University of Kansas Center for Research Inc

NSF Awards · FY 2025 · 2025-03

The proposed research will develop a new experimental technique, to selectively remove a specific protein in a cell, but only when this protein is attached to a specific, unique spot on a chromosome. Many genetic and biochemical methods of protein depletion are known, but all of them deplete protein throughout the cell. If one wishes to study how a DNA-binding protein does its job in a cell, these methods likewise will eliminate the protein whether or not it is bound anywhere on DNA. In contrast, the proposed technology will eliminate only those protein molecules that are bound to a specific region of interest. The project will provide training for up to four graduate students in the EPSCOR state of Kansas. The proposed novel method will involve tagging a protein of interest with an auxin-inducible degron (AID), which has been used before to rapidly deplete nearly all the protein target throughout any cell when the plant hormone auxin is added extraneously. If a protein has multiple functions within a cell, however, this depletion can have multiple direct and secondary effects. The proposed High Risk/High Reward research will conbine several genomic technologies in a novel way, to develop, first, a method to selectively deplete the chromatin-bound Rhino-Deadlock-Cutoff (RDC) complex at specific locus that flanks a transposable element insertion in Drosophila. Next, the method will be applied to human cells and extended to deplete specifically a complex of two interacted proteins, CTCF and cohesin, without affecting each of the proteins alone. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-03

This award is a continuation of a Research Experience for Undergraduates (REU) site at the University of Kansas with the objective of exposing ten undergraduate participants for 10 weeks per summer to research in the areas of astronomy, astroparticle physics, high energy theory, and condensed matter theory and experiment. The mentoring faculty of the Department of Physics and Astronomy at the University of Kansas have experience designing short-term research projects and including student results in publications. At the same time participants will increase their computing skills through a computational bootcamp during the first week, and develop professional skills such as scientific writing, presenting, and discussing results. Workshops to prepare students for graduate school are also included. This REU site will offer participating students, after completion of their research projects, the opportunity to attend a scientific conference and present their results. In addition, this REU will provide ethics training, including workshops on implicit bias, bystander intervention, and research ethics. The scientific activities will be supplemented with departmental social activities. Participant recruitment efforts will be national, but will provide a particular focus on students from smaller colleges in the Midwest. Applications will be evaluated holistically including both cognitive and non-cognitive assessments. A keystone outcome of this REU program is to have participating students present at national scientific conferences. This will broaden their exposure to the fields of physics and astronomy while increasing their visibility. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-02

This workshop will bring together members of the paleontology community to determine best practices for sharing and reusing published scientific data. This workshop will provide collaborative space to generate and exchange ideas and strategies, especially in today’s rapidly changing scientific publishing and data dissemination landscape, where emerging methods are increasing the amount of data that can be harvested from scientific papers. The workshop will focus on: 1) new approaches to data gathering to support and facilitate scientific research; 2) ways to ensure that researchers who contribute paleontological data, as well as the journals that publish it, receive proper credit and are supported and recognized for their work; 3) ways to ensure that data sources can be continually verified, modified, and updated; and 4) new and innovative ways to use these data to engage with the public. Workshop participants reflect the breadth of the field and include editors of paleontology journals, developers of fossil databases, and individuals and organizations involved with sharing scientific literature, collections, data, and educational resources online. Scientific publishing and data dissemination are changing rapidly with the development of new methods that extract high volumes of data from scientific papers. In paleontology, systematic publications contain extensive amounts of data that have not been previously culled. These systematic data are foundational to paleontology, and the publications represent invaluable repositories for several scientific disciplines. The workshop comprises plans to develop the most effective ideas and approaches to make these data resources and publications Findable, Accessible, Interoperable, and Reusable (FAIR) and to encourage community support for this effort. This workshop will convene editors of peer-reviewed journals, contributors to online data-sharing platforms, organizations sharing systematics literature online, and practitioners in systematics, collections digitization, and education. The specific aims of the workshop are to generate and share techniques and approaches to: 1) best enable the rapid collection of paleontological data from the literature to make data more broadly available to scientists and the public; 2) better ensure that authors and venues that publish these data be properly cited and credited; 3) develop methods to continually evaluate the veracity of the underlying data; and 4) better connect authors and publishers with those building and maintaining the databases to create a mutually supportive framework. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-02

Stress, or the location of prominence within a word, may be encoded and used differently across languages. Second language (L2) learners whose native language does not use stress to contrast word meaning often face difficulty in perceiving stress in their L2. Even when both languages do use stress contrastively, stress acquisition may be challenging if the two languages differ in their phonetic cues used for stress, or if stress plays a stronger role in differentiating words in the L2 compared to the first. While phonetic training has been shown to be effective for improving the perception of L2 speech segments and tone acquisition, whether it is effective for improving suprasegmental stress perception in a L2 has not been well established. This doctoral dissertation investigates whether the perception of stress by L2 learners may be improved through phonetic training and whether the benefits of training generalize to untrained syllable positions. Additionally, this dissertation investigates the role of attention in the learning of L2 stress. The importance of attention for the acquisition of unfamiliar speech sounds has been discussed by L2 learning models, but few studies have examined its role during phonetic training for non-segmental features. Understanding whether phonetic training is effective for improving stress acquisition and the role that attention plays during training can help inform linguistic theories for L2 acquisition and aid in developing effective pedagogical methods for teaching second language stress. The doctoral dissertation aims to establish whether the perception and phonological processing of suprasegmental stress by L2 learners may be improved through phonetic training, the role that attentional allocation plays during the acquisition of suprasegmental features, and whether the benefits of training are generalizable to untrained syllable positions. The Automatic Selective Perception model posits that attentional focus is required during the early stages of L2 learning in order to successfully perceive and acquire novel L2 sounds. This predicts that mere exposure to L2 sounds may not result in improving perceptual accuracy if a learner’s attention is not directed towards the feature in question. The present dissertation provides participants with a series of four phonetic training sessions. While all participants are exposed to the same stimuli during training, they are split into two groups with different tasks: a stress group and a segmental group. The stress group receives feedback during training directing their attention to identifying stress placement, while the segmental group has their attention directed to initial consonant voicing. Four pre- and post-tests are given to measure performance differences after training: a sequence-recall task, two discrimination tasks (an AX task and a novel AQX task), and an identification task. In sum, this dissertation aims to contribute to our understanding of the role of attention during L2 stress acquisition and determine whether phonetic training is effective for improving stress perception for first and second language pairs that differ in their instantiation of stress. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-01

The increasing production and low recyclability of legacy plastics, such as polyolefins, pose a significant environmental challenge. Despite ongoing development of chemical processes to convert waste polyolefins into valuable products, polyolefins’ long carbon chains, high melt viscosity, and low diffusivities create substantial reaction engineering issues. These issues lead to transport-limiting kinetics, low product selectivity, and low product yields. This fellowship project aims to explore how tunable media can improve the transport properties of the reaction medium and impact the catalytic conversion of polyolefins, notably polyethylene (PE), into hydrocarbon fuels. Using high-temperature and high-pressure in situ/operando spectroscopy tools, the team will study the transport properties of PE melt in the presence of CO2-tunable media and gather detailed molecular-level information on the transformations during catalytic conversion. This fellowship will promote partnerships between academic institutions, boost STEM workforce development, and strengthen the State of Kansas’ competitiveness to attract federal and industrial research funding. This Research Infrastructure Improvement (RII) EPSCoR Research Fellows project will provide a fellowship to an Assistant professor and training for a graduate student at the University of Kansas Center for Research Inc. This work will be conducted in collaboration with researchers at Washington University, St. Louis. Although supercritical CO2 is commonly used to reduce the viscosity of polymer solutions, its full potential in enhancing the catalytic transformation of waste polyolefins remains unexplored. The primary objectives of the fellowship project are to investigate how CO2-tunable media affect the transport properties of PE melt, and to determine the impact of CO2-tunable media on the catalytic conversion kinetics of PE. Pulsed Field Gradient (PFG) Nuclear Magnetic Resonance (NMR) will be leveraged to measure the diffusivities of PE melt, intermediates, and reactants within porous catalysts in the presence of sub- and supercritical CO2. Operando Magic-Angle Spinning (MAS) NMR will enable real-time monitoring of reactions, providing detailed molecular-level insights into the transformations during hydrocracking of PE across various catalysts and reaction conditions. Such knowledge is transformative, offering new design principles for optimizing conversion processes for waste polyolefins, which can be applied to other chemical processes and other postconsumer plastics. 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 · 2024-12

The global commodity chemical market is responding to a shift away from traditional petroleum refining (driven primarily by decreased oil refining) to greater reliance on natural gas. Simultaneously, more energy-efficient and targeted chemical manufacturing processes are needed to ensure the supply of high-volume chemical feedstocks during the clean-energy transition to net-zero carbon emissions. Those trends have created a gap in the production of propylene – a vital olefinic hydrocarbon critical to the production of plastics and other polymeric materials. The project addresses the so-called propylene gap by researching novel catalyst designs to lower the energy requirements (i.e. decreased carbon emissions) while simultaneously increasing the reaction efficiency of producing propylene from other olefinic hydrocarbons in a chemical conversion process known as olefin metathesis. To those ends, the project contributes to U.S. energy security, net-zero emissions goals, and the sustained supply of high-volume chemicals that drive the economy. Monometallic single-site heterogeneous catalysts based on tungsten (W) and Molybdenum (Mo) on silica supports have been widely used for olefin metathesis of ethene and 2-butene into propylene (i.e., propene). In a series of breakthrough studies, the investigators have shown that the presence of small amounts of a second metal, such as niobium (Nb) (e.g.,1 wt% of Nb loading for 20 wt% of W/Mo) in the silicate support matrix, significantly increases the propene yield compared to the monometallic catalyst. While increased metal (M) dispersion on the Nb-based silicate support, and the formation of additional dioxo [(O=)2M(-O-Nb)(-O-Si)] pre-catalyst sites, clearly contribute to the enhancement, a fundamental understanding for the enhancement effect is still lacking. The project will explore two specific thrusts to fill the existing knowledge gaps and provide testable predictions for the improvement of the catalytic activity: 1) determine the complete reaction mechanism for the metathesis of ethene and 2-butene to form propene on silica-supported W or Mo catalyst in the presence of a second metal such as Nb, and 2) investigate the structural and electronic effects of varying the second metal. Quantum chemistry and machine learning simulations will be combined with experimental catalyst synthesis and characterization to identify chemical descriptors that will lead to rational design principles for better-performing catalyst materials. Although the immediate benefits of the project are predicated on propylene synthesis utilizing ethene and 2-butene from natural gas, the generic nature of the catalytic olefin metathesis mechanism opens the door to olefins produced from biorenewable feedstocks. For example, the repurposing of ethanol-based biorefineries to make chemicals with significantly more value (compared to its use as a transportation fuel, which will steadily decline as electrification of the passenger car industry takes hold) has potential to facilitate profitability and rejuvenate rural agro-based economies, while significantly promoting decarbonization and sustainability in the chemical industry. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-12

This award will partially fund 10 students to attend the 2024 Women in Hardware and Systems Security (WISE) Workshop. Hardware and systems security is a critical social issue given society's reliance on microelectronics that are targets of malicious attackers. To increase the number, quality, and diversity of hardware and systems security researchers, the WISE workshop series provides intellectual, mentoring, and professional network development activities for researcher entering the field. The series offers a platform for the exchange of innovative ideas around hardware and systems security, as well as panel discussions of the professional challenges of succeeding in this research area. Students will also have the opportunity to present posters about their own work to both the WISE workshop and the co-located IEEE International Symposium on Hardware Oriented Security and Trust (HOST). Through these efforts, the WISE workshop series will broaden participation in hardware and systems security, in turn increasing the size and quality of the workforce. Students' work will also be disseminated through the WISE YouTube channel, increasing awareness of hardware and systems security advances for both the research community and the general public. Students will be selected based on financial need, the relevance of their research to the field of hardware and systems security, and their career stage (with consideration given to both first-time attendees and to attendees about to enter the job market). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Environmental accumulation of postconsumer plastics, including poly (ethylene terephthalate) (PET), is a significant ecological concern. Various chemical recycling technologies are being actively developed to address plastic waste management issues and their threat to the environment. Methods that use chemical solutions can facilitate the recovery of building blocks called monomers. These building blocks can be used to synthesize new-like PET or generate other materials and chemicals. However, moving the target products through in the solutions can be challenging, especially at temperatures below the melting point of PET. At these temperatures the solutions can become thick and or the feedstock is less soluble in most conventional solvents. Therefore, this research program will investigate how CO2-H2O mixtures can be used as a tunable media to reduce these challenges and better break-down PET into its monomeric compounds for recycling/ upcycling. The research will be conducted by a team of researchers located at the University of Kansas and Northwestern University in collaboration with researchers at Washington University in St. Louis and SLAC National Accelerator Laboratory. The technical and environmental impacts of this project are significant, given the millions of tons of waste plastics that must be recycled or chemically transformed into valuable products. The researchers will receive cross-disciplinary training in science and engineering, attend communication workshops and conduct outreach activities, and work collaboratively in partnering universities and National laboratories. This project is built around the high-media tunability offered by near-supercritical and supercritical CO2 (scCO2) to minimize the limitations of chemical recycling processes. The limitations encompass poor accessibility of catalysts and reagents in a viscous semi-crystalline polymer matrix and thermodynamic barriers pertaining to polymer morphology and structure. These impact the reactivity and selectivity during solvent-based deconstruction of waste plastics. The two primary aims of this project are (1) to elucidate the impact of CO2 on PET polymer morphology, phase behavior, and reagent transport during acid-catalyzed hydrolysis, and (2) to understand the deconstruction of semi-crystalline PET in CO2-tunable media mechanistically. Advanced ex situ and in situ/ operando analytical techniques, such as small- and wide-angle X-ray scattering (SAXS/WAXS) and Magic Angle Spinning-Nuclear Magnetic Resonance (MAS-NMR) Spectroscopy will be leveraged to generate fundamental knowledge on how CO2 impacts polymer phase behavior, morphological and thermal properties as well as solvent transport at varying temperatures and pressures. A detailed kinetic Monte Carlo model will be developed to provide insights into the reaction and transport mechanisms of hydrolytic deconstruction of PET into monomers in the presence of CO2. This work will also put forward a state-of-the-art methodology blueprint, which can be adapted to expand multi-scale mechanistic studies to other chemical recycling strategies for post-consumer plastics. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Over 10 million fossil specimen records are publicly available via online portals, such as GBIF (Global Biodiversity Information Facility). However, researchers are currently unable to realize the full potential of these data because they are difficult to find and use due to the bio-focused nature of the portals. This project aims to: (1) leverage the Paleo Data Working Group's (PDWG) decade-long leadership to connect existing open science cyberinfrastructure resources in a network that will better integrate data from fossil and biological collections; (2) democratize access to collections-based, digitized paleontological data for research; and (3) expand PDWG's successful community-of-practice model to further build capacity for improving and mobilizing data from fossil collections. Paleontology, situated at the intersection of geo- and bioscience, is an inherently interdisciplinary field with impactful research that has the potential to significantly contribute to better understanding the current biodiversity crisis in relation to rapidly changing global climatic conditions. This project will support transformational and translational research in these fields by driving development in the open data landscape, and improving discoverability and use of millions of fossil specimen records. It will target known cyberinfrastructure gaps related to taxonomy and stratigraphy by engaging with the paleontological collections and research user communities, in collaboration with cyberinfrastructure partners, to evaluate the existing technical landscape. These efforts will ultimately lead to the development of a roadmap for establishing an enhanced network of FAIR and research-ready data accessible via TRUSTed digital repositories (the “Paleo Roadmap”). The project goals will be accomplished through a community-based approach that centers the role of humans in open science cyberinfrastructure. Engagement of a diverse group of stakeholders - ranging from small collections to early career individuals - is central to all parts of the project and development of the Paleo Roadmap. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Generative AI systems, which can produce text, images, and other content, are increasingly commonly used. However, from a security and privacy perspective, these systems pose a number of risks. Generative AI systems can violate the property and privacy rights of the people whose data are used to build them. They can also be used to generate content that might trick people into making mistakes that affect their security, privacy, and beliefs. On the other hand, generative AI systems might be used to support security and privacy goals. They may be able to create synthetic data that helps detect and predict new attacks more rapidly, which in turn could be used to make safer software, policies, and security operations practices. This project's goal is to support the planning of a large-scale proposal to study the risks and benefits that Generative AI-based systems may pose to security and privacy, developing methods to increase their safety and usefulness for society. The project's goal is to develop a fully realized proposal in terms of the scientific questions, team and partnerships, and social impacts to be addressed. To do this the research team will start with project ideation and identification of key stakeholders in both the scientific and social impact realms. These efforts will be based on established methods for identifying and learning from those affected by projects, including interviews, workshops, and community-building meetups. The research team will also identify an external advisory board and evaluation team to guide the project as it goes forward. Through these efforts, the team will develop the knowledge, resources, and people required to create a high-quality, large-scale proposal. 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

Nontechnical description The need for ultrathin (thickness in sub-2 nm) oxide semiconductor films with tunable electronic structures and functionalities arises from the steady trend of reducing device dimensions in electronics for advanced computing and artificial intelligence following the empirical Moore’s law during the past few decades. New energy-efficient computing paradigms have emerged, such as neuromorphic computing (NC), which is inspired by how brains work. This paradigm aims to address the von Neumann bottleneck, taking advantage of the computing strength of a neural system, namely pattern recognition and unstructured data sorting. The challenge for ultrathin oxide semiconductor films and their applications in devices and circuits is the lack of understanding and control of the physical and chemical properties of the materials when approaching atomic scales, when defects within those films and at their interfaces become increasingly important. Memristors, regarded as the fourth fundamental circuit element next to resistor, capacitor, and inductor, consist of a thin oxide semiconductor film sandwiched between a pair of electrodes. The operations of both memory storage and low-power computing are integrated in memristors. The ability to control at the atomic scale the memristive resistance, switching speed, power efficiency, scalability, and stability among other performance criteria, presents a major challenge to future NC circuits. The proposed research will address this challenge through the development of a co-design approach for design, synthesis, and characterization of sub-2 nm wide-bandgap semiconductor memristors and prototype NC circuits with atomically tunable physical properties and functionalities. The success of the project can have a broader impact on a large spectrum of commercial applications including neuromorphic and quantum computing, artificial intelligence, quantum information science, CMOS, etc. This project emphasizes forefront STEM workforce training through a set of education and outreach activities towards producing a unique and diverse workforce for the future semiconductor industry. This award is cofunded by Advancing Informal STEM Learning program. Technical description Atomically tunable memristors based on ultrathin (sub-2 nm) wide bandgap semiconductors, such as Ga2O3, with their electronic structure and the oxygen vacancy (VO) concentration, distribution, and diffusion controlled with atomic precision, are key to future NC circuits of high performance, scalability, stability, and energy efficiency, which present major challenges to current NC technologies. To address those challenges, the research team has recently developed a simulation-guided design and fabrication approach for an atomic layer stack (ALS) of sub-2 nm memristors using a state-of-the-art custom-designed/built in vacuo atomic layer deposition (iALD) system. Using this capability, atomically controlled bandgap tuning and VO doping of pristine wide-bandgap Ga2O3-ALS has been demonstrated by insertion of Al2O3 and MgO atomic layers of different numbers and stacking sequences. This has led to the successful atomic tuning of Ga2O3-ALS memristors’ physical properties including the on/off ratio of 10-40000 and switching speed from microsecond to nanosecond. The proposed co-design approach for fabrication, characterization and testing of sub-2 nm wide-bandgap semiconductor ALS memristors and prototype memristor-based NC circuits has three aims. Aim 1 focuses on simulation-guided design and synthesis of Ga2O3-ALS memristors. Aim 2 investigates memristor structure-property relationship using various advanced tools for a thorough understanding and full control of the ALS design parameters towards atomically tunable memristors to enable brain-inspired NC with high energy efficiency, switching speed, stability, and scalability. Aim 3 explores the prototypes of NC circuits based on the tunable memristors. New fundamental understanding of sub-2 nm wide-bandgap semiconductor Ga2O3-ALS is crucial to achieving atomically tunable memristors for future electronics and computing. A transformative leap in novel co-design approaches of sub-2 nm ALS enables new functionalities for future electronics. 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 supports participants at the 2024 and 2025 editions of the Prairie Analysis Seminar. The Fall 2024 event will be held in October 2024 at the University of Kansas; the Fall 2025 event will be hosted by Kansas State University (date to be determined). The Prairie Analysis Seminar is an ongoing collaboration between the mathematics departments at Kansas State University and the University of Kansas. Since its inception in 2001, the conference has showcased the research of a diverse group of mathematicians working in analysis and partial differential equations. The event provides participants in early career stages with the opportunity to present their work via contributed talks, to get advice from experts, and to expand their professional networks. In addition, the event promotes the participation of underrepresented and underserved groups in mathematics, in particular, researchers from smaller colleges and universities in geographical proximity to the host institutions. Invited speakers at the Prairie Analysis Seminar are leading scholars well known for their contributions to active areas of research within analysis and partial differential equations and for their ability to communicate with a broad mathematical audience. Each event features an invited principal speaker, who gives two one-hour lectures, accompanied by two invited speakers who each give a one-hour lecture. An important component of the seminar is the time reserved for short talks by early career participants, including advanced Ph.D. students and postdocs. The conference also includes a session for discussion of open problems suggested by conference participants. https://www.math.ksu.edu/research/centers-groups/group/analysis/prairie_seminar.html 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

Microbial symbionts help plants acquire resources and thereby improve plant productivity. Many plant species simultaneously interact with multiple symbionts. Notably, legumes, including economically important crops such as beans, associate with both soil fungi called arbuscular mycorrhizal fungi (AMF) and rhizobia bacteria, which improve uptake of soil phosphorus and nitrogen, respectively. Legumes can realize greater benefits from associating with both symbionts than expected from the effect each symbiont has on its own. That is, plants can derive synergistic benefits from multiple symbionts. However, when legumes will receive synergistic benefits is not understood. Understanding the contexts under which legumes are likely to receive synergistic benefits will help land managers and restoration ecologists manipulate environmental conditions to help establish desirable legumes in managed and degraded systems. In agricultural systems, understanding these context dependencies could help improve food production while potentially lessening the need for fertilizer inputs on legume crops. The goal of this project is to develop and test a predictive framework for synergistic benefits within the legume-AMF-rhizobia system. The investigators will also develop educational modules using legumes, rhizobia, and AMF for use in middle and high school classrooms, and train students within a collaborative environment. Although individual studies of legume-AMF-rhizobia interactions have shown synergism, synergism is not the general result according to meta-analyses. This suggests that the impact of simultaneous interaction with AMF and rhizobia on legume performance may depend on environmental context or plant and microbial characteristics. The investigators predict that synergism can occur when symbionts provide plants with complementary, limiting resources required for growth (phosphorus and nitrogen). This stoichiometric complementarity hypothesis suggests that synergism will occur when nitrogen and phosphorus are co-limiting and when the symbionts are effective at providing complementary resources. Moreover, synergism may require sustained reinvestment in symbionts over time and consequently be more likely in perennial than in short-lived annual legumes. The investigators will test these predictions by evaluating synergism in legume-AMF-rhizobia interactions while manipulating soil nitrogen and phosphorus availability, symbiont quality, and legume life history. The investigators will couple the experimental work with the development of theoretical models to extend mechanistic understanding of these symbioses to predictions of synergism. This work will improve understanding of the role that symbionts play in plant ecology and evolution and guide development of regenerative agricultural systems that maximize the value of plant microbiomes. 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

Society has grown to rely on smart, embedded, and interconnected systems. This has created a great need for well-qualified and motivated engineers, scientists, and technicians who can design, develop, and deploy innovative microelectronics and Artificial Intelligence (AI) technologies, which drive these systems. This project will address the need for a more robust computer science and engineering workforce, a matter of national security, by broadening access to microelectronics and AI education leveraging the cutting-edge technologies of Tiny Machine Learning and low-cost microcontroller systems in diverse Florida, Kansas, and Texas high schools. This project will leverage the partnership with the Scientist for Every Florida School network and nurture new relationships with industry partners. The goal of this project is to engage about 500 high-school students and approximately 25 teachers from under-resourced communities in the design and creative application of AI-enabled smart, embedded technologies, while supporting their engineering identity development and preparing them for the STEM jobs of tomorrow. This project will benefit society with its timely and accessible high-school curriculum that integrates Computer Science and Engineering using the rich context of microelectronics and AI. The curriculum will be accessible because it has no prerequisites for programming or hardware knowledge. Every module is centered around a real-world application of microelectronics and AI with direct implications for improving the quality of life in local communities, making learning relevant and place-based. All course materials and resources will be disseminated as open source via the platforms popular among K-12 stakeholders, broadening access and inspiring the next generation of AI practitioners. The focus of this design-based implementation research program is to conduct a systematic inquiry into the effective conditions for designing and integrating curricula and technologies that foster engineering identity development and conceptual understanding of AI in embedded systems as an important trend in engineering. To this end, the research is informed by both qualitative research questions (How are the altruism informed activities perceived and used by students?) and quantitative questions (What are the quantifiable impacts of this approach on students’ motivation and conceptions of edge AI and microelectronics?) The research plan will employ a concurrent triangulation mixed-method research design, incorporating phenomenology, comparative case studies, and mixed-effects modeling. Specifically, the researchers will conduct classroom observations, interviews with students, teachers, and parents or caregivers, surveys, and learning tests to examine the uses and effects of the proposed approach in high school classrooms. This research will contribute new data for building theories on a) altruism as a motivation framework for supporting engineering education, and b) negotiation of engineering identities when engaging students in community-relevant AI and microelectronics projects. This Design and Development project is funded by the Discovery Research preK-12 (DRK-12) program, which seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

With this CAREER Award, the Chemical Synthesis Program of the NSF Division of Chemistry is supporting the research of Professor Manar Shoshani and his students who will explore new methods to convert carbon dioxide selectively to more valuable products such as formic acid, methanol, and oxalic acid under mild conditions. While carbon dioxide can be converted to other materials the processes to do this usually suffers from lack of selectivity and lead to mixtures of various products. This research will use new and well-defined complexes, featuring multiple metals centers that are abundant on Earth, and work cooperatively in carbon dioxide reactivity. Deliberate access to varying carbon dioxide reduction products, directly from carbon dioxide, has been a long-standing challenge in sustainable sciences. Professor Shoshani has collaborated with a local community college, Johnson County Community College (JCCC), in the Kansas area. Prof. Shoshani will host students from JCCC to work in the research lab for summer-semester internships. This research leverages single component and Earth-abundant multimetallic architectures in the cooperative reduction of carbon dioxide to value-added products. Current challenges in deliberate access to a variety of CO2 reduction products on well-defined platforms will be addressed by utilizing Lewis-acidic or Lewis- basic design elements within well-defined scaffolds to direct selectivity and reactivity. Single-component Ni-Lewis acid complexes will be utilized to access distinct reduction pathways and provide insights through structure-function studies to uncover design elements needed to access modular and selective carbon dioxide reduction. Multimetallic Ni-Lewis base complexes will be leveraged for new methodology in carbon dioxide reduction by incorporating metal-metal cooperativity as well as Lewis-basic nitrenoids equipped to regulate proton and electron flux within a single molecular system. Cumulatively, this work represents new strategies in the controlled access of varying carbon dioxide reduction products through the incorporation of underexplored and traditionally challenging design elements in well-defined molecular motifs. This research provides a rich training opportunity for a new generation of chemists and the outreach initiatives engage students at the K-12 and post-secondary level. 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

Most flowering plants, including many key food and cash crops such as cocoa and coffee, rely on animal pollinators for reproduction. Disruptions to these plant-pollinator relationships due to climate and landscape changes are expected to have severe negative consequences for plant reproduction and ecosystem functioning. This is especially true in tropical regions, where a higher proportion of plants depend on animal pollination compared to temperate ecosystems. Such disruptions in tropical pollination systems also pose a threat to food security and global economies, given the significant number of crops imported from these regions. However, tropical plant-pollinator interactions remain understudied. This project provides research training and mentorship to 15 U.S. students over three years in Colombia, one of the most biologically and agriculturally diverse countries in the world. Colombia’s highly variable topography and diversity of climates support an astonishing diversity of native plants, as well as tropical and temperate crops, making it a natural laboratory. The project offers students a unique opportunity to integrate multiple fields of research, from behavior to ecophysiology, and to apply cutting-edge techniques to address pressing scientific and societal challenges in conservation and agriculture. Plant-pollinator interactions are increasingly affected by climate and landscape changes through various mechanisms. Yet these interactions remain understudied, posing a significant risk to efforts for biodiversity conservation and ecosystem services. This IRES project aims to bridge this knowledge gap by engaging the next generation of U.S. scientists in investigating fundamental questions about the drivers of changes and disruptions in plant-pollinator interactions in rapidly transforming and understudied tropical ecosystems. The project offers training in research and science communication to 15 U.S. students from underrepresented groups (five per year) giving them a unique research experience in an international setting. Guided by a transdisciplinary and multicultural team of researchers, students participate in collaborative research during an eight-week program in Colombia, a megadiverse tropical country. The project addresses predictions regarding phenotypic plasticity, the interactive effects of environmental stressors on organisms’ thermal tolerance, and the roles of temperature and humidity in shaping plant-pollinator interactions, among other topics. This project provides students with a unique opportunity to integrate observational, comparative, and experimental methods across various scales of biological organization while building a robust network of national and international collaborators. The results of this project will enhance our understanding of ecology, physiology, and the conservation of plant-pollinator interactions, with practical applications for sustainable agriculture. 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

A fundamental challenge in biology is to understand how DNA differences between individuals determine trait differences, particularly those trait differences that define species. Traditionally, researchers have focused on striking differences that distinguish one species from another. They have then worked to discover the underlying genetic variation explaining those trait differences. This focus on individual traits considered in isolation has limited our understanding of how changes across the entire genome promote the formation and maintenance of new species with complex trait differences. This project takes a novel approach by leveraging advanced genomic technologies to first identify the precise DNA differences that distinguish focal species of flowering plants from one another, and second to validate the trait differences that result from those DNA-level differences. The species-distinguishing traits in this system are complex and highly integrated differences between flowers that lead to bee pollination in some species and hummingbird pollination in another. In-line with the goals of NSF EDGE-CMT, outcomes from this project will improve our understanding of how trait complexity first arises and is subsequently maintained between species. It will further provide a methodological approach for biologists to link variation found between genomes to complex trait differences across the tree of life. This project will strengthen our scientific workforce by providing students and postdoctoral researchers from diverse backgrounds training in the application of genomic and quantitative methods. Such training can be leveraged across research enterprises, from basic science to novel discoveries in health and agriculture. The proposed research will use recently developed genetic and genomic resources to dissect the genome to phenome relationship between bee- and hummingbird-adapted floral syndromes that define species in a Penstemon complex. A set of approximately twenty genomic regions, previously shown to be strongly diagnostic of floral syndrome and species identity, will be confirmed using genome-wide association mapping. Based on preliminary data, these regions are expected to be physically unlinked, scattered genome-wide, and sufficiently narrow to include only 1-2 genes each. These narrow, divergent genomic regions result from natural selection favoring alternative floral trait combinations promoting bee- versus hummingbird-pollination in the face of gene flow and ample recombination. Using population genomic, transcriptomic and gene functional prediction methods, these loci will be genetically dissected to discover the history of complex trait assembly, the contribution of mutational types to adaptive evolution, and the broader set of adaptive traits that form canonical pollination syndrome phenotypes. The unique genomic architecture in this system provides a novel opportunity for the researchers to dissect the contributions of regulatory versus protein coding mutations to adaptive evolution, determine how selection acts to maintain multi-locus species differences in the face of gene flow, and to test fundamental questions of complex trait evolution. 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 Louis Stokes Alliances for Minority Participation (LSAMP) program assists universities and colleges in their efforts to significantly increase the numbers of students matriculating into and successfully completing high quality degree programs in science, technology, engineering and mathematics (STEM) disciplines in order to diversify the STEM workforce and supports the production of scholarly research in STEM broadening participation. Particular emphasis is placed on transforming undergraduate STEM education through innovative, evidence-based recruitment and retention strategies, and relevant educational experiences in support of racial and ethnic groups historically underrepresented in STEM disciplines: Blacks and African Americans, Hispanic and Latino Americans, American Indians, Alaska Natives, Native Hawaiians, and Native Pacific Islanders. These strategies facilitate the production of highly competitive students motivated to pursue graduate education or careers in STEM. For the United States (U.S.) to remain globally competitive, it is vital that it taps into the talent of all its citizens and provides exceptional educational preparedness in STEM areas that underpin the knowledge-based economy. This project develops a new alliance, Aligning STEM Trainees for Enterprising Research (ASTER), in eastern Kansas and Nebraska. ASTER LSAMP is composed of six institutions: University of Kansas, Pittsburg State University, University of Nebraska, Johnson County Community College, Kansas City Kansas Community College, and Southeast Community College. The alliance will develop pathways between the three 2-year community colleges and three 4-year universities to facilitate undergraduate research activities, matriculation of underrepresented minority students, and better prepare students for careers in academia, industry, and government. ASTER LSAMP goals include increasing the proportion of STEM students who 1) transfer to partnering 4-year institutions, 2) matriculate into their second and third undergraduate year, 3) graduate with STEM bachelor’s degrees, and 4) earn a graduate degree. ASTER LSAMP will use evidence-based high impact educational practices including monthly professional development, involvement with research activities, conference attendance, peer mentorship, study groups, and summer internships to meet these goals. Students will be paired with faculty mentors who have participated in cultural humility training and understand evidence-based mentorship practices for diverse students. Participating students will gain professional, academic, and social skills to prepare them for coursework and post-graduate career success. ASTER LSAMP will contribute to the development of STEM talent in Kansas and Nebraska. 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

Atomically thin materials, such as transition metal dichalcogenides, exhibit unique optical and electronic properties, making them promising candidates for the development of optical devices and quantum information processing applications. These applications have gained momentum due to the ability to utilize light to generate specific quantum states in such materials and their compatibility with graphene, forming heterostructures for efficient electron capture and transport. While such potential applications paint an exciting picture for quantum-related technologies, several major hurdles impede their progress. These include the ultrafast decay of quantum properties and the challenge of accessing quantum information without distorting the systems. The objective of this project is to address these challenges by developing a transformative approach wherein, instead of attempting to tame the very fast processes that hinder applications of such systems for quantum processing, they will be leveraged to access the quantum states and to encode and encrypt information. This project establishes a novel platform that allows the use of well-established electronic systems, such as field-effect transistors, for gaining access to quantum states via electronic currents, and application of systems consisting of atomically thin semiconductor combined with metallic structures with nanoscale sizes for quantum encryption of optical information and processing. This platform can also enable the development of quantum nanosensors capable of detecting individual biological molecules and even their structural features and promote the application of quantum mechanical processes for the transport of energy and information. Additionally, this project will enhance the research capacities of the University of Alabama in Huntsville and Kansas University, leading to the development of new curricula, research, educational, and outreach programs in the states of Alabama and Kansas. This project develops a transformative approach by harnessing the decay of plasmons to gain electronic access to quantum states and processes within systems composed of transition metal dichalcogenides monolayers and plasmonic nanoantennas. In such systems the non-radiative decay of plasmons into hot electrons will be exploited to convert spin-valley quantum information into currents in field-effect transistors, thus establishing an electronic quantum readout. Therefore, the temporal variations in hot electron generation will bear the signatures of coherent spin-valley processes and quantum information. The proposed field-effect transistor devices will feature atomically-designed super-heterostructures comprising transition metal dichalcogenides monolayers, semiconductor oxide layers with sub-2-nm thicknesses, and Au nanoantennas. These heterostructures will support atomically-tunable ultra-thin high-mobility Schottky barriers capable of efficiently capturing hot electrons and transporting them without scattering. Within these field-effect transistors, quantum information will be encoded into the hot electron current by modulating their generation rates over time through spin valley exciton-plasmon coupling. An in-vacuo Atomic Layer Deposition system integrated with in-situ characterization tools will be developed for fabrication of defect-free sub-2-nm oxide/Au Schottky junctions with ultra-high mobility and atomistically controlled dimensions. These Schottky junctions will efficiently capture hot electrons and transport them without scattering, while being ultrathin allows efficient exciton-plasmon coupling. To encode quantum information into the current, we will utilize spin valley exciton-plasmon coupling to create a set of quantum states in the time domain. Quantum information will then be decoded by analyzing the dynamics of the output circuit current and mapping the evolution of the dynamic states in Bloch space. The outcomes of this project have the potential for multidisciplinary impact, spanning from quantum sensors to optical coherent transistors and coherent energy transfer. Additionally, this research presents a unique opportunity for graduate and undergraduate students to engage in cutting-edge scientific exploration. The associated outreach program aims to provide high school students in North Alabama and Kansas with hands-on experiences in nanoscience and quantum information science through experimental and tutorial sessions. 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

Microorganisms are everywhere and control many of Earth’s processes. Fungi that interact with plants play one of the most critical roles in these processes, helping most plants grow and survive but also causing some of the worst plant diseases. Yet we know remarkably little about how plant-fungal interactions vary across the globe. Mapping plant-fungal partners could help us predict plant functions, particularly under environmental change. We need rapid answers to these questions and they must scale from microorganisms to the entire planet, but the small research communities working on pieces of this grand problem are largely scattered and independent. Our MICROBENet^Net project will unite a diverse array of research networks from around the world, integrating databases and tools to build a common foundation to predict plant-fungal roles and solutions in current and future environmental challenges and overcome logistical roadblocks. For example, more accurate predictions of plant-fungal interactions can help us enhance crop yield and disease resistance or better predict which ecosystems will absorb more carbon dioxide versus those that will release it. Our project also will train the next generation of biologists that work across currently siloed disciplines, so that they can be just as comfortable measuring the traits of individual fungi as modeling fungal-mediated processes across the entire planet. Individual networks struggle to address some of our most fundamental interdisciplinary questions, inhibited by an inability to scale globally and a lack of interdisciplinary knowledge. Connections among disparate networks of plant and fungal biologists are also currently hindered by differences in disciplinary lexicons, limited face to face capacity, lack of harmonized data streams, and challenging cross-cultural interfaces. MICROBENet^Net, our proposed network of networks, will bridge convergent networks of people and research lines, train the next generation of interdisciplinary scientists, and link databases, all of which are needed to address cross-cutting, societal challenges. Our online hub, annual colloquia, and research exchanges will provide an integrated, international community to build out an easily accessible integrative workflow that links our network of researchers to cross disciplinary expertise and data. With this access, individual networks (and new, future nodes) can rapidly advance answers to long-standing questions in plant-fungal interactions. Convergent research on plant-fungal interactions can, for example, improve predictions of plant productivity, as well as which ecosystems around the globe will tip between net carbon sources or sinks. This project is jointly funded by the Accelerating Research through International Network-to-Network Collaborations (AccelNet) program and the Established Program to Stimulate Competitive Research (EPSCoR). This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This project will improve understanding of what constrains where a species can live, both currently and in an altered future climate. Improved understanding of species’ geographic ranges is important for conservation and resource management and for controlling pest species and disease vectors. “Species distribution models” (SDMs) compare a list of locations a species has been seen to past climatic data to help understand what controls the species’ geographic distribution. SDMs can also project a species’ future distribution. SDMs are extremely widely applied. But SDMs have a major weakness that limits their effectiveness. Traditional SDMs use data on average climate, e.g., average temperature for 1980-2000. But researchers working in the field of stochastic demography know that climate variability in a location can also make a species unable to live there, even when the average climate is suitable. For instance, a reliable 6 inches of spring rainfall in a location, every year, may be ideal for a species. But suppose a second location gets 12 inches spring rainfall in some years and 0 in other years. It may be impossible for the species to live in the second location, even though both locations may have the same average spring rainfall. Traditional SDMs cannot accurately assess the influence of variability on species geographic ranges. Addressing this shortcoming is pressing because climate change will alter climatic variability, influencing species’ ranges. This research will fill this knowledge gap by integrating demographic methods into SDMs. The project will develop an understanding of how variability influences species niches and ranges in the present and future. The project will also provide training in ecology to hundreds of 3rd grade teachers and students in underserved schools. Software and other resources facilitating uptake of new methods will be released to other scientists and conservation and management practitioners. Objective 1 of the project is to develop theoretical and statistical foundations of a new approach to SDMs that we call XSDM, and to quantify the effectiveness of XSDM compared to existing methods. Objective 2 is to apply XSDM to thousands of species, broadly examining the role of interannual climatic variability in constraining species ranges. Objective 3 is to further expand XSDM to account for population age structure, allowing for the possibility that different life stages of a species have different environmental sensitivities. The research framework allows statistical assessment of the degree to which each increase in demographic complexity/realism of the model used is needed to understand a species’ niche and distribution. Objective 4 involves the provision of resources to the research and applied community to facilitate the broad uptake of XSDM. 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

Heating, ventilation, air conditioning, and refrigeration (HVACR) are essential to human quality of life but exact a significant environmental toll. Most current refrigerants are high-global-warming-potential (GWP) hydrofluorocarbons (HFCs) with up to 4000 times the impact of CO2. High HVACR-associated energy consumption and HFC leaks account for 7.8% of total greenhouse-gas emissions. HFCs’ chemical stability, combined with challenges associated with separating HFC refrigerant blends into components, make sustainable recycling and repurposing of these refrigerants difficult. In addition, tightening U.S. regulations have created a market for illegal HFC imports. The American Innovation and Manufacturing (AIM) Act mandates an 85% phasedown of HFCs over the next two decades, but these challenges threaten that goal. Even if the technical goals are met, implementing such sweeping changes will require societal and industrial adoption and a greatly expanded U.S. HVACR workforce. The Environmentally Applied Refrigerant Technology Hub (EARTH) Engineering Research Center (ERC) will use a team-science approach to bring together talent in engineering (chemical, environmental, mechanical, and materials), architecture, business, chemistry, economics, geography, history, law, psychology, and entrepreneurship in one Innovation Ecosystem to co-create convergent technical and societal solutions with industry partners, technical and community colleges, professional organizations, regulators, and end users. EARTH’s vision is to create a transformative sustainable refrigerant lifecycle to address the HVACR ecosystem’s key technical and societal challenges: (1) lowering HFC emissions, (2) creating safe, property-balanced replacement refrigerants, and (3) increasing HVACR energy efficiency. In addition, EARTH will work toward workforce goals co-created with industry to increase the number of HVACR engineering researchers and will involve community and technical colleges to address workforce gaps through coordinated outreach and training. With stakeholder input and integration across fundamental knowledge, enabling technologies, and system testbeds, EARTH will convergently address the societal problem of refrigerant environmental impacts. Refrigerant leaking and venting will be addressed by new separation, conversion, security-tagging, and waste-refrigerant-reuse technologies, spurring sustainable decision-making and new startups. Novel, safe, property-balanced, low-flammability, low environmental-impact refrigerants will be explored with molecular simulations of candidate fluids, development of solid-state materials, regulatory-impact economic analysis, and corporate-innovation insights. Higher HVACR energy efficiency will be obtainable through new energy-efficient dehumidification materials, refrigerant-specific leak sensors, alternative refrigeration cycles, systems modeling, lifecycle analysis, technoeconomic analysis, and exploration of corporate, environmental, social, and governance activities. Crosscut themes - Synthesis & Characterization, Behavior & Policy, and Modeling & Analysis - will integrate research with all ERC pillars. The EPA estimates the AIM Act’s successful implementation from 2022 to 2050 will net benefits of $272 billion and emission reductions of 4.6 billion tons of CO2. It will also create 150,000 new jobs, increase U.S. manufacturing by $39 billion, and prevent a 0.5 °C increase in global temperature. EARTH will enable and accelerate these benefits with new technologies, data-informed regulatory guidance, and industry and stakeholder buy-in. By addressing the technical, environmental, and societal challenges of replacing high-GWP refrigerants, EARTH’s research will generate scientific knowledge, engineering products, environmental-policy recommendations, and industry and stakeholder behavioral changes to stimulate this HVACR-ecosystem transformation. EARTH has identified over 70 initial HVACR-ecosystem partners, including companies, community colleges and technical/trade schools, non-profit organizations, international universities, and federal labs, to aid with industry adoption of new technologies. EARTH will increase the HVACR industry’s workforce capacity across 6 core institutions (3 EPSCoR), in partnership with native-Hawai’ian-serving and tribal colleges/universities, community colleges, and technical/trade schools. 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

Fitness refers to the ability of an organism to survive and reproduce in its natural habitat. It is one of the most important attributes of any species. Fitness varies greatly among individuals within most species and this variation is ‘complex’ in multiple aspects. First, differences in fitness are caused by both differences in the environment experienced by organisms and in the genes they carry. Second, fitness involves multiple distinct components including survival, mate acquisition, fecundity and even the competitive success of gametes (sperm or egg). This research project develops and executes a collection of novel experimental and statistical methods to provide an unprecedented characterization of fitness variation in the model fruit fly species. The experiments will dissect fitness differences into their many distinct genetic causes by linking genetic variants at the DNA level to their effects on survival, mating success, and competition among gametes. The research exploits recent technological developments in genome sequencing, facilitating large-scale experiments, and enabling powerful hypothesis testing. The experimental results in the model fruit fly will provide proof-of-principal for the subsequent study of many different organisms. The project will also build our scientific workforce through training of students and postdoctoral researchers in genomic and quantitative science. Finally, the project will provide generalizable software that will be distributed to the scientific community for the analysis of similar experiments in genetics and genomics. A mechanistic understanding of natural selection requires that we (1) identify the processes generating fitness variation among individuals and (2) quantitatively estimate how that variation results in allele frequency change. This project employs massive-scale genome sequencing combined with field collections and experimental crosses to estimate the importance of differential survival relative to differential reproductive success. It estimates the frequency and strength of gametic selection, defined broadly to include meiotic drive, relative to fitness differences among diploid individuals. Synthesis of estimates within and across experiments will determine if different components of selection, such as viability and sexual selection, are typically reinforcing or conflicting. A substantial component of the project is theoretical, to develop algorithms and then make them publicly available (software development). These algorithms use genomic data to estimate fitness differences from their immediate effects, specifically the change in allele frequency at loci across the genome as they experience selection. The second phase of experimental work is a series of lab experiments using wild-derived genomes. These experiments test alternative hypotheses about how different aspects of male reproduction generate fitness variation at genes across the genome of Drosophila melanogaster. Finally, the project will train the scientific workforce in genomic and quantitative science and advance discovery in other systems by the dissemination of generalizable software that will be disseminated to the scientific community. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The increasing use of reusable hardware intellectual property (IP) in modern semiconductor design faces significant confidentiality threats, including reverse engineering (RE), IP theft, and piracy throughout its lifecycle. Various active IP protection techniques have been investigated to secure hardware IPs against these threats. With the emergence of a broad range of attacks on these techniques, there is a need for a principled approach to enable robust protection against possible attacks, while achieving low hardware overhead and scalability to large designs. The key novelty of this project is the use of diverse Artificial Intelligence (AI) techniques, such as reinforcement learning and explainable algorithms for automated discovery of new hardware security attacks and deriving commensurate design transformations to effectively protect against these attacks. The research outcomes from this project are used to develop new cybersecurity courses, increase the participation of undergraduate/high-school students in research, and release of open-source tools/datasets for the broader research community. This project also contributes to enhancing the security and trustworthiness of electronic hardware and greatly benefits the semiconductor industry, as well as making a positive impact on national security. This project is developing a new framework for microelectronic security and trust. The approach utilizes a fundamentally different, knowledge-guided systematic design transformation approach for securing IP against RE attacks. This framework mimics the way security researchers and engineers gather knowledge from existing attacks to discover novel attack vectors and their root causes. Furthermore, the method can devise strong defense strategies to mitigate the newly discovered attacks and apply these defense strategies in a scalable manner to create a protected design with minimal design overhead. This project comprises of three parts: (1) the reinforcement learning techniques discover novel attack vectors against logic locking and identify root causes behind the success of these attacks, (2) explainable diverse Artificial Intelligence (AI) is used to extract design transformation rules that can defend against diverse attack vectors, (3) the discovered design rules are applied to successfully meet design and security requirements while also ensuring correctness. The research team is also developing novel security metrics and integrating all the components into a comprehensive IP protection platform for rapid evaluations. Moreover, the research team also extends the framework to other Design-for-Security techniques, such as fault, side-channel, and Trojan attack countermeasures. 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 summary: Since high-temperature superconductors (HTS) were discovered and awarded a Nobel prize, many prototypes of electronic and electric applications based on HTS materials have been demonstrated. A great impact on reducing energy loss and environment impact is anticipated from adopting superconducting devices and systems, including fusion systems for energy, electric propulsion for electric aircrafts, wind-powered generators, high efficiency electric power grid, superconductor magnets for high-energy physics and NMR/MRI in medicine, etc. Significant market penetration of HTS technologies, however, requires performance-cost balanced HTS materials and demands basic material research to resolve the critical issues relevant to applications in achieving high superconducting critical current density, Jc. Growth of nanoscale impurities (so-called artificial pinning centers or APCs) in HTS matrix provides a powerful approach to raise Jc in APC/HTS nanocomposites, and the method can be directly implemented to large-scale commercial HTS devices and systems. The objective of this project, supported by the Ceramics Program in the Division of Materials Research at NSF, is to investigate the growth mechanism of APC/HTS nanocomposite films in a novel multilayer approach developed by this team for strain-field guided Ca diffusion to, and cation replacement on the HTS crystal lattice, aiming to achieve a precise control over the microstructure of the APC/HTS nanocomposites for enhanced Jc at high applied magnetic fields (H). The goal is to achieve high, H-orientation independent Jc in APC/HTS nanocomposites demanded for a variety of commercial applications ranging from lightweight electric-propulsion aircraft to high-efficiency power grid, to environmental-friendly fusion, etc. The project emphasizes forefront workforce training in science and engineering and the cutting-edge research capability that integrates nanoscale material design, fabrication, modeling and characterization which will attract high-quality students to pursue careers in science and technology. Technical summary: A long-standing question in superconductors is whether the theoretical depairing limit of superconducting critical current density Jc (so-called Jd) can be reached in high-temperature superconductors (HTS) through low-cost, controllable, strain-mediated, self-assembly of nanoscale APCs to pin the magnetic vortices with optimal efficiency. Addressing the challenge in approaching the Jd in APC/HTS nanocomposites demands understanding and controlling the strain fields at atomic to macroscopic scales. Such control cannot be achieved using the traditional trial-and-error approach. The proposed integrated modeling-synthesis-characterization approach represents a leap forward from the traditionally empirical one via materials by design. The recent success of this team in the development of a novel multilayer approach for strain-field guided Ca diffusion to, and cation replacement on the HTS Y123 (i.e. YBa2Cu3O7) crystalline lattice is a demonstration of this approach. Two integrated research themes are proposed focusing on understanding and manipulating strain fields towards controllable growth of APC/RE123 nanocomposite films for optimal critical temperature Tc and Jc in a strong magnetic field (H) approaching the theoretical depairing limit. Theme 1 will focus on modeling and simulation of the effect of Ca diffusion and cation replacement on the strain field in BaZrO3 1D-APC/RE123 multilayer nanocomposites, which will guide the sample synthesis by varying the nanocomposite structure design and processing parameters. Theme 2 consists of a workflow of characterization of strain field (Ca distribution and cation replacement, lattice constant, etc.) using advanced high-resolution electron microscopy-based characterization with the modeling and synthesis in Theme 1 to develop a machine-learning approach towards materials-by-design in superconductor nanocomposites for high, H-orientation independent Jc using a microscopic control of the strain field effect in APC/RE123 nanocomposites. The goal is to achieve a thorough understanding of strain-field guided Ca diffusion and cation replacement in tunning the strain field on the APC/Y123 multilayer nanocomposites towards achieving the Jd and a new material-by-design approach for a spectrum of functional ceramic materials. 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.