William Marsh Rice University

NSF Awards · FY 2024 · 2024-09

The study of the social and cultural impacts of invasive species on global biodiversity is an important area of study in conservation biology and environmental anthropology. Understanding these impacts to manage and control invasive species requires the development of new scientific knowledge and environmental policies. This doctoral dissertation research examines the various ways that environmental public policy responds to the management of invasive species. In addition to training a graduate student in scientific data collection, the research will impact policy related to conservation and environmental management. In order to test the strength of the relationship between environmental policy and management of species, the investigators use qualitative methods such as participant observation, semi-structured interviews, focus groups, and archival research. The research tests for various factors and focuses on several stakeholders such as agriculturalists, scientists, policymakers, and conservationists involved in environmental management and policy. The research makes significant contributions to environmental anthropology, cultural and rural geography, conservation science, and science and technology studies. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This project was in response to a NSF-DFG German Research Foundation partnership. The partners are Rice University and Justus Liebig University Giessen in Germany. This project aims to advance fundamental understanding of the chemical processes occurring at the interfaces within next-generation all-solid-state batteries. These promising battery technologies have the potential for higher energy densities and enhanced safety compared to conventional lithium-ion batteries with organic liquid electrolytes. However, their performance is critically dependent on the properties of the solid-state electrolyte and its interfaces with the electrodes. By developing cutting-edge surface analysis methods to study these interfacial regions during battery cycling, this research project will provide unprecedented molecular-level insights into the degradation mechanisms that currently limit solid-state battery lifetimes. These scientific advances will help guide the rational design of optimized materials and architectures to enable widespread commercialization for applications ranging from electric vehicles to grid storage. The project fosters international research collaboration, provides interdisciplinary training for the next generation of scientists/engineers, and engages underrepresented groups in energy research through targeted outreach efforts. This project will develop and apply advanced time-of-flight secondary ion mass spectrometry (ToF-SIMS) methods to characterize solid-solid interfaces in all solid-state battery materials during operando electrochemical cycling. The focus is on a NMC (nickel, manganese, cobalt) cathode, sulfide-based electrolyte, and a silicon anode. Integrated electrochemical cells will be designed to enable operando ToF-SIMS mapping of the evolving solid-electrolyte interphase chemistry. Labeling studies will probe lithium transport pathways. Benchmarking will be performed against post-mortem analysis and molecular dynamics simulations. Machine learning algorithms will be applied to correlate the ToF-SIMS spectral features to degradation processes and capacity fade. This combined experimental and computational approach provides a multi-scale view spanning from molecular mechanisms to bulk performance losses. Expected outcomes include elucidating the impact of surface coatings and binders, particle sizes, current densities and other factors on interfacial stability. This foundational knowledge will guide strategies like interfacial engineering to mitigate issues like dendrite growth, mechanical cracking, and resistive film formation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This award funds the research activities of Professor Andrew J. Long at Rice University. Whereas the Standard Model of the Elementary Particles has been unerringly successful at describing the properties of the known elementary particles and the forces by which they interact, a combination of cosmological and astrophysical observations furnish overwhelming evidence that New Physics is at play in the fundamental laws of nature. The phenomena of dark matter, cosmic inflation, and the excess of matter over antimatter cannot be explained within the framework of the Standard Model. Candidate theories include the well-studied axion and dark photon, which are being targeted by experimental campaigns in laboratories on Earth. At the same time, it is important to seek out these new particles and forces through their possible manifestations in the cosmos, including the cosmic microwave background radiation, for example. Under this grant award, Professor Long will use the tools of quantum field theory and particle physics to make robust predictions for cosmological and astrophysical signatures of axion, dark photon, and other hypothetical new physics to strengthen the connection with ongoing (and bold, new) experimental activities. This research will advance the national interest by expanding the scope of human knowledge in an effort to better understand the fundamental constituents of nature. This grant award will provide the financial support for graduate student researchers at Rice University where Professor Long will supervise the training of these early-career physicists. In addition, Professor Long will deliver lectures at local high schools and invite students to visit his university’s campus in order to promote science literacy among the general public and to encourage the next generation of physicists. Some specific examples of the work to be performed include: deriving predictions for cosmic microwave background birefringence arising from axion strings and assessing the compatibility with data, developing an analytical model for string network dynamics and assessing the observational implications (e.g., gravitational waves), deriving predictions for the isocurvature associated with gravitationally-produced dark matter to assess the signatures of light spectators during inflation, and evaluating the impact of dark photon dark matter on small-scale structure formation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This National Science Foundation Research Traineeship (NRT) award to Rice University will advance the interdisciplinary field of cavity quantum electrodynamics (C-QED). C-QED integrates principles from quantum mechanics, photonics and materials science to explore and harness the unique interactions between light and matter enabled by micro- or nanoscopic cavities. The program will prepare a new generation of scientists and engineers to tackle complex problems, bridging fundamental research and applications based on quantum optical systems. The training program addresses a crucial need for highly skilled STEM professionals capable of leading innovations in quantum technologies. By providing interdisciplinary training to 150 graduate students, including 30 funded trainees from diverse fields across physics, materials science, and electrical engineering, this program will foster a comprehensive education for academic and industrial career opportunities. The traineeship aims to develop a versatile and diverse workforce equipped to drive advancements in quantum electrodynamics, including secure quantum communication, quantum materials, and nanoengineered photonic technologies, contributing to national security and economic competitiveness. The NRT program will implement a robust, integrative educational model combining coursework, hands-on research, and professional development. Central to this program is the 2:1:1 co-advisory model, pairing each trainee with two faculty mentors from different disciplines in Natural Sciences and Engineering. This structure promotes interdisciplinary collaboration and broad exposure to complementary research. The curriculum is tailored to include fundamental education (e.g., ‘Introduction to Quantum Information Science and Engineering’) and specialized courses (e.g., ‘Quantum Engineering of Nanomaterials for Energy Harvesting’) to provide students with thorough and far-reaching formative training. Research projects will be developed through a ‘problem-first’ approach where open questions are identified, and research challenges are tackled with a problem-solving mindset. The method is consistent with professional careers even beyond academia, where defined goals typically set the agenda for the work of scientists and engineers. To facilitate the students’ affiliation process, trainees will engage in rotational research groups, providing exposure to multiple research environments and helping them make informed decisions about their thesis topics. The program also includes extensive professional development components, including workshops in communication, leadership, and industry internships, ensuring that trainees are well-prepared for diverse career paths. By integrating research, education, and personal development, the program aims to educate graduates capable of making significant contributions to both academia and industry, ultimately driving innovation and technological advancement in the field of quantum science and engineering. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new potentially transformative models for STEM graduate education training. The program is dedicated to effective training of STEM graduate students in high priority interdisciplinary or convergent research areas through comprehensive traineeship models that are innovative, evidence-based, and aligned with changing workforce and research needs. 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

How do smallholder farmers approach novel digital agricultural technologies in the context of environmental change? In response to technologies ill-suited for small-scale, sustainable agriculture and the corporate consolidation of agricultural production, emerging networks of farmers, agronomists, engineers, and government actors are challenging the presumed superiority of industrial agricultural regimes through local innovation. Farmers are collaborating with university agronomists and government researchers to develop locally appropriate digital hardware and software, such as low-cost soil reflectometers and open-source farm management software, to bolster agroecological practices. This project analyzes how an emerging network of farmers and agrarian stakeholders seek to repurpose digital technology innovation as a grassroots endeavor to address their social, ecological, and economic goals. The project trains a graduate student in methods of scientific data collection and analysis and builds capacity for the future conduct of scientific research in this setting. The findings of this doctoral research project are shared with a wide range of stakeholders, to improve the public’s understanding of science and the scientific method. This research explores more socially accountable and ecologically oriented forms of innovation emerging from grassroots alliances that center small-scale farmers and agricultural communities. As a range of stakeholders compete to make claims about the value of agricultural technologies and the future of agri-food systems, the researcher asks what kinds of agricultural relations and futures are being imagined and created through grassroots technology innovation between farmers, agronomists, engineers, activists, and government actors, particularly in the context of changing climate conditions; and how small-scale farmers participate in and draw on multi-stakeholder alliances to generate new technologies. The research takes place at a site where extreme weather events, increasing temperatures, and loss of groundwater shape conditions for grassroots responses to food system challenges, and where local technology innovation intersects with agroecology and grassroots mobilization. Twelve months of fieldwork is being conducted at multiple sites where the researcher engages a range of actors, including farmers, agronomists, engineers, and government actors. Methods include participant observation, semi-structured interviews, and event ethnography. The findings of this research advances basic science within the fields of the anthropology of agriculture, digitalization, and socioenvironmental systems. 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 Earth’s radiation belts are a dynamic and complex plasma environment. Large amplitude waves can nonlinearly accelerate particles to energies high enough to pose a radiation hazard in the near-Earth space environment. These large amplitude waves are common but only occur in small regions for a short period of time. Therefore, it is unknown if such a drastic but localized acceleration can have an impact on a global scale. By modeling the nonlinear wave-particle interaction in a global scale radiation belt model, this research will conclusively show the importance of these large-scale waves on the whole space environment. The research will promote the development of two early-career researchers. Additionally, undergraduate students at a minority-serving institution will be trained as an integral part of this project. The physics of wave-particle interactions in the Earth’s radiation belts is well understood in the linear and quasilinear regimes, but large amplitude waves create a complex nonlinear problem. Significant theoretical and computational work has been done to understand how nonlinear wave-particle interactions can efficiently energize or pitch angle scatter high-energy electrons. As successful as local studies of nonlinear wave-particle interactions have been in explaining the micro-scale physics of a particle in a large amplitude wave, it has yet to be demonstrated that these nonlinear effects lead to global, macro-scale changes in the radiation belts. In this study, we will use theory, modeling, and data analysis to answer the fundamental science question: Do nonlinear wave-particle interactions affect the radiation belts on a global scale? This will be done by calculating advection and diffusion coefficients from nonlinear wave-particle interactions that can be directly included in the K2 radiation belt model. K2 is a global scale radiation belt model based on the stochastic differential equation (SDE) framework and accurately captures wave-particle interactions at an individual particle level. By simulating real events with K2, the sensitivity of the whole radiation belt system to localized large amplitude waves can be quantified. 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 is designed to extend the capabilities of tree-based models within the context of machine learning. Tree-based models allow for decision-making based on clear, interpretable rules and are widely adopted in diagnostic and learning tasks. This project will develop novel methodologies to enhance their robustness. Specifically, the research will integrate deep learning techniques with tree-based statistical methods to create models capable of processing complex, high-dimensional data from medical imaging, healthcare, and AI sectors. These advancements aim to significantly improve prediction and decision-making processes, enhancing efficiency and accuracy across a broad range of applications. The project also prioritizes inclusivity and education by integrating training components, thereby advancing scientific knowledge and disseminating results through publications and presentations. The proposed research leverages Bayesian hierarchies and transformation techniques on trees to develop models capable of managing complex transformations of input data. These models will be tailored to improve interpretability, scalability, and robustness, overcoming current limitations in non-parametric machine learning applications. The project will utilize hierarchical layered structures, where outputs from one tree serve as inputs to subsequent trees, forming network architectures that enhance precision in modeling complex data patterns and relationships. Bayesian techniques will be employed to effectively quantify uncertainty and create ensembles, providing reliable predictions essential for critical offline prediction and real-time decision-making processes. This initiative aims to develop pipelines and set benchmarks for the application of tree-based models across diverse scientific and engineering disciplines. 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 heavy isotopes deuterium (D), a form of hydrogen in which the nucleus has a neutron as well a a proton, and oxygen-18 (18O), a form of oxygen with two extra neutrons, are found in trace amounts in all water on Earth. These isotopes are of interest for two reasons: first, the heavier water molecules formed from them, with formulas HDO and H2(18O) instead of H2O, evaporate more sluggishly and condense more readily than ordinary water, and the differences in evaporation and condensation depend on temperature. The relative abundances of the heavier forms of water thus contain valuable information about the climatic conditions encountered by water along its journey through the hydrological cycle. Second, the heavier isotopes are stable, so their record of climatic conditions lasts essentially forever and can be used to track the water cycle over periods from days to millennia. The heavier isotopes of water can be measured in ice cores over multiple ice ages, and isotopic abundances present in rainfall long ago can be determined from tree rings, speleothems (the stalactites and stalagmites found in limestone caves), and even fossil corals. But the climatic record encoded in the heavier water isotopes has not been used to its full potential for a variety of reasons, chief among them the lack of easy access to isotope data in a standardized format, covering both present-day measurements and paleoclimate proxies. Another is a lack of isotope-enabled climate and earth system models that can be used to interpret the isotope record. Coordinated modeling efforts in which isotopic effects are represented consistently across an ensemble of models can be extremely valuable for relating isotopic abundances to specific climatic effects. For example it would be difficult to determine based purely on observations whether depletion of heavy isotopes in ice cores is a consequence of warmer temperatures in the source region where the water evaporated or a consequence of rainout as the water vapor traveled from the source region to the ice sheet. Such distinctions can easily be made in model simulations, but guidance from models is most trustworthy when several models are used and they all handle isotopes in a consistent manner. Work performed here addresses the data access barrier through the creation of the Water Isotopes and Climate Network (WISONet), a research platform that provides seamless access to modern isotope observations and paleoclimate proxy data. Present-day isotope data includes in-situ measurements of rainwater isotopic composition, in-situ measurements of water vapor isotopic composition, and estimates of water vapor isotopes based on satellite data (for instance HDO retrievals from AIRS, the Atmospheric Infrared Sounder). The paleoclimate proxies mentioned above are also included, along with relevant paleoclimate reconstructions covering the last two millenia (the project builds on the earlier Iso2k effort). As for isotope-enabled model simulations, the project supports the Stable Water Isotope Intercomparison Group version 3 (SWING3), a coordinated effort to generate a database of simulations for the period 1000 to 2100 CE using consistently isotope-enabled models (typically the atmospheric component models of earth system models). The resources of WISONet and SWING3 are used to address questions related to the climate sensitivity of the earth (the amount of warming caused by a doubling of carbon dioxide) and the response of the east-west tropical overturning circulation to warming and cooling. Other research focuses on the extent to which water isotopes can be used to infer changes in climate processes, for instance whether they can be used to infer the extent of vertical mixing from the ocean surface to the atmosphere above the planetary boundary layer. The educational component of this CAREER award includes efforts to teach climate and hydrological science to audiences including students in the Houston Independent School District (HISD), the Girl Scouts of San Jacinto Council (GSSJC), students at Rice University, and the general public. The Principal Investigator (PI) works with 11-15 HISD high school teachers to develop lessons related to climate science and the water cycle. Through this award the PI organizes an annual Girl Scout Climate Challenge Event at Rice, attended by over 100 Girl Scouts. As for on-campus activity, the award supports the addition of labs and field trips to the PI's climate science classes. For instance Longhorn Caverns is a venue where students can learn about speleothems and their use as a paleoclimate proxy. Finally, the PI engages with the general public by managing the development of rooftop rainwater collectors which can be deployed and maintained by interested members of the public. The rainwater collectors are designed to collect rainwater samples during intense storms and properly store the samples so that their isotopic composition is preserved for later measurement. 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

Energy experts have been advocating for green hydrogen as an alternative to fossil fuels and a means to decarbonize heavily polluting industries. While green hydrogen is situated as part of global energy transition and climate mitigation processes, it is also guided by financial, geopolitical, and geoeconomic logics. Investigating how hydrogen projects are imagined and developed improves our understanding of how energy transition and climate mitigation are directed and how financial industries and geopolitical and geoeconomic relations inform them. This doctoral dissertation research project examines how experts situate this hydrogen technology within the broader context of energy transition and climate mitigation. The project trains a graduate student in methods of scientific data collection and analysis and builds capacity for the future conduct of scientific research in this setting. The findings of this doctoral research project are shared with a wide range of stakeholders, to improve the public’s understanding of science and the scientific method. This project examines the relationship between energy transitions, speculative financial investment, and the transformation of geoeconomic relations. The researcher asks how policymakers, energy researchers, non-governmental organizations, and communities adjacent to hydrogen projects envision the impact of these projects; how financiers assess risk and opportunity in these projects; and what impact engineers and energy experts see hydrogen development having at different stages of the development process. The research takes place at a site where hydrogen development has rapidly emerged as a potential solution to regional decarbonization efforts. The research consists of a year of fieldwork at three sites, each representing a stage in the developmental chain (scoping, design, and implementation) for hydrogen technology. Methods include participant observation, semi-structured interviews, event ethnography, and document analysis. The findings of this research advance basic science within the fields of the anthropology of energy, social studies of climate finance, and anthropology of infrastructure and geopolitics. 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

Non-technical abstract: In order to make the next generation of computers more energy efficient, new materials that can replace copper wires and silicon chips need to be discovered. One class of candidate materials are those envisioned to constitute spin-based electronic or "spintronic" devices. This project studies spin and lattice properties of two-dimensional magnetic materials potentially relevant for spintronics applications. The research team uses a highly technical experimental capability available at national labs to shoot neutrons at materials and detect the quanta of energy and momenta absorbed, a process called neutron scattering. Because neutrons do not have a charge but carry spin, the way that they scatter provides unprecedented insight into magnetic properties of materials. In addition to potential technological applications, the project provides deeper insight into the fundamental nature of magnetism in condensed matter systems. Broader impacts of this program will include training of graduate students, particularly women and historically under-represented minorities, and hosting undergraduate and high school students during the summer. Technical abstract: Two dimensional (2D) magnetism plays an important role in many exotic condensed matter phenomena like quantum spin liquids, anyons, topological magnetic excitations, and high-temperature superconductivity. For both fundamental understanding and practical applications of 2D magnetism, it is important to determine magnetic orders and interactions that govern the ground states and spin dynamics of these materials. This project involves an innovative experimental program that integrates national lab based neutron scattering experiments with single crystal synthesis and characterization at the principle investigator's lab to gain a fundamental understanding of the charge, spin, and lattice interactions in bulk 2D honeycomb and kagome lattice structure magnetic materials. The project provides training of young scientists at the graduate and post-graduate levels, strategically coupled with a concentrated under-represented minority recruitment component created with collaborators at Prairie View A&M University. 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 the 2024 edition of the Seminar on Stochastic Processes, held March 13-16, 2024 at Rice University. This annual meeting has had tremendous impact on the probability community since its inception in 1981, both in North America and internationally. The conference brings together a diverse group of accomplished and early-career researchers and graduate students working in the field of probability and stochastic processes. There are five invited speakers, delivering three plenary lectures and two distinguished plenary lectures known as the “SSP Founders lecture” and the “IMS Medallion lecture”, and one tutorial speaker. There are two poster sessions with brief introductory talks, two open problem discussion sessions and a panel session on career development. The conference provides all the participants an opportunity to interact and discuss recent advances in probability theory and stochastic processes, and their applications. As such, the conference represents an important networking opportunity for the many dozens of early-career researchers in attendance and it will enhance the careers of the next generation of researchers in stochastic processes. The scientific committee has chosen invited speakers who represent a wide breadth of research areas in probability and stochastic processes, including stochastic analysis, stochastic partial differential equations, backward stochastic differential equations, discrete probability, mathematical finance, stochastic geometry, and mathematical physics. The topics also cover a wide range of application areas including biology, data science, physics and epidemiology. Recent research work by other participants is presented at poster sessions. The open problem sessions provide opportunities for discussions about emerging and challenging topics in probability and stochastic processes and the formation of future collaborations. https://ssp2024.rice.edu/ 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

To maximize scientific contributions in the field of legislative studies, this project creates a new initiative with the mission to engage, support, and promote the study of legislative politics across gender and sub-disciplinary divides. The initiative hosts virtual events monthly throughout the year, a professional development seminar, a research seminar, and a writing group, an in-person annual conference. The project also maintains a website and listserve with over 550 members and promotes women’s research via social media. Additionally, the initiative collects/analyzes data on women in legislative studies. This project seeks to bring new research and perspectives to scholarship on legislative politics by promoting the study of legislative politics across gender and sub-disciplinary divides. The initiative focuses on the research being done by a diverse set of scholars studying legislatures around the world. One of the aims of the project is to bridge the gap across the study of individual legislatures and the study of legislatures in comparative perspective. Bringing together a diverse set of scholars of legislative politics will encourage intellectual contributions that bridge these subfields. The initiative hosts virtual events monthly throughout the year, a professional development seminar, a research seminar, and a writing group, an in-person annual conference. The project also maintains a website and listserve with over 550 members and promotes women’s research via social media. Additionally, the initiative collects/analyzes data on women in legislative studies. 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 aims to improve the understanding of how the amount of disorder present in an environment can promote or suppress transport in a system. This issue is studied in the context of quantum mechanics at the atomic level. Applications of new insights about quantum systems include the development of quantum computing devices and quantum algorithms. The project supports education and diversity though the mentoring of postdoctoral scholars, the training of graduate students, and the supervision of undergraduate research. This project addresses the general theory of Schrödinger operators with ergodic potentials. These operators are relevant in many areas, primarily in quantum mechanics and approximation theory. The objective is to establish results for general base transformations and for large classes of sampling functions. The methods employed range from functional analysis via harmonic analysis to dynamical systems and ergodic theory. The investigator seeks to identify the almost sure spectral type of an ergodic family of Schrödinger operators, while establishing a version of Simon's Wonderland Theorem in this setting and answering a question of Walters about the existence of non-uniform cocycles as byproducts, to develop further gap labelling theory based on the Schwartzman group, along with a comparison with gap labelling based on K-theory, to study the Laplacian on Penrose and other aperiodically ordered tilings, and to obtain proofs of Cantor spectra via cocycle perturbation techniques beyond the two-dimensional time-discrete setting. 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 doctoral dissertation project examines how the use of generative AI in the legal sector may transform legal expertise and reconfigure the positions of technical experts, legal professionals, and laypeople within the larger legal system. The novel data-driven AI solutions rely on identifying the stochastic patterns in existing legal data instead of encoded rules. For this reason, the conventions of AI-powered legal reasoning may deviate from human standards. Thus, large language models, such as ChatGPT, may significantly impact how specialized information is created and disseminated and how people access and make sense of it. While this project focuses on legal practice, its findings also contribute to developing a more profound, generalizable understating of the interactions between AI and established forms of expertise, informing legislative and policy-making efforts in the area of AI’s safety and its impact on various professions. Along with the training of graduate student, this project contributes to raising technology literacy around generative AI usage, especially in the context of the legal system. During a year of ethnographic fieldwork, the doctoral student examines how three groups of people interact with legal AI tools: (1) technical and legal experts developing legal AI; (2) legal professionals using AI at work; and (3) laypeople who may use AI while seeking legal advice. This allows the researcher to learn (1) what kinds of knowledge and expertise inform legal AI development and how the developers conceptualize successful legal AI tools; (2) what qualifies as legal work in the age of generative AI and who can perform it; and (3) how interactions with AI shape people’ expectations and strategies for engagement with the legal system. By answering these questions, this project contributes to the anthropological and socio-legal discussions around automation’s impact on labor and expertise, as well as technologies’ potential role in public governance. Simultaneously, this research contributes to developing the appropriate ethnographic approaches to conduct in-depth studies of AI systems. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-07

The magnetosphere is the region that surrounds the Earth, which is carved out by its magnetic field as it deflects the supersonic solar wind plasma around it. The solar wind is a major energy source for the magnetosphere that can lead to complex dynamics. One such dynamic is the magnetospheric substorm, a major system reconfiguration that results in an energy release in Earth's magnetosphere-ionosphere system. During a substorm, a large-scale current system is observed known as the substorm current wedge (SCW). This project's focus is to better understand the physical process that leads to the SCW. Another example of the complex behavior observed in the magnetosphere is the presence of sporadic fast flows, known as bursty bulk flows (BBFs). This project seeks to investigate if there is any connection between the formation of the SCW and BBFs. The project's successful outcome will lead to a better understanding of the Earth's magnetosphere and current systems. This project will support two early-career scientists. Results of the study will be conveyed to the public (including K-12 students) via education and public outreach eWorts in both the PI and Co-I's institutes, which will enhance public interest in space science. The research focuses on the substorm current wedge (SCW), which plays a crucial role in the energy release process within Earth's magnetosphere-ionosphere system. This research aims to explore the causes behind this asymmetry and investigate the validity of the collective wedgelet formation of a SCW. Specifically, the team suggested to answer the following questions: Q1. Do the thermal pressure asymmetries around DFBs result from an interplay between the meso and global scales? Q2. Which plasma populations contributed to the pressure asymmetry within the dipolarization front layer? Q3. Are the collective eWects of wedgelets consistent with a substorm current wedge? The team will use the Multiscale Atmosphere-Geospace Environment (MAGE) model, inertialized Rice Convection Model (RCM-I) numerical simulation, and THEMIS observations to achieve the science goals. The outcome of our studies will provide constructive information on the physics of the inner magnetosphere dipolarization process and advance our understanding of the nature of substorm current wedge formation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-07

The overall goals of this conference is to spotlight the kinds of research that disabled investigators are conducting, to highlight ways that disabilities can lead to innovation in research materials, methods, and findings, to discuss the kinds of accessibility challenges and systemic ableism faced by researchers with disabilities at every stage of the research process. The conference will also suggest ways to engage the scientific community in working to overcome challenges and to promote access, equity, and inclusion in fundamental research for disabled investigators. It will highlight both the excellent science that is done by investigators with disabilities, and the means by which excluded individuals may be better supported in STEM. The conference will improve collaboration within and across career stages, fields, and institutions, and between investigators with and without disabilities. This conference centers the work, perspectives, and lived experiences of researchers with disabilities, in order to initiate a focus in various scientific communities on increasing equitable participation of persons with disabilities in fundamental research. The conference will take place on July 10, 2024 at NSF headquarters in Alexandria, VA, in hybrid format to ensure maximal access to persons with disabilities. It will consist of two panels of 5 invited panelists each. All invited panelists are STEM researchers with various types of disabilities who work in a range of academic disciplines. The first panel seeks to spotlight examples of the kinds of research that disabled investigators are conducting. The second panel focuses on researchers with disabilities who are working on projects to specifically promote access, equity, and inclusion in STEM fields. These conversations will facilitate more inclusive and representative scholarship across disabilities, and will facilitate direct discussion with scientific communities, leadership, and staff. Community awareness and understanding should result in improved policies and opportunities for scientists with disabilities and the communities that engages with them. 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

Cellular wireless networks, such as fifth generation (5G) networks, are crucial for national economy and security. Next-generation networks, namely sixth generation (6G) and beyond, are envisioned to deliver much higher speeds and new services like city-scale perception. To invent the ideas that will enable next-generation networks, it is crucial that researchers can conduct novel experiments to test new ideas. This project will develop Houdini, a new flexible platform that allows researchers to mix-and-match different radio bands in unique ways for new experiments. Houdini will be designed to be flexible and programmable to support the unique needs of many different researchers. Project Houdini involves investigators from Rice University, University of California-San Diego, Northeastern University and University of Notre Dame. The project main thrusts are: 1) Houdini Mix-and-match Radio System: The project will develop open-access software-defined radio to simultaneously support multiple radio modules across different bands, 2) Houdini Software Stack: The project will develop a software framework to virtually bond multiple bands, and new open-source libraries to support research use cases in wireless networking, sensing, and imaging, and 3) Novel Dissemination Models: The project will support multiple models of platform access, including remote access, build-your-own and a rent-to-use model. Houdini will provide capabilities beyond existing platforms, and thereby empower the community to experimentally explore research in new directions in wireless networking, sensing and imaging. By building one platform that could address the needs of many research communities, the platform will also spur collaboration between diverse research communities. The project will develop course materials with hands-on tutorials and laboratory sessions, hold show-and-tell events, host a (remote) Genius bar and release novel datasets. The investigators will seek to involve students in research and learning activities. The Houdini project website will be https://houdini.rice.edu, which will host code, designs, user documentation and tutorials for the use of the platform. The project will ensure searchable, and well-organized documentation, including step-by-step multimedia enriched startup guides. The Houdini software, firmware, and hardware schematics will be hosted as public repositories on GitHub. New training modules will be developed to teach students the basics of developing communication, sensing and imaging applications using Houdini. We will design an open-source Houdini Data Recording Application Programming Interface to record real-world radio datasets in an easy and automated manner. 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 broader impact of this I-Corps project is the development of a novel, 2-in-1 technology that can absorb and destroy "forever chemicals". Current solutions on the market are expensive, energy and time intensive, hard to implement, and leave behind forever chemical-contaminated waste products, which results in risks of litigation and difficulties in complying with existing and upcoming regulations. The estimated market size for industries that use forever chemicals is over $4 billion, with potential for the market to grow to $6.5 billion by 2030. Since 2012, 6,000+ cases have been filed, with over $6 billion in liabilities for remediation. This technology helps address this problem providing an easy-to-implement system that requires less energy than all competing destruction technologies, helping manufacturers to stop polluting the communities they serve. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of a water treatment system that can continuously degrade forever chemicals with Ultraviolet light at room temperature in a single, continuous stream. The reactor contains organic-based adsorbent photocatalysts. These materials make excellent adsorbents due to their hierarchical porous structure that gives them extremely high surface areas. There has been no feasible method of mass producing these photocatalysts until now. This novel technology allows for the absorption of forever chemicals at room temperature for on-site degradation with minimal energy cost and no need for treatment of contaminated absorbent. This solution presents an advantage as most current technologies must destroy forever chemicals in a secondary step where the absorbent must be removed and disposed. 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.