Oklahoma State University

NSF Awards · FY 2026 · 2026-07

This Faculty Early Career Development Program (CAREER) award will support the development of new methods for simulation-driven regional-scale risk and recovery assessment of civil infrastructure systems subjected to extreme and cascading natural hazards. Evaluating the vulnerability of infrastructure to extreme event scenarios is crucial for protecting lives, preserving economic security, and accelerating post-event community recovery. However, designing informative regional-scale computer simulations of such scenarios is challenged by the spatial and temporal variability of extreme events and their cascading threats to infrastructure. These challenges are compounded by the computational costs of high-resolution regional simulations and lack of scientific mechanisms to identify the most informative simulation scenarios. This project will address these challenges by developing a computational paradigm for designing uncertainty-informed regional-scale simulations, which will enable engineers to understand the consequences of cascading natural hazards and optimize the allocation of computational resources toward reliable infrastructure risk and recovery assessment. The project outcomes will advance national welfare and contribute to the National Science Foundation’s role in supporting the National Earthquake Hazards Reduction Program by improving earthquake risk assessment and recovery planning methods and understanding of the consequences of earthquake sequences on infrastructure. The research outcomes will be translated into computational tools for the natural hazard engineering community and educational materials on uncertainty quantification for engineering students and professionals. This CAREER award will address the fundamental gap between low-resolution probabilistic modeling and high-resolution physics-based simulations in the context of regional-scale analysis of infrastructure systems subjected to high-consequence low-frequency fault-rupture events and their cascading threats. The main contribution is a computational method for quantifying and reducing uncertainty in natural hazard engineering through adaptive acquisition of the most informative simulations or field data. The project will develop schemes for coupling physics-based and probabilistic simulations using the concepts of optimal design of computer experiments, information theory, and artificial intelligence models. The project has three objectives: (1) to optimize the design of physics-based simulations of cascading seismic events and distributed infrastructure systems using an uncertainty-informed regional sequential Bayesian experimental design framework; (2) to enable learning of infrastructure recovery trajectories and dependencies by integrating regional simulations, stochastic recovery analysis, and Bayesian network models; and (3) to optimize feedback loops between field-data acquisition and natural-hazard simulation using an adaptive spatiotemporal optimization scheme. The project outcomes will enable scientific discovery and engineering assessments in typically cost-prohibitive contexts, specifically: measuring through simulation the regional vulnerabilities and recovery trajectories of multiple infrastructure systems under cascading extreme events. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2026 · 2026-05

This Research Infrastructure Improvement (RII) EPSCoR Research Fellows project provides a fellowship to an Assistant Professor and training for a graduate student at Oklahoma State University (OSU). This work is conducted in collaboration with Prof. Babak Anasori at Purdue University. Through the fellowship, the principal investigator (PI) will investigate the formation of protective films at sliding interfaces via catalytic reactions on MXenes, a class of layered ceramics with excellent catalytic properties. These self-forming and self-healing films mitigate friction and wear, but the underlying mechanisms remain poorly understood. This award supports fundamental research to address this gap and provide needed knowledge for designing more effective catalysts. These catalytic materials could find applications in anti-wear and anti-friction coatings for harsh environments in aerospace, automotive, and energy industries. The project will also support education and training of a graduate student in advanced synthesis, microscopy, and chemical characterization techniques. Mechanocatalysis leverages mechanical forces to drive catalytic reactions. This project will focus on the design, synthesis, and characterization of MXene nanocrystals tailored to catalyze the conversion of hydrocarbons to carbon-based tribofilms. This research will address two questions: (i) how do surface terminations on MXenes affect their mechanocatalytic activity; and (ii) what are the mechanisms by which stress drives catalytic reactions on MXenes. The project methodology combines top-down selective etching with high-speed atomic force microscopy and in-situ Raman spectroscopy techniques, enabling quantitative measurement of the nucleation and growth kinetics of tribofilms at single-asperity nanocontacts. The results will provide insights into mechanochemical reaction pathways activated by MXenes. The fellowship visits will enable the PI to acquire expertise in the synthetic chemistry of MXenes, gain access to unique instrumentation, and forge new collaborations. These outcomes will be sustained beyond the fellowship period by establishing the MXene synthesis capability at OSU, which will stimulate new research, education, and workforce development activities in Oklahoma. This project is supported by the EPSCoR Research Infrastructure Improvement Program: EPSCoR Research Fellows, which supports early- and mid-career investigators in eligible jurisdictions to develop collaborations at the nation’s private, government or academic research institutions. 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 2026 · 2026-05

This award supports US-based graduate students and other early-career researchers participating in “Building Bridges: 7th EU/US Summer School on Automorphic Forms and Related Topics” (BB7), which will take place from August 10-15, 2026 at the Bedlewo Conference Center in Poland. The summer school explores the theory of automorphic forms, a field of study with a far-reaching impact that extends well beyond the field of number theory, and encompasses various branches of mathematics. The program provides early-career mathematicians high-level research training on cutting-edge topics, contributing to a robust and globally-connected workforce in the mathematical sciences. The summer school will feature three intensive mini-courses, on the analytic aspects of automorphic forms, theta lifts and arithmetic aspects of automorphic forms, and the relationship between Galois representations and hypergeometric functions, respectively. The program pairs morning lectures with afternoon collaborative problem-solving sessions to bridge the gap between foundational theory and current research. This structure facilitates knowledge transfer from world-class experts to early-career researchers. To provide a permanent, open-access resource, comprehensive course notes will be published on the BB7 website, advancing the field of number theory and enhancing the technical proficiency of US participants. More information can be found on the following website: https://bb7.wmi.amu.edu.pl/ 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 2026 · 2026-04

Vortex rings are swirling fluid structures that appear in many natural and engineering flows. Applications include the way the heart moves blood to how jets cool hot surfaces and control airflow over vehicles. The interactions of vortices with a surface determine how heat is transferred, how fluids mix, and how forces develop. Most current understanding of this process comes from studies of vortex rings interacting with flat or smoothly curved surfaces. In many real applications, vortex-wall interactions occur over surfaces with significant geometric corrugations. The effects of the local surface features on vortex behavior remain largely unexplored. This project will investigate how specially designed wavy surfaces influence vortex behavior. The research will examine whether surface shape can be used to guide and control flow outcomes. The results will provide new knowledge for designing surfaces to improve cooling and reduce energy losses in advanced manufacturing, energy, and transportation systems. The project will also train students in experimental and computational methods and engage K–12 audiences through hands-on demonstrations of fluid motion. The project will examine how local variations in the shape of a surface and the timing of incoming vortices work together to influence flow behavior. Carefully controlled experiments and computer simulations will be used to study these interactions. Vortex deformation, stretching, and interactions will be tracked as they encounter wavy surfaces. The study will measure how surface features affect pressure, flow separation, and the formation of new swirling structures near the wall. Single and repeated vortex interactions will be compared. The project will identify patterns that determine when vortices remain stable, reconnect, or break down. The research will generate high-quality datasets. These datasets will support development of data-driven models and artificial intelligence tools. The results will generate design principles for using surface shape and timed flow forcing to improve heat transfer in applications such as microelectronics and turbine cooling. The results will also provide guidance to enhance mixing in additive manufacturing and chemical processing and to control airflow over aircraft wings to reduce drag and noise. 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 2026 · 2026-03

Today, analog circuit debugging is a daunting task because of its manual nature and heavy reliance on experience. A manual root cause search is time-consuming, which creates a profitability issue for the semiconductor industry by delaying time-to-market and time-to-revenue. Over-reliance on human subject matter experts also poses a workforce challenge: if experienced experts leave or retire before new engineers are fully trained, critical knowledge may be lost. This research seeks to address both problems by building an artificial intelligence (AI)-based virtual expert to help people think. This project also investigates how to provide privacy guarantees to debugging queries when using cloud-based, closed-source large language models. This research has the potential to increase the economic competitiveness of U.S. semiconductor companies by boosting productivity through automation, leading to cheaper and more advanced sensors, smartphones, and mobile devices for everyone. Privacy research will also protect company intellectual property, another competitive advantage of the U.S. semiconductor industry. This project aims to automate analog circuit debugging through human-AI collaboration. Specifically, this research focuses on the architectural and algorithmic foundations within various AI technologies for analog experience accumulation, representation, and delivery to novices during human-AI collaborative debugging to expedite bug localization. The project tasks include designing retrieval-augmented generation for single-step root cause recommendation, multi-agent systems with conflicting goal management (hypothesis generation vs. problem-space reduction) to balance intuition with pragmatism during multi-step debugging, and differential privacy-based security guarantees for bug-related information. This CAREER project tightly integrates research and education by using research artifacts (e.g., AI copilots) to improve debugging education at both the college and K-12 levels. Educational activities will also use and generate real-life data for research. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2026 · 2026-02

Many aquatic organisms use a technique called metachronal rowing to swim. They use their paddle-like appendages to row in a coordinated rhythm, starting from the rear and moving toward the front of the organism. Metachronal rowing is observed in organisms that range in size from single cells to large crustaceans such as shrimp and krill. This project will use experiments and computational modeling on live animals and metachronal rowing vehicles to explain why this swimming technique works regardless of organism size. By examining how animals of different sizes optimize their swimming appendages, this research will help design underwater vehicles that can efficiently operate over broad ranges of sizes and speeds. Undergraduate and graduate students will receive cross-disciplinary training in fluid mechanics, robotics, and scientific computing. New summer camps on bio-inspired engineering will be developed for high school students. This project will elucidate the fluid dynamic principles that enable thrust and lift generation by metachronal rowing across an astounding seven orders of magnitude in paddle-scale Reynolds number from strongly viscous (0.01) to inertially dominated (10,000) flow regimes. Previous studies of metachronal rowing have considered tethered paddling without body motion for a limited Reynolds number range. Flow visualization and force measurements will be performed on state-of-the-art dynamically similar remotely operated vehicles to examine the flow physics, swimming performance and scalability of metachronal rowing across the biologically relevant range of Reynolds numbers. Computational simulations will be conducted to examine fluid-structure interaction in untethered metachronal swimming and evaluate the cost of transport for varying Reynolds number, paddle geometry and kinematics. The integrated experimental and computational approach will be used to test whether differences in the mechanical design and paddling kinematics of natural metachronal swimmers can facilitate efficient locomotion in their specific flow regime. The findings can guide the development of new bio-inspired autonomous underwater vehicles that provide efficient propulsive performance across broad ranges of sizes and speeds. 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 2026 · 2026-01

This Research Infrastructure Improvement EPSCoR Research Fellows project provides a fellowship to an Assistant Professor and training for a graduate student at Oklahoma State University (OSU). This work is conducted in collaboration with Prof. Stanislav I. Stoliarov at the University of Maryland (UMD). Water remains the most widely used firefighting agent, but it is often ineffective against lithium-ion battery and wildland fires, especially in drought-prone and rural areas with limited water supply. This highlights the urgent need for new suppression technologies. Through this fellowship, the PI will use advanced bench-scale testing to accelerate the development of thermo-responsive, water-efficient hydrogels as next-generation fire suppression agents. The project will strengthen OSU’s research infrastructure and support the goals of the NSF EPSCoR program through collaboration with UMD. Students will benefit from access to cutting-edge facilities and hands-on, interdisciplinary training. This effort will contribute to workforce development in fire safety engineering, materials science, and emergency response. Thermo-responsive hydrogels show promise as eco-friendly file suppression agents, but their application is limited by unoptimized formulations and gaps in understanding of their thermophysical properties and interactions with fire. This fellowship will advance hydrogel-based fire suppression through a collaboration between OSU and UMD, combining innovative material development with advanced fire testing. The project has three aims: 1) optimize hydrogel formulations for thermal resistance, adhesion, and cooling; 2) evaluate performance in bench-scale tests simulating wildland and battery fires; and 3) investigate suppression mechanisms to understand how formulation components influence effectiveness. This work will provide insights into hydrogel-fire interactions, guiding the development of next-generation agents with improved field applicability. Beyond advancing fire safety science, the project will strengthen Oklahoma’s research capacity, enhance public safety, and inspire future STEM learners through community engagement and hands-on training. This project is supported by the EPSCoR Research Infrastructure Improvement Program: EPSCoR Research Fellows (ERF), which supports early- and mid-career investigators in eligible jurisdictions to develop collaborations at the nation’s private, government or academic research institutions. 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 · 2025-10

Even though global leaders have made clean water a top priority through the United Nations Sustainable Development Goals, millions of people around the world still struggle to get safe, affordable drinking water. This ongoing crisis is a major challenge for governments, scientists, and nonprofits alike. Solving it isn’t easy - it involves a mix of environmental, social, and economic factors and demands teamwork across many different fields. This research project helps prepare U.S. students who are studying water resources and environmental science to meet that challenge. Over the course of three years, student-led projects - carried out in partnership with colleagues in South Africa - explore how ecosystem-based conservation and management approaches can provide low-cost, flexible, and sustainable ways to improve water security. Through this experience, students develop practical scientific and communication skills by taking part in online training courses, in-field data collection and analysis, professional meetings, and public outreach. In the process, they also learn how to work across cultures and disciplines - essential skills for solving complex water problems both abroad and at home. Addressing global water-related challenges requires that future leaders have a strong understanding of complex socio-hydrological systems and the feasibility to address water insecurity through decentralized approaches. This IRES project equips emerging U.S. hydrologic and environmental scientists with the skills to conceptualize and carry out field-based Nature-based Solutions (NbS) research on decentralized water solutions, communicate their findings effectively, and work collaboratively in an international setting. Research activities are based at the Water Hub, an established living lab outside of Cape Town, South Africa. This lab and location are ideally suited to understand the compounding challenges and opportunities inherent to meeting water security goals. Eighteen U.S. undergraduate and early-stage graduate students (six per grant year, for five weeks each summer) are investigating the suitability and application of NbS in addressing water pollution and contributing to watershed and community resiliency. Students are developing independent research projects, working with students from South Africa, and receiving mentorship by scientists from South Africa. The intellectual merit of this research lies in the integration of physical hydrology, environmental chemistry, and Geographic Information Systems to understand how informal settlements contribute to degraded stream water quality and to determine the effectiveness of NbS to improve water quality and contribute to a positive economy. Each cohort builds upon past research, working to determine (a) the timing and load of contaminants in streams adjacent to informal settlements; (b) the dynamics of related surface-groundwater interaction to model potential and real groundwater contamination; (c) the efficacy of various natural mediums to remediate contaminated surface water; and (d) the viability of using re-claimed water to irrigate community gardens. The broader impacts of this project include the development of global competencies and skills for three cohorts of students from U.S. institutions and greater knowledge of the linked social and environmental systems leading to better investment decisions by government officials and non-profits addressing water insecurity in urban areas of the Global South. This knowledge also benefits U.S. communities and decision-makers seeking decentralized approaches to solving water security challenges. 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 · 2025-10

The process-defect relationship is one of the key elements to the certification of additive manufacturing (AM) parts, which has been a major challenge in accelerating AM technology deployments in the industry. Advanced machine learning methods that leverage massive data to characterize the process-defect relationship have been studied for AM certifications. However, some AM fabrications and certification courses, especially for high-valued metallic parts, are lengthy and costly; thus, if the certification could be transferrable between different AM systems, it may greatly broaden the industrial use of AM technologies. Though feasible in theory, combining data from multiple AM systems on a shared platform for the certification purpose is not practical because of the desire to protect intellectual properties and sensitive data. What is lacking, therefore, is a holistic strategy to share knowledge learned from different AM systems without compromising the private information. This Faculty Early Career Development (CAREER) award supports fundamental research on privacy-preserving AM process-defect modeling and certification means across different systems. The project aims to establish a transfer learning groundwork, while protecting the process and part confidentiality, to understand and establish the process-defect relationship in metal AM between different systems. In addition, educational activities closely integrated with the research will provide basic training in privacy-preserving manufacturing systems modeling to next-generation manufacturing engineers from diverse groups, including minorities and women. Current data-driven AM certification schemes largely focus on characterizing the process-defect relationship of individual systems (i.e., one model for each single system and not generalizable to other systems, even similar ones). Although the state-of-the-art transfer learning methods can leverage data collected from multiple machines for cross-system studies, the research need is to maintain certain confidentiality—for both the part and process—to realize such collaboration. The goal of this project, hence, is to advance the scale-up of metal AM technologies by establishing a data-sharing platform, which enables process-defect modeling among multiple AM systems without divulging critical part and processing data. If successful, the major contribution of the research project will be a privacy-preserving transfer learning framework derived from the following research activities using directed energy deposition AM as an example: 1) constructing masked process features through de-coupling variability components assignable to product designs and process quality using a physics-informed tensor decomposition method, 2) establishing cross-system process-defect relationship through multi-task transfer learning to characterize intra- and inter-system variability and 3) enhancing AM certification capability by integrating part-level density and process-level thermal data based on fundamental physics principles. This project is jointly funded by the division of Civil, Mechanical and Manufacturing Innovation (CMMI) 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 2025 · 2025-10

Data centers (DC) are the backbone of the modern digital economy, critical to the U.S. economical growth, national security, public health, and enhanced data security and management. DCs are an energy intensive infrastructure, accounting for over 4% of total electricity use worldwide. As demand for AI and cloud computing grows, efficient cooling systems are critical to ensuring reliable and resilient DC operations. A critical failure in DC cooling systems can have catastrophic consequences, including total system shutdown, loss of data, and IT equipment. To prevent such catastrophic events, novel Fault Detection and Diagnostics (FDD) and mitigation techniques are essential. Currently, most FDD methods rely on conventional statistical techniques, machine learning models, or ad-hoc estimations. However, these methods are often limited in scope and may fail to detect rare or complex failure scenarios – particularly those arising from complex cascading events or malicious cyber-attacks. To tackle this challenge, this project develops a new FDD method based on failure and cyber-attack detection in supervisory control theory of discrete event systems. The intellectual merits of this project are: (1) new FDD methods for detecting and mitigating cascading faults and cyber-attacks resulting in resilient DC cooling system operation, (2) an open-source virtual testbed for evaluating performance of the proposed algorithms, and (3) a hardware-in-the-loop testbed to understand the challenges of FDD-enabled controls in real-world DC cooling equipment. The broader impacts of this project include new FDD methods to transform conventional DC cooling system design and management into future resilient DC cooling infrastructure and a field-validated computational framework for advanced FDD analysis of resilient cyber-physical infrastructure. By integrating the event-driven supervisory control and physics-based modeling, the goal of this project is to develop a field-validated, FDD-enabled, model-based control and computation framework for the robust design and reliable operation of next-generation resilient DC cooling systems. The proposed FDD method: (1) identifies, analyzes, and captures complex dynamics of benign and malicious faults, with rigorous detection guarantees, (2) characterizes critical attack vectors that pose a severe threat to cooling system management and DC operation, and (3) generates robust, real-time control responses that enable adaptive system adjustments to sustain normal cooling operation during major disruptions. The findings of this research are expected to have a broad range of real-world applications, particularly in design and development of attack-resilient DC cooling infrastructure across the United States and can be used by DC developers, technology companies, utilities, and HVAC manufacturers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

The construction industry--which increasingly relies on rapidly evolving technologies related to Artificial Intelligence and building information modeling--remains vital to economic development across the United States. Although this industry accounts for a significant proportion of the Gross Domestic Product, there are few empirically-based approaches that foster pathways to high-demand, lucrative construction careers among K-12 learners. To address this issue, this conference will bring together construction industry members, K-12 educators, educational researchers, extension specialists, and instructional designers to identify promising approaches and trajectories for STEM (Science, Technology, Engineering, and Mathematics) learning that builds youths' awareness of, interest in, and competencies related to construction careers of the future. This conference will focus on rural regions, given the need for continued infrastructural and economic development in these regions, and given the unique educational circumstances faced by many rural schools. Conference participants will use cutting-edge technologies while engaging in STEM practices on construction sites, in addition to participating in interactive and vision-setting conference sessions. They will discuss innovative and effective strategies for supporting K-12 youth in using emerging and evolving technologies, as embedded within STEM practices, in preparation for construction careers. Syntheses from the conference discussions will be shared with relevant networks of practitioners and researchers, such as 4-H Extension Networks. In this collaborative project, several institutions will host a two-day in-person conference, with virtual elements, on advancing practice and research related to K-12 STEM learning for the construction industries of the future. K-12 educators, who currently teach innovative construction practices in the context of STEM learning, will partner with construction industry members to generate and share ideas related to promising educational practices, particularly in rural regions across the United States. A mixed-method modified Delphi study will be used to ascertain and synthesize expert opinions on technology-infused K-12 learning that can foster US global leadership in the construction industries of the future. Results will be disseminated through high-traffic, peer-reviewed curricular repositories used by K-12 educators; through state, regional, and national professional organizations that serve practitioners in rural settings; and through national networks of STEM educators and educational researchers. This project is funded by the Innovative Technology Experiences for Students and Teachers (ITEST) program, which supports projects that build understandings of practices, program elements, contexts and processes contributing to increasing students' knowledge and interest in science, technology, engineering, and mathematics (STEM) and information and communication technology (ICT) careers. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Quantum technology and artificial intelligence (AI) are transforming how we live, work, and communicate. From self-driving cars and medical diagnostics to secure communication and powerful new computers, AI and quantum technologies are reshaping industries and creating new opportunities. These technologies have led to tremendous growth in several sectors, with private and public investment in these areas exceeding $250B in 2024 and expected to exceed $500B in 2025. However, this rapid pace of innovation and growth has outstripped the supply of skilled professionals. This National Science Foundation Research Traineeship (NRT) award to Oklahoma State University (OSU) will address this demand by training graduate master’s and doctoral students in the interdisciplinary fields of AI and quantum technology. This will create a vibrant community of researchers and communicators who will tackle challenges at the frontier of discovery and design. The project anticipates training more than 100 graduate students, with 30 students on full stipends (annual salary and paid summer internships) and an additional 70 students engaging with several dimensions of the program’s training cycle. The program will draw students from the OSU Ph.D. and M.S. programs in Physics, Computer Science, Mathematics, Materials Science, Engineering, and Photonics. The OSU NRT Program will address critical gaps in STEM graduate education by restructuring and refocusing graduate education to increase breadth of interdisciplinary knowledge, implementing internships, developing needed professional skills, and maintaining depth of specialization with no change in time-to-degree. The trainees will actively engage in experiential learning via project-based research and internships with industrial partners and at national laboratories, organized to align with important questions in three integrated research focus areas: artificial intelligence, quantum information science, and functional materials. These areas align with the existing strengths of core participants and across departments at OSU. In addition to transdisciplinary coursework in quantum technologies and AI, trainees will benefit from a team practicum and group rotations, engage in annual skills workshops, attend an Expert Visitor seminar series, work with industrial partners and national laboratories as part of internships, and gain leadership experience as part of shared governance and peer mentoring. By reimagining graduate education, this program will produce a new generation of scientists and engineers equipped to solve complex problems and lead in emerging technology sectors. The NSF Research Traineeship (NRT) Program is designed to encourage the development and implementation of bold, new, and 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 2025 · 2025-09

This Major Research Instrumentation Program (MRI) award supports the acquisition of a high-velocity cold spray manufacturing system at Oklahoma State University (OSU) to advance multidisciplinary research, education, and training in advanced manufacturing. Cold spray manufacturing enables 3D printing of net-shaped structures with complex geometries, the deposition of coatings to enhance surface properties, and the repair of damaged components. The research enabled by this equipment looks to address challenges in applying cold spray to a wide range of engineering materials and applications, potentially leading to faster, more economical, resource-efficient, and energy-saving manufacturing processes. The equipment will support research projects of multiple investigators and students across OSU and partner regional universities. It will also be made available to researchers at a nearby U.S. Air Force base as well as to manufacturing, aerospace, and advanced materials industries, and scientists from national laboratories. Additionally, the equipment will support the education and career development of multiple early-career faculty, postdoctoral scholars, graduate students, and undergraduates by providing access to advanced manufacturing capabilities. It will also facilitate experiential learning opportunities in multiple courses across mechanical, materials, aerospace, and industrial engineering programs. The cold spray manufacturing system seeks to enable new fundamental research in advanced manufacturing, integrating mechanics, materials science, fluid dynamics, surface engineering, tribology, and bioengineering. The research projects supported by this award include investigations into the physics of impact bonding of microparticles; high strain rate deformation mechanics of metals and polymers; multiphase flows consisting of solid particles in gas; microstructure evolution in nonequilibrium solid-phase processing of metals; mechanisms of wear and corrosion under extreme environments; regulation of cell adhesion, proliferation and differentiation on implant surfaces; and data-driven modeling for additive manufacturing. These coordinated multidisciplinary research efforts aim to close critical knowledge gaps in processing-microstructure-properties relationships in cold spray, guide the design and processing of high-performance alloys, polymers, and composites, and enable predictive models for large format additive manufacturing using cold spray. The innovative research projects, along with the educational and training programs, will contribute to both advancing fundamental knowledge and developing a skilled workforce in the critical area of advanced manufacturing. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

With support from the Chemical Structure and Dynamics (CSD) program in the Division of Chemistry, Professors Pinar Akcora of the Stevens Institute of Technology and Jindal Shah of Oklahoma State University will combine experimental and computational techniques to study the motion of ions in mixtures of ionic liquids and polymers, called ionogels. Ionic liquids are solvents comprised solely of ions. When combined with polymers at high concentrations, the interactions between the ions and the polymer cause the structure of the mixture at a molecular level to be nonuniform, potentially giving rise to ionic conductivity gradients. Professors Akcora, Shah, and their students will combine neutron spectroscopy and dielectric spectroscopy with atomistic simulations to link polymer-ionic liquid interactions with ion distribution and ion transport in ionogels. Their discoveries could provide ways to regulate conductivity with potential applications in ionotronics, sensors and biomedical devices that require strength, conductivity and flexibility. The project will provide research opportunities for graduate students, as well as planned outreach activities for students of all ages, which will promote scientific curiosity and contribute to the development of a STEM workforce. This project will use neutron scattering and dielectric spectroscopy measurements coupled with atomistic simulations to explore the structure and dynamics of mixtures of uncharged and charged polymers with ionic liquids. The ion distribution and conformation of ionic gels will be explored to interrogate the role of dynamic heterogeneities in the system. These studies will allow us to identify molecular origins underlying nonuniform swelling, crosslinking and structure-dependent ion transport in ionogels. The specific objectives are to understand the role of ion-dipole interactions on chain conformations in polymers differing in chemistries; determine the relationship between ion correlations and ionic transport; analyze the field-induced ion distribution in gels; and measure and simulate the ion distributions within ionic liquid and polymer brush interphases. Understanding the structure and dynamics in gels will enable the design of novel structured ionogels that could have implications for applications in sensing and biomedicine. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

Metals are essential for the development and advancement of our society, but their presence in natural environments is a double-edged sword- acting as vital nutrients at low concentrations but becoming toxic at elevated levels. The concentrations of many metals in soils, sediments, and aquatic environments are controlled by biogeochemical processes involving manganese (Mn) oxides. While microbial activities promoting Mn oxide formation in bacteria are well understood, the role of metals - particularly in fungi-mediated biomineralization – remains unclear. Despite fungi’s high abundance and metabolic activity, major knowledge gaps exist in our understanding of how they affect Mn oxide formation and how metals in return affect fungal biomineralization processes. This project seeks to unravel the interactions between common bivalent metals, fungi, and biominerals, providing insights into bioremediation strategies and environmental metal cycling. In addition to its scientific contribution, the research will incorporate educational components to address issues of student recruitment and retention in interdisciplinary fields within geoscience. A comprehensive set of outreach activities will be developed to engage the public and students at multiple levels, emphasizing the importance of interdisciplinary geoscience research and its relevance to our environment. Biogenic Mn oxides play an important role in metal cycling but the mechanisms of how metals affect fungal biomineralization remain poorly understood. The overall goal of this project is to elucidate the roles of common bivalent metals on the fungi-mediated Mn oxide biomineralization process, subsequent biomineral structure transformation, and bivalent metal sorption mechanisms. A systematic approach will combine laboratory-based wet chemistry, advanced structural characterization of biominerals, and molecular biological techniques including proteomics and transcriptomics to identify the key reaction products involved in fungal Mn oxide biomineralization process. The proposed study will ultimately contribute to the development of cost-effective bioremediation strategies and inform models predicting metal cycling in natural settings. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-09

The demand for robust, reliable, and flexible energy sources will continue to increase in the United States. In order to satisfy consumer, industry, and technology demands for global competitiveness, the domestic energy grid must bring on many new reliable energy sources. This planning project will invoke fundamental and applied expertise in energy science and engineering to develop a research project that will lead to the implementation of hydrogen as a reliable but sustainable energy carrier that otherwise might be lost due to difficulties in capturing and storing waste energy from traditional sectors like hydrocarbons and wind. By working with potential and existing academic, industry, and state partners in the planning stages, new technologies can be identified that can be integrated into the existing energy landscape. This work will lead to the development of a long-term project that has the potential to create new energy output while simultaneously creating new workforce opportunities. It is anticipated that hydrogen can sustainably mitigate the loss of produced energy both from hydrocarbon and renewable sectors in Oklahoma. The project aims to facilitate new energy and workforce sources statewide. The project will be led by the Oklahoma State University in collaboration with the University of Oklahoma and Southwestern Oklahoma State University. In Oklahoma, existing energy production results in lost or wasted energy through combustion of waste methane from oil and gas exploration, stranded electrons in wind production, and loss of critical elements like lithium and rare earth metals from produced water associated with hydrocarbon production. Hydrogen (H2) can provide a robust, flexible, and widely-deployable route to harvest and capture this waste energy, while simultaneously introducing new technology to potential corporate and state government partners that play key roles in diversifying energy production and distribution in Oklahoma. During the planning project, the team will explore the development of two key emerging energy areas that can, with appropriate research advances, lead to (1) new CO2-free hydrogen supplies via conversion of waste hydrocarbons, and (2) new hydrogen supplies from wastewater using waste electrons from existing wind production, with ancillary recovery of critical and rare-earth elements for battery and electronics production. This project is supported by the EPSCoR Research Infrastructure Improvement Program: EPSCoR Research Incubators for STEM Excellence (E-RISE), which supports the development of sustainable research infrastructure and capacity in EPSCoR jurisdictions through collaborative, hypothesis-driven, or problem-driven research and workforce development to improve competitiveness in selected STEM fields. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

The Great Plains region faces an ever-increasing need to conserve dwindling water reserves from the Ogallala aquifer. The same region also annually generates more than 80% of the country’s total livestock wastes (dairy, beef, swine), raising concerns about the impact on water quality and living conditions. About 12– 35% of the water used annually for production-intensive agriculture in Kansas, Nebraska, and Oklahoma combined (8 M acre-ft/yr) can potentially be derived by recovering and treating water contained in livestock waste. A team of interdisciplinary researchers from Kansas State University (KSU), Seward County Community College (SCCC), Oklahoma State University (OSU), and the University of Nebraska-Lincoln (UNL), representing three contiguous EPSCoR jurisdictions, will synergize their complementary research capacities to enable adoption of circular waste resource recovery and water reuse technology platforms. This research will enhance economic resiliency, environmental sustainability, and quality of life in Great Plains micropolitan communities. The overall project objective is to build regional research capacity and develop an economically viable, socially accepted, and efficient circular resource recovery platform integrated with water reuse from livestock wastes that are copiously generated in the region. The proposed work would build capacity for use-inspired research to be demonstrated for adoption by livestock operations in southwest Kansas first (Liberal, KS), in collaboration with SCCC, and with regionwide adoption potential. The project will integrate a wide array of workforce development activities such as an early-career faculty development program and technical skills training through exchange site visits. Workforce development initiatives will be guided by an industry-government advisory council composed of livestock and agricultural producers, local associations and councils, and government/policy representatives. During this project, critically important and complex concepts such as resource recovery will be introduced to participating students and the public through science cafés, summer research field experiences, and interactions with public utilities to realize the research advances at scale. This will enable a holistic framework and encourage incorporation of the circular resource recovery and reuse systems into the rural communities and workforce. This collaborative research team seeks to achieve optimal circular waste resource recovery and water reuse technology platforms through three interconnected research thrusts. Research Thrust 1 aims to develop the Anaerobic Sequencing Batch Reactor (ASBR), Anaerobic Membrane Bioreactor (AnMBR), and Microbial Electrochemical Cell (MxC) platforms for holistic recovery of swine manure co-digested with fats, oils, and grease (FOG) to produce methane or organic acids, hydrogen peroxide, nutrients (N and P) as tunable-release inorganic fertilizers (Octacalcium phosphate and struvite), and treated water for reuse. Such groundbreaking advancements in membrane science will be guided by Artificial Intelligence/Machine Learning. Research Thrust 2 focuses on circular water reuse by combining advanced oxidation and membrane-based processes, including using waste-derived hydrogen peroxide to produce high-quality water. Specific focus will be placed on mitigating antimicrobial resistance, a prevalent and understudied issue in rural water supplies. Research Thrust 3 will integrate techno-economic and risk simulation with agribusiness decision node modeling for region-specific adoption of the circular systems. Human dimensions, including cultural perceptions, assessments of safety and security risks, and social-economic impacts of the proposed technologies, will be analyzed from representative communities. Collective research capacity from the contiguous jurisdictions will be synergized and verified through a field demonstration of the AnMBR + advanced oxidation unit at Liberal, KS, in Year 4 of the project. New avenues for cross-convergent research between applied and pure science-based researchers as well as potential manufacturing and industry partners will be achieved throughout this proposal. Synergistic research that co-addresses engineering grand challenges and society-based sustainable development goals, such as responsible consumption and production, clean water and sanitation, will also be demonstrated. This project is supported by the EPSCoR Research Infrastructure Improvement Program: Focused EPSCoR Collaborations Program (FEC). FEC supports interjurisdictional teams of EPSCoR investigators to perform research in topics that align with NSF priorities, with the goals of driving discovery and building sustainable STEM capacity. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

The Paleocene-Eocene Thermal Maximum (PETM, 56 million years ago) is an important paleoclimate event used to understand how Earth’s climate system responded to rapid increases in atmospheric methane and carbon dioxide. One approach to study this interval is chemical analysis of microfossils known as foraminifera preserved in deep-sea sediment. Foraminifera grow calcium carbonate shells that record the environmental conditions of the organism’s habitat. However, PETM foraminiferal records suffer from two well-known limitations: first, ocean acidification at the PETM onset can lead to the dissolution of the carbonate shells and, second, vertical sediment mixing (bioturbation) can intermingle shells from different time periods together. Until recently, vertical mixing was a significant drawback because analyses required multiple shells to have sufficient accuracy. This project will remedy those issues by constructing records of individual foraminiferal geochemistry and morphology across the PETM at International Ocean Discovery Program (IODP) Site U1580 located on the Agulhas Plateau in the Southern Ocean. Site U1580 features abundant microfossils that were not dissolved. Cutting-edge analytical techniques will permit measurements on individual foraminifera to disentangle signals affected by bioturbation. Results will produce new estimates of surface and deep-water warming and carbon cycle dynamics across the PETM onset. The proposed work will support a team of three early career researchers plus graduate students and postdoctoral scholars. The project integrates educational outreach; investigators will create an open educational resource on the PETM and its relevance to contemporary climate. The presence of well-preserved foraminifera throughout the PETM onset at IODP Site U1580 offers a unique opportunity to reconstruct the magnitude, pace, and dynamics of climate change during the earliest phases of the PETM. However, pilot data demonstrate extensive vertical mixing of individual foraminifers across the event (as observed at other sites). The investigators will disentangle vertical sediment mixing by applying a series of measurements performed on individual shells. Shells will first be imaged by Scanning Electron Microscopy (SEM) and Computed Tomography (MicroCT) to characterize preservation and document morphology. Shells will then be analyzed for Mg/Ca (a paleotemperature proxy) via Laser Ablation Inductively Coupled Plasma Mass Spectrometry, then finally analyzed for their stable carbon and oxygen isotopic composition using a new CryoFocusing technique adapted for small carbonate samples. The resulting individual foraminifera carbon isotope data will distinguish pre-PETM from PETM individuals, allowing quantification of shell morphology, Mg/Ca-based temperature, hydrologic change, and the carbon isotope shift across the PETM onset. Any observed structure in the geochemical data will provide insight into the pace of change or lead-lag relationships between aspects of the carbon cycle and climate. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

The U.S. manufacturing sector is rapidly digitizing through the adoption of additive manufacturing (AM), the integration of cyber-physical systems, and the shift toward smart manufacturing. As manufacturing systems become increasingly connected and software-driven, innovation in processes and materials must be matched by robust cybersecurity measures to ensure system reliability, data integrity, and operational resilience. To meet these evolving demands, there is a need to create programs that train undergraduate students to address the growing shortage of engineers and scientists working at the intersection of advanced manufacturing and cybersecurity. This REU Site at Oklahoma State University, Stillwater, will recruit 10 undergraduate students each summer from 2026 to 2028 for a 10-week research and professional development program, drawing participants from across the country, including those from 2-year and 4-year colleges with limited access to research infrastructure in these fields. Students will work on structured, hands-on research projects of their choice at the intersection of advanced manufacturing and cybersecurity, mentored by OSU faculty conducting research in these areas. Students will also engage with industry professionals, manufacturing entrepreneurs, and national lab researchers through webinars and networking events. They will receive training in scientific writing, communication, and research methods, and will be guided by domain experts on pursuing graduate education or careers in these fields. Student research outcomes will address current, high-impact challenges in their chosen area, while the broader activities will support their development as future contributors to the advanced manufacturing and cybersecurity workforce. The specific objectives of this REU Site are to: (1) prepare students to perform independent research in AM and cybersecurity by immersing them in hands-on projects spanning bioengineering, energy storage, aerospace, and construction, as well as projects focused on securing interconnected AM systems; (2) promote interdisciplinary collaboration through lab meetings, peer engagement, and group activities; (3) broaden students’ understanding of AM’s societal and industrial relevance by facilitating interactions with researchers at national labs, entrepreneurs, and OSU alumni in the manufacturing sector; (4) strengthen students’ professional skill sets through structured workshops on ethical research, scientific communication, and graduate school preparation; and (5) support students’ long-term success in STEM by providing individualized mentoring, networking opportunities, and continued guidance beyond the program. Students will have opportunities to present and share their research findings through oral and poster presentations at the end-of-program REU Symposium, inclusion in final research reports submitted to faculty mentors, and potential dissemination through campus events or conference participation facilitated by the program. Program effectiveness will be assessed through pre- and post-program surveys, mentor evaluations, and focus group interviews, and student career trajectories will be tracked over time. Evaluation findings will be shared through education conferences, peer-reviewed publications, and relevant STEM education networks. This Site is supported in part by funds provided to the National Science Foundation by the Semiconductor Research Corporation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

Quantum simulation of many-body systems is a research area with important applications, from quantum information storage to the development of novel materials. This project will use ultra-cold sodium atoms to experimentally simulate complex quantum systems. The principal investigator (PI) and co-workers will explore applications of this simulator in quantum information science and quantum sensing. Additionally, the PI will integrate research and teaching by involving undergraduate and graduate students in research projects that will prepare students for a career in science and technology. The PI will also organize workshops for local high-school students to get hands-on experience with state-of-the-art quantum physics experiments. This award supports experimental quantum physics studies in a programmable spinor quantum simulator consisting of sodium spinor Bose-Einstein condensates. The proposed studies include investigating ergodicity breaking and novel nonequilibrium spin dynamics, realizing and characterizing quantum scars in a many-body system, generating massive entanglement, and exploring promising applications in quantum information science. This proposal thus provides an exciting opportunity to investigate nonequilibrium dynamics, ergodicity breaking, quantum scars, and the interplay of superfluidity, strong correlations, and quantum magnetism. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

Agriculture plays a crucial role in meeting the food and energy needs of our growing population. However, intensive farming practices can contribute to significant environmental impacts, such as groundwater depletion, soil degradation, and loss of biodiversity. At the same time, these farming systems are increasingly vulnerable to extreme weather events, such as droughts and heavy rainfall, driven by a changing climate. To ensure long-term sustainability, it is essential to balance crop productivity with environmental stewardship. This work focuses on understanding how farming practices impact both the environment and crop resilience under these challenges. Working closely with farmers, the project will develop an easy-to-use tool to help them make informed decisions that optimize productivity while minimizing environmental harm. Additionally, the project will foster education and mentorship through the creation of a mentorship network and connecting agricultural communities with the knowledge and resources needed to achieve more resilient and sustainable agriculture. The overarching goal of this work is to advance sustainable agricultural practices through research, education, and mentorship by integrating and advancing water footprint and environmental impact assessment tools. A critical challenge in agriculture is the lack of systems-level understanding of how farm management decisions impact the environment under variable and changing climate conditions. This proposal addresses this gap through three specific objectives: (1) quantify and assess environmental impacts of farm management decisions under variable climate conditions, (2) develop and implement a site-specific, user-friendly decision-making tool, and (3) establish and sustain a state-wide mentorship network to recruit and retain students. The underlying research hypothesis is that environmental impacts of agriculture will shift in response to climate transitions due to evolving management decisions, requiring site- and scenario-specific recommendations to minimize negative outcomes. To address this, the research integrates field measurements from an experimental irrigated cropping system under diverse management scenarios, process-based model calibration and validation, life cycle assessment, water footprint analysis, and projections under future climate scenarios. These efforts will culminate in the development of an online decision-support tool to help farmers make informed, sustainable decisions tailored to their specific conditions. The educational aim is to establish tools and networks for long-term learning and mentorship, with a particular focus on supporting neurodivergent students during educational transitions. This includes the creation of a multi-tiered mentorship program to promote broad engagement in environmental and agricultural fields. Together, the research, education, and mentorship efforts will enhance understanding of the interplay between agricultural management, climate variability, and environmental impacts, while fostering a robust, informed, and inclusive workforce dedicated to sustainable agriculture. This project is jointly funded by the CBET/ENG Environmental Sustainability 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 2025 · 2025-08

When a baby cries, parents respond quickly and know where their baby is immediately. However, how animals can find, or localize specific individuals, particularly those that are incredibly socially important like offspring or a partner is not well understood. A common hormone, oxytocin - that is involved in social bonds like with kids or partners – may tune a specific area of the brain to social sound information such as a baby’s cry. Dr. McCullagh’s lab will explore how oxytocin is involved in this area of the brain using a highly social animal called a prairie vole that forms bonds with their partner and shows parental care like humans. Dr. McCullagh’s project will have broad impacts on the community through a proposed course engaging students with neuroanatomical techniques at Oklahoma State University and a mobile interactive exhibit in partnership with local speaker company Kicker. The mobile “sound of science” exhibit will be brought to local schools and industry expos to engage the public with science in an approachable way. Dr. McCullagh’s CAREER award provides an integrated framework for using the auditory system to study important questions related to novel auditory processing mechanisms, as a tool for engaging undergraduates in research, and as a gateway for increasing excitement about science in the public and school system. Dr. McCullagh and her team propose a model in which oxytocin signaling in the sound localization circuit enhances neural sensitivity to allow for quick sound localization to social vocalizations. They will measure the sensitivity of the prairie vole auditory brainstem to different types of acoustic information using prepulse inhibition of the acoustic startle response and complex auditory brainstem response measures with the prediction that animals will be more responsive to prairie vole calls, particularly calls from pair-bonded mates, rather than socially irrelevant tones and that this sensitivity will be reduced or eliminated in oxytocin receptor knockout voles. For oxytocin to influence the auditory brainstem, it must project from other areas and have a cellular consequence. The researchers predict there are neural connections between oxytocin releasing neurons and the auditory brainstem. They will quantify oxytocin and oxytocin receptor expression in areas of the auditory brainstem. The researchers predict oxytocin must be acting through its receptor to change neural responsiveness at a cellular level in this circuit and will test this prediction through measuring auditory brainstem cellular responses in vitro during and after oxytocin application. These experiments will give insight into the mechanisms and connections through which oxytocin is acting on the sound localization circuit to enhance localization ability of specific individuals. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

This planning grant for the Energy-Related Geologic Storage (ERGS) Industry-University Cooperative Research Center (IUCRC) enables the interaction between university faculty and companies in the energy and subsurface fluid/gas injection sectors of the economy. Its goal is to identify mutual interests of both university faculty and companies that can lead to use-inspired, university-driven innovations and knowledge needed by industry to overcome hurdles that are holding it back from developing new products and services that benefit the economy and society. Activities include training university faculty in customer discovery and their developing a value proposition for Center research that aligns with critical industry needs and is capable of attracting investment from the private sector. The resulting industry-funded, use-inspired research focuses on global geological subsurface storage resources capable of securely containing buoyant fluids/gases critical for the energy and low carbon economy. Center research will also provide much needed understandings of processes, using AI, machine learning, and novel materials for well completion to prevent greenhouse gas leakage. It also develops solutions to address subsurface gas/fluid containment risks and mitigation for fluid/gas extraction and/or injection. Gases and buoyant fluids, subject to investigation, include, but are not limited to, hydrogen, compressed air, and methane. Broader impacts of the work include research that aligns with the critical needs of the U.S. energy and subsurface storage sectors of the economy and workforce training of students who are involved in the industry-aligned research activities. The new Center will enact integrative research that aligns with industry needs related to storage mechanisms, reservoir and drill hole integrity, and associated scientific and engineering issues that impact the geological storage and containment of fluids. The Center is motivated by the nation’s need to sequester the gases/fluids emitted, as a result of energy production, that need to be stored in secure, large volume, subsurface reservoirs. The Center will use a variety of machine learning techniques and AI to assess geological storage capacity and formation heterogeneities, and security. It will develop novel materials and drilling/wellbore completion techniques to provide for a secure energy and environmental future. The Center research team has extensive expertise in exploration geoscience for the energy industry and for the assessment of hydrocarbon resources. It also has engineering expertise in well drilling and borehole completion. Research will focus on analyzing sedimentary basin potential for storage and and risks related to geological factors such as subsurface faults and basin margin exposures. It will work to provide solutions that dramatically reduce and/or eliminate wellbore leakage and determining the leak potential of reservoirs. Research will utilize university faculty expertise and innovative ideas and approaches as well as university infrastructure of Texas A&M University and Oklahoma State University, the two Sites that form the Center. The research serves the national interest by promoting the progress of science and engineering and helps to advance national prosperity and national energy security. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-07

This research focuses on developing privacy-preserving collaborative design methods for additive biofabrication to advance US biomanufacturing goals. Additive biofabrication, a critical aspect of biomanufacturing, holds the potential to revolutionize healthcare by producing patient-specific medical solutions, and improving treatment outcomes. However, two key challenges must be addressed to fully realize the benefits: (1) accommodating the wide variability in patient-specific requirements, resulting in an infinite spectrum of potential products, and (2) protecting sensitive patient data throughout the manufacturing workflow. Current approaches rely on iterative experiments to refine product designs, a process that is both time-consuming and resource-intensive thereby limiting diversity and scalability. This research looks to accelerate the development of biofabricated products by establishing methodologies that enable secure knowledge transfer between manufacturing facilities while preserving data privacy. The developed methodologies will be assessed on a distributed computational testbed, as well as on a laboratory-based experimental testbed that will mimic two collaborating biofabrication facilities. This project will promote interdisciplinary research at the intersection of data analytics, privacy, and advanced manufacturing. Outreach efforts include industry engagement, curriculum development, and undergraduate research opportunities. This research pursues three interconnected objectives to develop the privacy-aware collaborative design framework for additive biofabrication. First, latent encoding mechanisms and a novel single-view fusion framework will be developed to integrate design data from multiple manufacturing facilities with heterogeneous capabilities. Second, differential privacy mechanisms will be incorporated to ensure strong privacy guarantees, preventing unintended leaks of design parameters during collaboration. Third, two testbeds will be established: a numerical testbed to evaluate scalability under varying privacy budgets, computational constraints, and temporal dynamics, and an experimental testbed to validate effectiveness in fabricating patient-specific bioengineered products. Overall, successful development of privacy-aware collaborative design framework looks to reduce existing barriers in design collaboration, advancing US biomanufacturing goals by reducing product development time and increasing the wide range of biofabricated products. 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 · 2025-06

The RET Site: Photonic Microchip Fabrication Experiences for Oklahoma Educators seeks to address the critical workforce needs in STEM fields by immersing eight high school and community college educators each year in a six-week research program focused on photonic microchip fabrication. By providing hands-on experience and foundational knowledge in microelectronic fabrication and photonics, the program will empower educators to develop curricula that will enhance STEM education and broaden participation in semiconductor-related fields. Through strategic recruitment and statewide collaboration, participants will engage in innovative research projects and professional development activities. By integrating cutting-edge research into classroom instruction, educators will be better prepared to inspire the next generation for high-tech careers, supporting the U.S. semiconductor industry, strengthening Oklahoma’s economy, and promoting national technological competitiveness. The primary objectives are to provide educators with hands-on experience in terahertz microchip fabrication and characterization at next-generation communication bands; enhance teachers' understanding of microelectronic fabrication and terahertz photonics; and develop curricula that integrate these research experiences into appropriate classroom instruction and lessons. Participating educators and their students will have access to on-campus Cleanroom facilities, where they will design and fabricate microchips, gaining practical skills in semiconductor processing. The program will also introduce terahertz photonics as an emerging field, enriching science education and fostering student engagement. Additionally, educators will develop pedagogical modules to make semiconductor education more accessible to all students. This kind of partnership between OSU and educators will lay the groundwork for sustainable semiconductor education initiatives that contribute to workforce development and technological advancement. 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.