocky Mountain Uncompahgre Uplift (with associated deep-seated structure). The Ouray stock shares similarities with models of volcanic-hydrothermal systems associated with ore deposits. However, the Ouray stock lacks geochemical analyses needed to determine the source of magma that fed the intrusion, there are minimal constraints on the thermal history of the intrusion and host rock, and the structural context and relation to other parts of the Colorado Mineral Belt are undefined. This work will address four research questions. 1) What is the rare earth element composition of the Ouray stock and host rock? 2) What is the timing of emplacement and cooling of the Ouray stock, and what is the timing of mineralization? 3) What is/are the source(s) of the magma that formed the Ouray stock? 4) What is the role of pre-existing structures on the location of the Ouray stock? These questions will be investigated with multiple techniques. 1) New whole rock geochemical analyses of the Ouray stock and host rock. 2) New geochronologic, thermochronologic, and peak temperature analyses will be made of the intrusion and host rocks. 3) New hafnium isotopic analyses from the intrusion will be conducted to assess magma source. 4) New mapping and kinematic modeling of deformation features will be conducted to determine the role of structures. Addressing these questions has implications for investigating how the interplay between structural inheritance, magma source, and thermal history may influence mineralization timing and distribution of critical minerals in a previously mined Laramide pluton, with implications for other plutons within the Colorado Mineral Belt. This project will assess the roles of geologic and geochemical processes that concentrate critical minerals and will contribute toward characterization and potential discovery of critical minerals within the Colorado Mineral Belt. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

Topological insulators are a class of materials that are insulators in their bulk and that nevertheless allow wave propagation along their edge. Such materials are at the forefront of the rapidly developing industry of low-energy consumption electronics technologies as they yield a fundamentally new type of electronic transport with ultra-low resistance. Mathematically, such transport is modeled by wave functions corresponding to the eigenvalues appearing, after introduction of a boundary, in a gap of the spectrum of the material without boundary. The principal goal of the project is to develop mathematical methods for measuring the number of such states based on readily computable information about the physical models of the corresponding material. The principal investigators investigate discrete boundary value problems for the tight-binding Hamiltonians describing electronic transport in topological insulators. One of the main themes is the derivation of explicit formulas for the number of eigenvalues in the gaps of the essential spectrum, which correspond to edge states localizing along the boundary. The formulas are expressed through mathematical tools stemming from symplectic geometry, such as the Maslov index and its discretization, the Duistermaat index, with the latter being particularly amenable to numerical computation. In addition to eigenvalues in the gaps, the new formulas give access to the integrated density of states (in the bands of the continuous spectrum) and shed new light on the bulk-boundary correspondence by connecting the gap indices with the band indices. The discrete boundary value problems are described using the theory of boundary triplets of non-densely defined symmetric operators. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

Mechanochemistry, the use of mechanical force to drive chemical reactions, was named in 2019 by the International Union for Pure and Applied Chemistry (IUPAC) as one of the top ten technologies that would change the world, as it permits cleaner, safer, and more efficient approaches to chemical synthesis and manufacturing. While many advances have been made towards understanding mechanochemical processes at the fundamental level over the past decade, a key challenge that remains is how to scale-up these approaches to afford reliable manufacturing at the industrial scale. This IRES project builds upon a collaboration between Texas A&M University (TAMU), leveraging its leadership position as the home of the NSF Center for the Mechanical Control of Chemistry (CMCC), with the University of Birmingham (UoB) in the UK, home to the newly completed resonant acoustic mixing (RAM) facility, to advance approaches for industrial scale manufacturing using mechanochemistry. This IRES project supports student researchers from the U.S. to gain hands-on experience in both mechanochemical synthesis and chemical manufacturing, by connecting the fundamental understanding of mechanochemical processes, with the opportunities for process design and scale-up, to support the translation of fundamental work into industrial practice. With the goal of developing next-generation, scalable approaches for mechanochemical syntheses, work being addressed through this IRES project includes several research themes: (i) advancing approaches for scale-up of mechanochemical syntheses; (ii) expanding the methods of solvent-free synthesis; (iii) designing computational approaches for understanding the fundamentals of mechanochemistry; and (iv) developing methods for real-time reaction monitoring. These projects leverage the unique resources and expertise available at UoB for scale-up and real-time reaction monitoring and create new opportunities for partnership and collaboration between the CMCC and UoB for the education and training of students in mechanochemistry. Through this collaboration, this IRES project fosters new directions for the scale-up of mechanochemical reactions, and initiates a global network aimed at advancing the application of mechanochemistry as a sustainable approach for chemical synthesis. In addition to the above-described research training that students receive, their experience is also enriched by a range of integrated professional development activities, including a weekly seminar series that includes presentations specific to learning about mechanochemistry, along with associated training (e.g. scientific writing, giving research presentations, and science communications). As such, this IRES project supports a high-quality international research experience for U.S students to conduct work in a unique global facility, while also garnering interdisciplinary education and training, that supports workforce development for the next generation of chemists in advanced chemical manufacturing. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

Building materials and building envelopes – the barrier separating a building’s interior from the environment – can be compromised by exposure to short, frequent, and intense cycles of freeze and thaw, dry and wet, and hot and cold. Impaired materials in an envelope can reduce a building’s operational energy performance and diminish its thermal insulation, structural integrity and moisture control capabilities. This project will use a combination of experiments and modeling to examine how and to what extent the degraded performance and integrity of building envelopes influence maintenance, repair needs, and heating and cooling demands of affected buildings. The research will bridge knowledge gaps associated with extreme weather-induced material degradation and sustainability of buildings. It will also inform utility providers to more accurately forecast energy demands and optimize power infrastructure for efficient supply-demand balance. By identifying the impact of extreme weather on building envelope performance and its subsequent effects on utility expenses, occupant comfort, and overall well-being of people, this project will help residential and commercial communities to remain sustainable and resilient during extreme temperature and humidity conditions. This project will examine the impacts of heat-moisture swings on envelope performance and life cycle emissions, which helps narrow the performance gap between simulated and measured energy use of buildings and enhances the fidelity of physics-based energy simulations to reflect extreme weather conditions. The study will 1) investigate extreme weather’s influence on the degradation of thermal, optical, and moisture control properties of building envelope via both lab tests and simulations; 2) examine the life cycle emissions impacts caused by deteriorated envelope performance over 55-years of building service life in current and future weather conditions; and 3) develop a novel methodology to integrate the space-time degradation of envelope performance into life cycle energy and carbon modeling. The research results offer architects, engineers, builders, general contractors, facility managers, material manufacturers, and policymakers a critical insight for informed decision-making in extreme weather strategies. The proposed in situ experiential and immersive virtual reality-based learning activities will equip all students with foundational knowledge essential for STEM education and careers to reinforce the United States building construction industry. The research training and mentoring activities for all students will yield long-term workforce benefits, thereby bolstering economic prosperity and technological leadership in the nation. 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.