University of Utah

NSF Awards · FY 2024 · 2024-09

This award funds the research activities of Professor Paolo Gondolo at the University of Utah. Dark matter and dark energy are two of the most intriguing and mysterious components of our universe. Dark matter is an unseen substance that does not emit, absorb, or reflect light, yet it exerts a gravitational force, helping to hold galaxies together. Dark energy is an unknown form of energy that is driving the accelerated expansion of the universe. Understanding the nature of dark matter and dark energy is crucial because they make up about 25% and 70% of the universe's total mass-energy content, respectively. Unraveling their secrets could fundamentally change our comprehension of the cosmos and the laws that govern it. Thus research in this area advances the national interest by promoting the progress of science in one of its most fundamental directions: the discovery and understanding of new physical law. In his research, Professor Gondolo will develop innovative methods to investigate the nature of dark matter and dark energy in areas that have been hitherto only slightly explored, such as newly proposed forms of dark matter (e.g., molecular dark matter), the possibility of trapping dark energy, and of using rotating particles to probe gravity theories. This project also envisions to have significant broader impacts. Professor Gondolo will involve undergraduate students in his research, thereby providing critical opportunities for a next generation of physicists. Professor Gondolo will also lead a science outreach program for K-12 students and their families. More technically, Professor Gondolo will (a) explore theoretical explanations for the dark matter in the Universe based on particle physics beyond the Standard Model, including strategies to eventually measure astrophysical properties of particle dark matter; (b) make progress toward an understanding of dark energy by studying compact objects with vacuum interior, including their possible observational signatures and models for their formation and rotation; and (c) test aspects of gravity, like its coupling to spin, by exploiting the precision of modern gravitational measurements of the motion of matter in strong gravitational fields. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

Numerous studies note that, over the past several decades, children in many Western societies spend less time engaged in independent exploration, less time in outdoor green spaces, and more time in structured activities which are supervised by adults. While these shifts frequently reflect parental concerns for their children’s safety and academic development, recent studies highlight risks associated with a loss of independence and time spent in nature among children. With that in mind, the current study examines children’s exploratory behavior in two societies where opportunities for independence and time spent in nature are cultural priorities in childhood. The research team investigates children’s independent exploration of their environments (e.g., playing in their neighborhood without adult supervision) and the types of environments children explore (e.g., green spaces versus playgrounds). The researchers then examine how these experiences may be associated with children’s spatial cognition, executive function, and well-being. Finally, the researchers survey the children’s parents to establish possible links between parenting behavior and children’s outcomes. It is anticipated that this study can help parents and educators develop a more beneficial balance between (1) protecting children’s safety and structuring their experiences, and (2) promoting autonomy, exploration, and experience in natural environments. The project assesses children’s exploratory behavior and time spent in different environments through several means including: GPS-tracking via phone, a vegetation index which is combined with GPS data, and a questionnaire concerning children’s experiences in nature. The researchers combine these measures with experience sampling methodology using text messages throughout the testing period so that children can provide information about their location, activity, and mood. Children complete a series of measures assessing (1) spatial ability, including a virtual navigation video game and a mental rotation task, and (2) executive function assessments from the NIH Toolkit Cognitive Battery and parental report. Additionally, researchers use questionnaires to document children’s well-being (via self-report) as well as strengths and difficulties (via parental report). Finally, parents complete questionnaires regarding their parenting style, such as their socialization goals and concerns about risky play. 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

Clouds are studied intensively due to their potential contribution to climate change, as changes in cloud amount or properties due to greenhouse warming could either offset or intensify the warming. The study of cloud change caused by climate change and its subsequent contribution to climate change has been productive but not conclusive, and future climate projections show a wide spread in cloud changes and their subsequent effects. Given the large uncertainty as to how clouds will change it would be helpful if there were some bulk cloud properties which can be counted on to not change, or in other words cloud properties which are invariant under climate change. In earlier work the Principal Investigators (PIs) of this award argued that the cloud size distribution could be just such an invariant, where cloud size distribution means the average number of clouds that occur for a particular cloud size, as measured by cloud area or cloud perimeter. They developed a theory for the cloud size distribution using thermodynamic arguments in which the cloud edge plays a special role as a surface of neutral energy through which ambient air of lower energy mixes with cloud air of higher energy, thereby dissipating the energy generated by solar heating (see AGS-2022941). The theory predicts that the number of clouds of a given size is inversely proportional to a power of the size, where alpha and beta are the powers for size measured by area and perimeter, respectively. The theory also depends on D, the fractal dimension of clouds, making for three geometrical parameters, as well as the square root of the atmospheric stability. Cloud data from satellites confirms the power law relationships but gives values of alpha and beta which differ slightly from theory, in particular the theory predicts beta=1 but cloud data shows beta=1.26. Work performed under this award seeks to further develop the theory and determine the extent to which it lives up to the promise of invariance to climate state. One issue to be addressed is the cause of the discrepancy between observed and predicted parameter values, in particular whether it is an artifact of satellite viewing angle or a real physical effect. The invariance of the three parameters is tested under a variety of climatic conditions including the warm pool region of the western tropical Pacific and the cooler eastern tropiical Pacific, and the contrasting conditions of low and middle latitudes. A further issue to be addressed is the extent to which the invariance is affected by atmospheric composition, as chemical compounds like nitrous oxide can affect cloud properties by generating aerosols. The project also seeks to derive minimal models which correctly predict all three cloud parameters and also account for general characteristics of cloud shape and spacing. The work is of societal as well as scientific interest given concerns over climate change and the importance of clouds for determining the amount of warming produced by a given increase in greenhouse gas concentrations. The work also builds international research capacity as the PIs collaborate with colleagues at the University of Lille who are developing satellite data products based on geostationary satellite observations. The project also supports a graduate student and a postdoctoral research fellow, thereby providing for the future workforce in this research area. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The NSF Center for Aqueous Supramolecular Chemistry (CASC) is supported by the Centers for Chemical Innovation (CCI) Program of the Division of Chemistry. The ability of custom-designed molecules to 1) selectively recognize and bind to negatively charged molecules (anions), 2) transport these anions across membranes and/or 3) enable chemical transformations to new products is an all-but-unmet challenge. This Center will overcome these challenges by synthesizing novel molecules that target two anions of particular importance to society: bicarbonate and perfluorooctanoic acid (PFOA). Carbon dioxide from greenhouse gas emissions resides predominantly in surface ocean waters as bicarbonate. PFOA is well recognized for its persistence and toxic effects in groundwater. The selective capture, transport and transformation of these two anions will foster numerous technological payoffs. Activities within this Center include the training of students in the commercialization of technology and the creation of custom Individual Development Plans for all incoming scholars. CASC will establish a summer undergraduate program that trains students to continue projects at their home institution, and for informal science communication will engage the public in hands-on activities at museums and science centers. CASC will enable the supramolecular control, transport and transformation of oxy and fluorinated anions, a widely recognized and longstanding challenge. The two targeted anions, bicarbonate and PFOA, represent two extremes in terms of size, shape, and solvation, features that will aid in the establishment of fundamental supramolecular principles applicable to a broad chemical landscape. Supramolecular recognition of anions will be manifested via the incorporation of fluxional receptors whose primary recognition motifs are unique ionic, hydrogen, or halogen bonds that are exquisitely sensitive to the local electronic and electrostatic environment. CASC will demonstrate this by adjusting these forces within supramolecular host guest complexes; both the affinity and selectivity of the host guest complexes can be manipulated to enable the design of a new class of switchable receptors. By exploiting electronic and electrostatic forces between a host and its guest, on-demand allosteric control over both the binding and release processes will be established for the transport of ions across lipid bilayer or polymeric membranes. Switchable supramolecular receptors will be utilized as directing agents to improve the reactivity of catalysts and foster transformation. Bicarbonate receptors will be conjugated to reduction catalysts that include iron and iridium complexes, and PFOA receptors will be grafted onto alumina or conjugated with photobases such as malachite green carbinol molecules. The ability to control both affinity and selectivity will propel anion supramolecular chemistry into novel domains that extend beyond recognition and sensing. A newfound capability to simultaneously transport and transform anions in water will impact environmental chemistry, chemical biology, and catalysis. 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

Volcanic rift zones are key features of shield volcanoes such as the Hawaiian Islands. They accommodate the growth and spreading of volcanic edifices and, as areas of weakness, allow magma to travel laterally within the volcanoes and erupt far away from the summit, posing threats or causing damage to local communities and infrastructure. On May 3, 2018, one such eruption occurred in the Lower East Rift Zone of Kilauea. The eruption lasted for about 4 months, destroying over 700 buildings, and resulting in an estimated $800-million-dollar recovery cost. Four years later, Mauna Loa erupted in late 2022, for the first time since 1984. Outpouring lava flows from its Northeast Rift Zone almost reached the Daniel K. Inouye Highway, threatening to cut off the only highway that connects directly the east and northwest coasts of the Island of Hawaii. These two eruptions highlighted the knowledge gaps in our understanding of volcanic rift zones. This project aims to obtain detailed subsurface imaging of the rift zones and their spatial and temporal variations, which are essential for volcanic hazard mitigation. The project will collect seismic data including from a similar survey to one completed after the 2018 eruption. The project will also coordinate with collaborators from Switzerland who will be deploying seismic instruments around Kilauea in 2024. In collaboration with the USGS Hawaiian Volcano Observatory and Hawaii Volcanoes National Park Service, the results from this project will enable the development of new volcano monitoring capabilities and enhance societal preparedness against volcanic hazards. Four linear arrays consisting of 460 nodal geophones will be deployed in the first year of the project: One across the Kilauea Lower East Rift Zone (KLERZ), one across the Kilauea Middle East Rift Zone near Pu‘u‘ō‘ō, two across the Mauna Loa Northeast Rift Zone (MLNRZ) up-rift and down-rift of the 2022 eruption site. In the second year, the KLERZ line and the MLNRZ up-rift line will be re-deployed for constraints on temporal variations at the two locations. The main scientific goals of this project are to understand (1) the fine structures of the Mauna Loa and Kilauea rift zones and the differences between the two, (2) the relation between the fine structures and their volcano-tectonic settings, as well as the relation between the fine structures and the frequency and intensity of rift zone eruptions, (3) the post eruption changes and constraints on rift zone healing and cooling of the magma plumbing system, and (4) the long-term evolution of the Kilauea East Rift Zone. This project is funded by the Geophysics Program and Cross-cutting fund in the Division of Earth Sciences. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

The Standard Model of particle physics has successfully described a wide range of experimental data. Nonetheless, cosmological measurements have shown that the particles described by the Standard Model correspond to only about 5% of the energy density in our universe, with the remaining 95% corresponding to dark matter and dark energy. Despite making up most of the energy density in the universe, very little is known about the dark components of the universe and their dynamics. Professor Marques-Tavares' research focuses on developing new ways to search for particles and forces in this dark sector of the Universe, leveraging data coming from accelerators, astrophysical observations, and cosmology. This research aims to shed new light on two central questions related to dark sectors: whether they have non-gravitational forces; and whether the dark matter energy density is made of multiple species of particles or just one. This work advances the national interest by promoting the progress of fundamental science. In addition, the PI will mentor graduate students and postdocs involved in this research, which contributes to the development of the national STEM workforce. The possible non-gravitational interactions of dark sector particles can be divided into two categories, they can either couple dark sector particles to the standard model or they can be forces that are confined to the dark sector. The PI will conduct a meticulous investigation of new signatures coming from theoretically motivated mediators of forces between the dark sector and the standard model in astrophysical objects, such as gamma-ray emissions following core-collapse supernovae, due to the decay of these mediators, and in cosmology, from late decay of mediator particles produced in the early universe. In addition, the PI will also determine the sensitivity of future lepton colliders to scenarios in which these mediators have larger masses and decay invisibly. To search for forces confined in the dark sector, the PI will study the impact of interactions of dark matter with other dark sector components on the cosmic microwave background and in observations of the large-scale structure of the universe. 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 award funds the purchase of a multi-collector inductively coupled plasma mass spectrometer (MC-ICP-MS) at the University of Utah to enable high-precision non-traditional isotope ratio measurements. Isotopes provide fundamental information about the world around us. The rocks that form our planet have been transformed through its history, with few original remaining pieces that are not deformed and twisted. This disfigured and patchy rock record is our only hope for understanding Earth’s past. Fortunately, some isotopes contained in these rocks are unstable, or “radiogenic”. These isotopes decay over known timescales, and their abundances can be used to estimate ages, such as the age of our planet and all of its pieces. Other isotopes contained in these rocks do not decay, i.e. they are stable. Their relative abundances are set by specific processes, for example interactions with free oxygen and biology. Isotopes contained in rocks serve as a tool for exploring the geologic history of our planet, past climates, and human interactions with the environment. Scientists at the University of Utah and beyond will benefit from the acquisition and availability of the new mass spectrometer. The instrument will be used to date ancient rocks and important events in Earth’s past, to track the movement of elements at and below Earth’s surface, to track the history of free oxygen, and to reconstruct the evolutionary history of complex life. The MC-ICP-MS will be housed in and managed by the Department of Geology and Geophysics at the University of Utah. Isotope ratio data collected with MC-ICP-MS technology is a fundamental research requirement of multiple recently hired early-career tenure-track faculty in the department. Some of the scientific applications of these faculty meet or exceed the limitations of currently present instrumentation. Increased detection limits associated with the new instrumentation will permit the generation of accurate and precise isotope ratio data for much smaller analyte abundances and isotope ratio differences. Technological advances associated with this newest generation of MC-ICP-MS instruments will dramatically simplify isotope ratio measurements for some classically cumbersome elemental systems (e.g., Calcium isotopes). Topics to be studied by the early-career scientists in the department include but are not limited to modern non-traditional isotope cycles, the rise of free oxygen on Earth, important events in biological evolution, anthropogenic pollution, fluid-rock interactions, subduction zone processes, magma genesis, crustal recycling, early solar system processes, and applications of non-traditional isotopes to medicine. Many new and existing users from across our largely rural state will benefit from the new instrumentation. In addition to supporting the education of undergraduate and graduate students in the department, the instrument will support the education of teachers through the Master of Science for Secondary School Teachers offered at the University of Utah. This award is funded by the Instrumentation and Facilities program in the Earth Science Division. 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 award funds the research activities of Professor Zhengkang Zhang at the University of Utah. Our understanding of Nature at the most fundamental level is based on effective field theory (EFT), a theoretical framework that combines quantum physics, relativity, and the fact that Nature is organized by scales (little things affect big things, which in turn affect even bigger things). Agreement between EFT predictions and experimental data underlies the success of elementary particle physics, and has done so over the past century. However, theoretical puzzles remain, and many of them are associated with small numbers. The Higgs boson, for example, has a mass that is much smaller than our expectations from EFT reasoning. Recent studies have also revealed many more small-number mysteries in the form of surprising cancellations in EFT calculations of particle physics models. Under this award, Professor Zhang will develop new theoretical tools to resolve some of these mysteries, and exploit recent developments in machine learning (ML) to advance EFT calculations. Professor Zhang will also perform new calculations to better evaluate the discovery potential of ongoing experiments searching for dark matter. This project advances the national interest by promoting the progress of science in one of its most fundamental directions: the understanding of new theoretical principles and discovery of new physical laws. This project is also envisioned to have significant broader impacts. Professor Zhang will build novel connections between EFT and ML which will improve our understanding of ML and promote more responsible use of artificial intelligence in many aspects of society. He will also involve students and postdocs in his research, thereby providing critical training for junior physicists beginning research in this field. He will also engage in outreach activities to share his research with the public and increase scientific literacy. More technically, Professor Zhang will develop new EFT tools, including geometric and functional methods, and seek to explain “magic zeroes” (surprising cancellations) in EFT calculations involving higher-dimensional operators in the Standard Model (SM). He will, in particular, use functional methods to systematically investigate the conditions under which magic zeroes arise, and further develop geometric frameworks in which EFT amplitudes are covariant under general field redefinitions. This research will at the very least expand the phenomenologist toolbox which will enable us to better understand the structures of SMEFT (Standard Model EFT) and make more efficient use of SMEFT for physics beyond the Standard Model. Optimistically, this might also lead to new insights into the hierarchy problem. Meanwhile, Professor Zhang will thoroughly explore a nascent correspondence between neural networks and field theories, and develop novel ML-inspired approaches for field theory simulations. Finally, he will extend sub-GeV dark matter direct-detection calculations in order to better quantify halo uncertainties and directional sensitivity in phonon-based 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 2024 · 2024-08

This project examines the Pleistocene-Holocene Transition (PHT), during which the first peoples of North America were dispersing across the continent and adapting not only to novel environments, but also to a rapidly changing climate as the Ice Age ended. Anthropologists’ understanding of this time period is limited by a paucity of archaeological sites. The principal investigator, in collaboration with Tribal descendant partners, studies a mortuary site using a range of biological and biogeochemical methods to advance knowledge about PHT residents of North America, including colonization of the Americas, the lifeways of the earliest Indigenous occupants, and human adaptation to rapid climatic shifts. The project supports undergraduate and graduate student training, research collaborations and community engagement with the Muwekema Ohlone Indian Tribe, and public science education activities. The project focuses on an archaeological site that dates to 12,000-9,000 years ago and was used by the ancestors of the Muwekma Ohlone Indian Tribe of the San Francisco Bay Area as a burial ground for their relatives. This is among the oldest known mortuary sites in North America and contains a large number of Indigenous ancestors (n=41). The project is a collaborative effort with the Muwekma Ohlone Indian Tribe to improve collective understanding of their ancestors’ lifeways and the adaptive strategies employed by North America’s first peoples. Specifically, the project seeks to reconstruct mobility, kinship systems, diet, parental investment strategies, and associated fertility by employing proteomic sex-estimation, stable isotope analysis (carbon and nitrogen) of dentinal serial sections of first and third molars, and strontium analysis of tooth enamel. The research outcomes include the generation of osteobiographies that allow ancestors’ life stories and Tribal history to be told. 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

A prerequisite to making AI systems safe and reliable is to get them to do what we, as humans, want. The focus of this project is to enable the safe deployment of learning-enabled systems that learn objectives from human feedback and then robustly optimize their behavior under these learned objectives. What humans want is often highly ambiguous and uncertain, so we need AI systems that are robust to this uncertainty. However, most prior work on reward learning does not easily facilitate uncertainty assessment. The project's novelties are to develop the first scalable learning methods that are robust to uncertainty, enable self-assessment, and provide basic test cases for assessing AI alignment with human values. The project's impacts are fundamentally new capabilities that will allow AI systems to safely learn models of human intent and enable humans to know with high-confidence whether an AI system will behave correctly with respect to that intent. The broader impacts of making progress on safe and robust human-AI alignment include better domestic robots, recommendation systems, self-driving cars, delivery quadrotors, and large language models (LLMs). The project broadens participation in computing by providing educational outreach opportunities for undergraduate research and K-12 summer AI camps. The key observation in this project is that AI systems will always face uncertainty when seeking to identify human intent and values. Thus, there is a need for methods that explicitly reason about uncertainty and can provide probabilistic guarantees of robustness under this uncertainty. The project is pursuing the following three specific objectives that will enable safe and robust reward learning: (1) Probabilistic performance bounds when learning policies from human input: the project is developing approaches that allow humans to know with high-confidence whether a learned policy achieves a desired performance threshold when learning a reward function from human feedback. (2) Unit tests for reward and policy alignment: the project is developing tests that verify with high-confidence whether a learned reward function and behavior are correct. (3) Robustness to reward misidentification and misgeneralization: the project is developing techniques that penalize misaligned behavior during policy optimization to ensure the resulting behavior of the AI system does not lead to unintended consequences. The investigators are applying these techniques to reward learning to prevent reward hacking and also to reinforcement learning with a known reward function to overcome the problem of goal misgeneralization. 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 award supports faculty, postdoctoral researchers, and students at the University of Utah who are pursuing research activities in gamma-ray astronomy. It supports performing astronomical observations and analyzing data to explore the physical forces and processes occurring in some of the most violent astrophysical settings in our universe. By studying the behavior of forces and particles in these extreme environments, the researchers supported by this grant will explore the origin and evolution of stars, galaxies, and the elements of our universe. The award also supports the scientific training of undergraduate students from small liberal arts colleges, funds targeted science workshops and meetings, and provides for faculty and student science outreach activities at Frisco Peak, UT. This project uses the multi-messenger approach to combine observations from the Very Energetic Radiation Imaging Telescope Array System (VERITAS) and High-Altitude Water Cherenkov (HAWC) gamma-ray observatories with satellite, neutrino, and gravitational wave alerts. This study will probe the nature of high-energy astrophysical sources and neutrino emitters such as Pevatrons. The study combines VERITAS γ-ray observations with milliarcsecond scale U-band imaging by the VERITAS Stellar Intensity Interferometer to observe recurrent nova T Cor Bor. These observations are only possible once every 80 years and will examine particle acceleration in a symbiotic binary system. The work will leverage the recently upgraded Schwarzschild-Couder Telescope (SCT) to increase the VERITAS detection area by a factor of about nine at energies above 10 TeV, exploring new morphological and multi-wavelength details at both high angular, and high energy, resolution. 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 2024 · 2024-08

With support from the Chemical Measurement and Imaging Program in the Division of Chemistry, Professor Shumaker-Parry's group at the University of Utah is studying the optical properties of metal nanostructures to improve the detection of chiral molecules. Chirality is a foundational property of molecules defined by the three-dimensional arrangement of connected atoms and the inability of a molecule to be superimposed on its mirror image. Chirality is of critical importance in determining the behavior of molecules, especially in medicine. For example, the chirality of a molecule developed as a therapeutic could determine if the drug is effective, inactive, or toxic. Vibrational Circular Dichroism (VCD) spectroscopy is used to detect and identify chiral molecules. However, the method requires large quantities of material, excluding the ability for trace analysis and detection of impurities. The Shumaker-Parry research group is studying incorporation of metal nanostructures with special optical behavior for VCD to enhance detection of chiral molecules. The development of enhanced VCD analysis through these studies could make plasmon-enhanced VCD a key analytical method for the pharmaceutical industry to improve both efficacy and safety of new drugs. The research incorporates chemistry, physics, and aspects of engineering, providing broad training for graduate and undergraduate students. The interdisciplinary approaches form a foundation for education and outreach activities. Analytical strategies for detection of chiral molecules are limited due to the challenge of dealing with enantiomers that have the same chemical formula and differ only in the three-dimensional spatial arrangement of atoms. The goal of the proposed research is to investigate plasmonic nanostructures with tunable infrared (IR) plasmons and orientation-dependent chiroptical activity for plasmon-enhanced vibrational circular dichroism (PE-VCD) spectroscopy. VCD combines IR spectroscopy and circular dichroism (CD) to provide information about chemical groups and local environment for chiral-based structural analysis of small molecules, biological molecules, and higher order assemblies. The research builds on observations of the coupling of chiral and achiral molecules with plasmonic nanostructures impacting both molecular VCD spectral signatures and IR CD of the nanostructures. The objectives of the proposed research are to 1) improve the capabilities of the VCD instrument for solid substrate measurements, 2) study the coupling of chiral molecules with chiroptically-active plasmonic nanostructures, and 3) investigate the influence of IR CD activity of plasmonic structures on achiral molecules. Through these studies, the mechanisms for the molecule-plasmon coupling observed in the IR CD and VCD spectra of the nanostructures and molecules will be explored. The findings from these investigations will establish a foundation for PE-VCD for the analysis of chiral molecules. Graduate and undergraduate students will be broadly trained through the interdisciplinary research incorporating nanofabrication, materials characterization, optical studies, and simulations. The interdisciplinary nature of nanoscience also provides the foundation for education and outreach activities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-08

Sea level rise remains one of the most pressing and widespread risks of climate change. The West Antarctic Ice Sheet (WAIS), with an ice volume equivalent to 4.3 meters of sea-level rise, provides substantial uncertainty and may dominate sea-level changes in the near future. As climate changes, WAIS surface mass (the balance of snow added and snow lost) changes, which then drives a change in the flow of ice into the ocean. Both the surface mass balance and the shifts in ice flow into the ocean, alter sea level. To determine how climate change will impact WAIS contributions to sea-level changes, it is therefore critical to understand the atmospheric processes driving WAIS surface mass balance and ice flow. In particular, the ice sheet's response to surface mass balance is nonlinear, meaning small changes in weather patterns triggered by variations over the tropics may produce large changes in ice flow. It is therefore critical to assess how changes in climate at both low (e.g., tropics) and high (e.g., polar regions) latitudes combine to impact WAIS surface mass balance and ice flow, and the potential to cross tipping points that would result in rapid changes in sea level. This project will also leverage the existing University of Utah Masters of Science in Secondary School Teaching (MSSST) program, which supports motivated middle and high school teachers to earn an M.S. while still actively engaging in classroom teaching. This project addresses two primary research questions motivated by the need to improve our understanding of atmospheric forcing of WAIS surface mass balance and dynamic response: (1) What climate mechanisms generate interannual-to-multidecadal surface mass balance variability and trends in different sectors of WAIS? (2) How do climate-driven variations at multiple frequencies and spatially divergent trends in surface mass balance project onto ice sheet dynamics? We use a combination of multi-platform, spatially dense surface mass balance records, two century-length climate reanalyses, and climate and glacier numerical modeling to address these two questions. The observational work will use multivariate statistical methods to identify internal versus tropically-forced modes of climate variability relevant to spatiotemporal variations in SMB across WAIS, leveraging spatially dense surface mass balance records from cores and radar in conjunction with multiple century-length climate and sea surface temperature data sets. The resulting hypotheses of climate driver causality will then be tested by conducting boundary-forcing experiments with a global atmospheric model. Finally, the response of ice sheet dynamics to the spectrum of climate forcing from the observational and atmospheric model results will be investigated using a hierarchy of numerical ice sheet models. Ultimately, this work will deconvolve the role of tropical and intrinsic climate variability and trends on the dynamic response of WAIS to SMB variance and trends and how that varies across different regions of WAIS. The results will point directly to the climate mechanisms most likely to significantly influence ice sheet SMB and dynamics in the coming decades to centuries. 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

Scientific discovery is increasingly driven by massive, complex datasets that hold the keys to unlocking new knowledge and solving global challenges. However, the current landscape of data storage and management is struggling to keep pace with this data deluge. IOWarp is designed to create a next-generation data management platform tailored to the unique needs of modern, data-intensive science. This platform will address the fundamental challenges that researchers face when dealing with diverse data types, the exponential growth of data, and the need for rapid access to critical information. By streamlining data workflows and enhancing data accessibility, IOWarp will empower scientists and researchers to focus their valuable time and resources on their core mission: making groundbreaking discoveries. Beyond its technical advancements, IOWarp will also foster a collaborative and inclusive research environment, democratizing access to data and equipping the next generation of scientists with essential data skills. By accelerating research in critical fields like genomics, climate modeling, and AI-driven discovery, IOWarp has the potential to unlock transformative solutions to global challenges and drive innovation. The IOWarp project will engineer a modular, adaptable, and scalable data management platform that addresses the specific challenges encountered in modern scientific workflows, particularly those enhanced by artificial intelligence (AI) technologies. IOWarp will significantly reduce data access times, accelerating the pace of scientific discovery by harnessing state-of-the-art technologies like NVMe SSDs, CXL devices, and CPU-GPU codesigns. It will foster a collaborative ecosystem, inviting contributions from diverse scientific and engineering communities. Building upon the team's extensive expertise in multi-tiered storage research and leveraging prior NSF investments in this field, IOWarp will integrate AI-driven solutions to redefine data management for high-performance computing environments. The anticipated outcomes of IOWarp will establish a thriving community-driven platform that continually evolves to meet the changing needs of scientific 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 · 2024-08

Two and three-dimensional spaces are fundamental objects lying at the intersection of many branches of mathematics. One approach to studying these spaces is to endow them with geometric structure and then use the geometry to study the spaces. The three most familiar geometries are the classical Euclidean or flat geometry, and the two non-Euclidean geometries: spherical and hyperbolic. It has been known since the late 1800s that most two-dimensional spaces (or surfaces) exhibit hyperbolic geometry. Thurston's groundbreaking work in the 1970s showed that "most" three dimensional spaces (or three-manifolds) also have hyperbolic geometry. The rich landscape of hyperbolic manifolds in two and three dimensions motivates this project's focus on hyperbolic geometry. The project will include many sub-projects suitable for training graduate students to work in this area. The PI, together with graduate students, will study questions around the geometry of hyperbolic 3-manifolds. One central topic will be the "renormalized volume" of a hyperbolic 3-manifold, and the connection between the Weil-Petersson gradient flow and the volume of the convex core. While renormalized volume has strong connections to physics, in this project the focus will be mathematical. The PI will study a version of renormalized volume of the universal Teichmüller space, and Thurston's skinning map. In another series of projects, the PI will study a family of curve complexes that interpolates between the usual curve graph and a quasi-tree, and will investigate the existence of actions of the mapping class group on median spaces and CAT(0) cube complexes. 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 nation’s ever-increasing reliance on wireless and mobile networks and the next generation technologies that will enable them are national economic and strategic concerns. However, the workforce needed to innovate and develop these technologies is lagging. The recently published National Spectrum Strategy from the National Telecommunications and Information Administration of the United States Department of Commerce articulates the importance of real-world wireless cyberinfrastructure (CI) for education and research and calls out the need for training the “spectrum ecosystem workforce”. CyberPowder is a wireless networking CI program to develop educational material and provide training on the NSF-funded POWDER platform to address these concerns. CyberPowder broadens and democratizes the use and adoption of wireless networking cyberinfrastructure and provides research training for the wireless research community. CyberPowder directly improves wireless communication and networking education, which has been siloed into two non-overlapping disciplines of electrical engineering and computer science. By broadly disseminating curricula and training material, both through online means and via academic publication, and by training instructors at diverse academic institutions across the United States, CyberPowder influences how wireless is taught. The program democratizes access to wireless networking cyberinfrastructure by ensuring that cohort training recruitment casts a wide net, which specifically includes a broad range of universities, including minority-serving institutions. CyberPowder runs a train-the-trainer program and offers to co-teach hands-on labs on the POWDER CI. By broadening wireless training, CyberPowder better prepares the nation for cross-disciplinary, next generation research and technology advancement. CyberPowder develops wireless networking content and training material for both classroom teaching and hands-on cyberinfrastructure training. Classroom teaching focuses on developing and teaching curricula that address the inherent multi-disciplinary nature of wireless networking by co-teaching material that is traditionally siloed in either the computer science or electrical engineering disciplines. CyberPowder’s cyberinfrastructure training follows a novel cohort approach that combines online and in-person, research-focused training on the POWDER platform, followed by structured research support involving both the trainees and their faculty advisors. The cyberinfrastructure training program provides training on the use of wireless networking and experimental research fundamentals as well as specific advanced wireless technologies. To complete the process of enabling students to become researchers who produce high-quality, reproducible work, CyberPowder develops and promotes an artifact evaluation support program by working with relevant conferences to promote experimental research in the wireless networking community. An external evaluator, with research expertise specifically in the design and assessment of research training, evaluates and helps improve the CyberPowder program. This award by the Office of Advanced Cyberinfrastructure is jointly supported by the Division of Computer and Network Systems within the Directorate for Computer and Information Science and 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 · 2024-08

This award supports a new research initiative, which will use the techniques of numerical relativity to model black hole formation and explore possible consequences for astrophysical observations. This effort is complementary to the work of a recently formed Utah LIGO group, and will enhance collaboration with gravitational researchers both within and external to the University of Utah. The work will be carried out by the PI in conjunction with both graduate and undergraduate students, as problems in numerical relativity are excellent training grounds in both modern physics research and state-of-the-art computational techniques. The PI will continue to maintain an affiliation with departmental outreach programs that conduct direct outreach in rural schools in Utah and Montana. The observation of gravitational waves by the LIGO and VIRGO interferometers is among the greatest scientific achievements of the twenty-first century, simultaneously confirming one of Einstein's most elusive predictions and opening a new window into the study of astrophysical processes. At the same time, these successes created new motivation to probe the foundations of General Relativity, which is known to be an incomplete picture of nature. In most cases of interest, it is necessary to bring the techniques of numerical relativity to bear on the simultaneous solution of ten independent Einstein equations in four-dimensional spacetime. These solutions may either predict observations or serve as a laboratory for "thought experiments" in which exotic spacetimes are tested to understand the limitations of the theory. One such laboratory is the study of critical phenomena that occur in spacetimes near the black hole creation threshold. Previous work by the Utah Numerical Relativity group has focused on competing critical collapse of scalar fields in spherical symmetry, in which the interplay between several stress-energy sources may tend to enhance or frustrate the collapse of the system. Under this award, the group will extend these studies to axisymmetric systems to test whether the competing collapse phenomenon persists in more generic systems, and if so, what the consequences might be for primordial black hole formation and other observables. In a related parallel effort, we are applying new computational techniques to the historically difficult problem of the collapse of vacuum gravitational waves. 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 goal of this project is to investigate little-understood mechanisms that lead to many severe injuries during earthquakes to support the development of new, effective interventions to reduce seismic risks. Through this investigation, this project aims to utilize new engineering models to capture the critical injury mechanisms and interactions between humans and infrastructure during earthquakes at fine scales in space and time, focusing on predicting earthquake impacts on health and life. This research has the potential to inform policymaking to design effective hard and soft interventions to protect many communities living in vulnerable buildings close to active seismic areas, like in Los Angeles or the Bay Area, California. In addition, the project offers opportunities for PhD training in interdisciplinary methods in engineering and disaster medicine and a broad dissemination of results to scientists and policymakers. The project embraces equity, diversity, belonging, and inclusion in the research design, recruitment of students, training, and teaching plan. This project integrates civil engineering and disaster medicine concepts, measures, and methods to develop next-generation earthquake casualty models that are more fine-grained and accurate. The novel measures and models will support the design and assessment of novel interventions to reduce risks to health and life. First, the project augments the spatiotemporal granularity of traditionally coarse damage assessments of infrastructure failures to reflect more types of physical mechanisms that lead to earthquake injuries. This part of the project employs both numerical experiments and empirical damage observations of structural and non-structural components. Second, the research elevates the granularity of earthquake injury modeling to predict medical diagnoses and needs rather than just severities, building on a new, more refined taxonomy of earthquake injuries. This part of the project will employ two validated methods to collect granular injury data from experts and field investigations in communities affected by the 2023 Turkey Earthquake. Third, the project will include creation of a hyper-resolution agent-based model coupled with a building dynamics model to explore the effectiveness of hard (e.g., building retrofits) and soft (e.g., earthquake early warning) interventions to reduce injury risks for diverse buildings and populations. Overall, this project distills technical insights for seismic risk reduction, focusing on health and life. The findings will yield insights relevant to communities residing and working in non-ductile concrete frame buildings in the Bay Area, California. 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

Legal pluralism, the coexistence of multiple legal systems within one society, is practiced in more than forty countries worldwide, often where customary law coexists with legal systems transplanted during colonization. Customary law courts generally address local issues such as marriage, land rights, inheritance, and inter-group conflicts. They tend to emphasize community participation and apply informal, dispute resolution processes that yield restorative decisions designed to support and heal individuals and communities. By contrast, formal courts (often based on Western legal traditions) employ official processes, focus on individuals, and emphasize retributive justice. These courts are intended to anchor a unified state legal system that serves governance, business development, and ties to the global community, If not well managed, the coexistence of multiple legal options can produce contradiction, uncertainty, and institutional weakness and can disadvantage the livelihoods of individuals and communities. The scientific study of legal pluralism, as exemplified in this project, identifies the advantages and limitations of legal pluralism by documenting and collaboratively developing customary law in relation to a state system. The case study model produced through this research illuminates how customary law’s guiding principles might underpin a legal system built on both longstanding customary practices and globally-recognized essential rights. The findings inform efforts to combine informal and formal legal options effectively in many contexts of legal pluralism, including the United States, where efforts to incorporate restorative justice options into the formal, retributive-based system are ongoing. This project expands on an ethnographic study of customary courts initiated in 2008 in response to an official call for increased reliance on customary law. One intended aim was to address violence and lawlessness in a locally-relevant manner. The research team will observe and document court cases in multiple contexts, including a formal District Court, to establish a database recording the application and adaptation of customary law across one local area. The database will be used to develop and refine theories of legal pluralism, including the challenges of facilitating collaboration between different legal systems, when one employs restorative justice and the other retributive justice. The research team includes locally-based formal and customary law experts, and the research design includes participatory opportunities for local collaboration in data analysis, including by sitting magistrates. Finally, the efficacy of customary courts for establishing peace after communal warfare with contemporary weapons will be investigated by monitoring peace negotiations and their incorporation of customary principles. An important product of these efforts will be a guidebook to customary law to be used to train new customary court magistrates and provide a resource for formal court personnel, law enforcement personnel, public servants and students and a model for such guidebooks for other contexts. Results of the in-depth study of this initiative will be relevant to the challenges of developing effective systems of legal pluralism in other nations worldwide. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-07

This project aims to serve the strategic national interests of the United States by training a highly skilled domestic workforce to meet the current and future technological needs of the semiconductor industry. As delineated by the 2022 Chips act, building and sustaining a skilled and diverse workforce is critical to America’s leadership in semiconductors. The University of Utah through a partnership between academia and industry aims therefore to develop and deploy a hands-on semiconductor training program “Semiconductor Manufacturing Program” breaking the accessibility barrier to expensive manufacturing training facilities for broader communities including ones with limited resources. The project ultimately will bridge the skills gap and enhance employability by providing hands-on experiences in state-of-the-art facilities. The program emphasizes diversity and equitable access to training opportunities through a pilot partnership. Through a cohort-based training model, the program will equip participants with the knowledge and skills vital for semiconductor manufacturing, fostering employment in the industrial sector. The instructional approach incorporates three key components: a customized curriculum focused on semiconductor manufacturing and characterization, hands-on experiential learning, and interaction with industry. Theoretical learning is aided by virtual tools and complemented by hands-on experiences. Collaboration between industry and academia constitutes the backbone of the program, ensuring alignment with industry needs and trends. Continuous monitoring of student and employer outcomes will inform program adjustments, with dissemination of lessons learned enriching semiconductor education not only nationally but also globally. Ultimately, this program strives to cultivate a job-ready workforce while contributing to the collective advancement of semiconductor education. 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

Ensuring environmental sustainability is one of the United Nation’s millennium development goals and this includes reducing the population without sustainable access to safe drinking water. Groundwater is the largest reservoir of usable fresh water on earth, but rates of movement and fluxes are typically small, extraordinarily variable, and poorly defined for most aquifers. Age dating groundwater has proven to be an exceptional tool for characterizing groundwater systems from both water resources and water quality perspectives. The age of a groundwater sample collected at a point in space contains information regarding the upstream velocity field and thus serves as a critical calibration target for numerical models of groundwater flow. Mean groundwater ages are related to the ratio of storage to recharge, two of the most fundamental parameters for evaluating water resources. A key goal of this project is to promote a better understanding of groundwater flow system (vulnerability to contamination and sustainability of groundwater resources) using environmental tracers. The equipment provided by this grant (sector-field and quadrupole mass spectrometers) will facilitate the continued characterization of groundwater systems by the more than 140 institutions which have previously utilized the noble gas laboratory at the University of Utah. The proposed project is to upgrade the noble gas laboratory by replacing a 30-year-old mass spectrometer in support of hydrologic and geologic research. Noble gases dissolved in water have been used for age dating groundwater, provenance studies, and thermometry along with surface exposure dating of minerals. This mass spectrometer acquisition will support hydrologic studies, such as those previously completed like characterization associated hazardous waste disposal in clay-rich aquitards, the evaluation of cap rock seals associated with carbon capture and storage (CCS), thermometry and age dating associated with aquifer characterization, and the transit time distribution of baseflow and streams. It would also indirectly support geomorphic studies that utilize exposure age dating. The major broader impact of this grant supports water sample analysis to partner institutions and to train visiting scientists at the noble gas laboratory. 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

A traditional dynamical system is a time lapse of a space that describes the motion of points. The time lapse can be in a single, discrete time step or a continuous time flow. One natural way in which dynamical systems can be considered the same, called conjugacy, is through change of coordinates. That is, two dynamical systems are conjugate if there is an equivalence between the spaces which connects the way in which time steps are made. One of the central classification questions in dynamics is to classify dynamical systems up to conjugacy. This question has variations based on what it means for two systems to be equivalent, usually taking the forms of measurable, continuous and smooth equivalences. The goal of the proposal is to study the classification question from various perspectives, including generalizing the notion of a dynamical system to a group action, understanding possible values for conjugacy invariants and relaxing the notion of conjugacy to allow for time reparameterization. The proposal also includes work with students at various levels to deepen the collective understanding. The proposal aims to capitalize on momentum in 3 key areas: smooth rigidity for actions of abelian groups and higher-rank semisimple Lie groups, Kakutani equivalence for flows and group actions, and flexibility for conjugacy invariants. Each of these questions is related to a classification question, the first working toward the Katok-Spatzier conjecture and Zimmer program, the second being an extension of results about Kakutani equivalence of parabolic flows to the setting of abelian group actions, and the third being a natural extension of the seminal work of Erchonko-Katok describing the possible values for topological and metric entropy for geodesic flows on surfaces. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-07

This project aims to build a workbench for scientists and engineers to address numerical issues in real-world applications. Numerical issues are issues caused by the gap between mathematical (real) numbers and the number representations used on computers, like floating point. Ultimately, this gap makes it difficult for scientists and engineers to develop software that does numerical computation accurately and runs reliably and efficiently on a variety of hardware and software platforms. Over the years, the research community has studied these issues and developed a number of tools that make developing numerical software easier, but these tools have become difficult to use together. In this project, the investigators will develop a set of standards, benchmarks, and user interfaces to make these existing tools interoperable and thus easier to use in concert. The project’s novelties are a set of standards where floating-point computations can be connected to the hardware and software platforms they run on, along with observed bad inputs or bugs. The project’s impacts are its potential improvements to real-world software packages, making them faster and more reliable across a wide range of hardware and software. Additionally, the investigators plan a variety of community-building initiatives including a community meeting, workshops, and REUs to build further ties within the numerical research community and between that community and practitioners in industry, national laboratories, and academia. The project builds on the existing FPBench standardization and interoperability effort. That standardization effort largely focuses on unambiguously describing floating-point computations, but real-world numerical workflows must track much more information: representative inputs; platform characteristics; pointers into codebases; and error bounds, observed or proven. This project will extend the FPBench standard with new formats to record and transmit this additional information, and update a variety of existing, widely-used numerical tools to use the new format. The investigators will then collect more benchmarks from real-world applications, recording rich metadata descriptions using the new formats, and distribute the extended tools and new benchmarks. To tie these standards, tools, and benchmarks together, the investigators will develop a novel, task-oriented user interface for scientists and engineers dealing with numerical issues. This interface will dispatch individual tools and collect the information they generate (in the new standard formats) in a single database, transparently passing the necessary information to every tool and informing the user when running additional tools would be useful. 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 · 2024-06

The goal of this project is to build and evaluate a system for exploring how the human brain processes information in everyday real-world environments. The investigators will directly record from the brain while participants navigate the real world, while synchronously recording information about the participant's first-person experience from a set of sensors including cameras, microphones, eye-tracking, and physiological recordings. Neurosurgical participants with a clinically implanted neural recording and stimulation system volunteer for these experiments, providing rare direct human brain recordings as they move around a real-world environment. The rich sensor data captured from the participant's first-person experience will be analyzed in relation to the neural data to infer how changes in patterns of neural activity over time relate to changes in experience. In addition, stimulation will be applied, at safe levels and timed according to "event boundaries" of the participant's experience, to determine whether memories of specific events can be enhanced. The proposed platform that allows for neural recording, direct brain stimulation, and synchronization with external, wearable devices will open an entirely new area of research at the intersection of computer science, engineering, cognition, and clinical neuroscience. These studies will launch and accelerate an emerging and pivotal area of research that will provide therapeutic interventions, proven in the real-world, for participants afflicted with debilitating cognitive disorders. This project will also make substantial contributions to education and outreach, including the development of K-12 classroom modules, interdisciplinary graduate training, outreach to industry partners in the neuromodulation field, and workshops at local Salt Lake City memory care communities. Development of this neural and first-person experience recording system will entail three collaborative research tasks: i) Synchronizing the Human Experience Relative to Neuronal Events: This module will develop a robust framework to record and synchronize neuronal activity along with internet of things (IoT) sensor data representing a broad subset of human sensory channels. The design will be portable such that the human experience can be reasoned about outside of a simulated lab environment. ii) Real-time Semantic Alignment between Human and IoT Perception: Reasoning about the complex relationships between neural biomarkers and the human experience captured by IoT sensing requires more than sensor synchronization. Neural-symbolic approaches that integrate the perception capabilities of deep learning with human logic will be leveraged to reason about the high-level complex spatiotemporal dependencies across a heterogeneous set of sensors. iii) Enhancing Episodic Memories of Real-world Experiences with DBS: Given a proper characterization of neural oscillations associated with event boundaries, the investigators will work to enhance episodic memories of real-world experiences with wireless deep brain stimulation (DBS) devices by directly stimulating the human brain. Under medical supervision, stimulation will be applied to the human amygdala at and between event boundaries in subjects with implanted stimulation devices as they encounter novel, 3D augmented reality objects while navigating a large-scale, real-world environment. Memory will be subsequently tested in laboratory and real-world settings. These three research areas will develop a situational understanding of neuronal activity in the context of human experience. They will further lay the foundation for future research directions in safe and effective stimulation of the brain in response to human experience in the wild. 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.

Other NSERC · FY 2024

asymmetric catalysis, data science, physical organic chemistry, catalyst design, chiral phosphoric acids, statistical modelling, reaction mechanism, enantioselective, click chemistry, computational chemistry