Washington State University

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY In rheumatoid arthritis (RA), activated synovial fibroblasts (SFs) transform into an invasive phenotype that recruits immune cells to cause tissue destruction. Recent findings show transforming growth factor β-activated kinase 1 (TAK1) as a pivotal mediator of IL-1β, TNF-α, and Toll-like receptor signaling cascades due to its central position upstream of mitogen-activated protein kinases (MAPKs) and nuclear factor-κB (NF-κB) pathways. However, the molecular mechanism by which TAK1 regulates SF functions to promote RA pathogenesis remains unexplored. Using FAPα+Thy1+ RASFs, we showed that IL-1β-induced inflammatory signals are suppressed by inhibiting the TAK1 kinase domain (Thr184/187). Analysis of RNA sequencing data showed that the TAK1 kinase inhibitors type I (irreversible, 5Z-7-oxozeaenol, 5Z-7o) and type II (reversible, NG-25) significantly blocked the expression of inflammatory (IL6, CXCL9, CXCL1, NFKB1, and JUNB) and invasive (CDH11, PDPN, SOD2, PRG4, MMP1, and MMP3) genes in human RASFs. TAK1 inhibitors showed a marked inhibition of (IL-1β+TNF- α+IFN-γ)-induced IL-6, IL-8, MMP-1, and MMP-3 production and Cad-11, Cox-2, and PDPN expression. 5Z-7o and NG-25 triggered the nuclear translocation of TAK1 (Ser439) on the C-terminal domain, the function of which is not characterized. Immunoprecipitation of nuclear TAK1 followed by Western blot analysis showed its novel interaction with CBP/p300, PCAF, GCN5, and acetylated histone 3, suggesting a role for nuclear TAK1 in chromatin remodeling. In addition, K63-linked ubiquitination (K63-Ub), a post-translational mechanism that provides stability to signal proteins, was severely repressed in RASFs compared to non-diseased SFs (NLSFs) and inversely correlated with increased expression of CYLD, a deubiquitinase specific for hydrolyzing K63-Ub chains. Treatment of human RASFs with 5Z-7o or NG-25 enhanced K63-Ub proteins in a dose-dependent manner and transcriptionally inhibited IL-1β-induced CYLD expression. Administration of 5Z-7o or NG-25 (2 mg/kg, p.o. daily) for 10 days from the onset of the disease significantly ameliorated AIA in rats. However, several questions remain unanswered, including the nuclear function of the TAK1 C-terminal in chromatin remodeling, its contribution to the RASF invasive and inflammatory phenotype, and the molecular mechanisms of TAK1 regulation in vivo. Hence, we propose a hypothesis that TAK1 is central to RASF synovial inflammation, and targeting TAK1 functions may ameliorate RA. Hence, studies proposed in Aim 1 will determine the role of TAK1 in RASF functions and the effect of kinase inhibition on its nuclear translocation and interaction with chromatin remodelers. In Aim 2, we plan to understand the effect of TAK1 inhibitors on restoring K63-Ubiquitination to inhibit IL-1β signaling pathways in RASFs. In Aim 3, we plan to study the arthritogenic potential of TAK1 in RASFs and the mechanism of action of TAK1 inhibitors in collagen antibody-induced arthritis (CAIA) mice, and in fibroblast- specific TAK1 conditional knockout or overexpressing mice. These findings will provide a mechanism-based rationale for developing TAK1-targeted therapy for RA.

NIH Research Projects · FY 2025 · 2025-08

Sleep/wake disruption in Alzheimer’s disease patients significantly affects their quality of life, is a major contributing factor for institutionalization, and may represent a proximal cause of neurodegeneration and cognitive decline. Aging remains the biggest known risk factor for Alzheimer’s disease, and poor sleep patterns, which are often associated with aging, can also increase dementia and Alzheimer’s disease risk. Clinical studies have suggested a bidirectional relationship between sleep disruption and deposition of β-amyloid (Aβ), a small peptide associated with plaque formation in Alzheimer’s disease. Exactly how these protein aggregates influence molecular and cellular mechanisms to affect Alzheimer’s etiology are incompletely understood but may target changes in transcriptional processing. This study leverages a multifaceted approach to unravel the complex interactions between aging, transcriptional processing, protein aggregation, sleep disturbance, and cognitive decline using an APP/PS1 Alzheimer's disease rat model. We aim to investigate these interactions by incorporating innovative techniques, such as the use of single-chain variable fragments (scFvs) for evaluating protein oligomerization of Aβ, tau, α-syn, and TDP-43, proteins known to aggregate neurodegenerative diseases, alongside advanced transcriptomic analyses, to identify differentially expressed genes and pathways associated with protein deposition. We propose to integrate complementary RNA sequencing (RNA-seq), whole-transcriptome sequencing (WTTS-seq), and capped small RNA sequencing (csRNA-seq), to explore the transcriptomic landscape of Tg-AD and wild-type rats following changes in sleep pressure associated with cognitive decline using the Vibration Actuating Search Task (VAST) cognitive assay. By integrating these methodologies, we aim to provide a holistic view of cognitive and molecular predictors in the severity of Alzheimer's disease pathology. The results could provide significant insights into the molecular links between protein aggregation, sleep disturbances, and cognitive impairments, offering avenues for the development of novel treatment strategies for Alzheimer's disease.

NIH Research Projects · FY 2025 · 2025-08

PROJECT SUMMARY Fleas are obligate blood-feeding arthropods that are associated with several notable bacterial-derived human diseases, i.e., rickettsioses, bartonelloses, and plague. Plague caused by the Gram negative bacterium, Yersinia pestis, is difficult to eradicate because flea-borne transmission is endemic in natural foci of wild rodents and their associated fleas world-wide. Insecticide control is the primary strategy for disease management, but like many vector-borne diseases this is compromised by development of insecticide resistance in fleas. Development of novel vector-based strategies for bacterial pathogen control are therefore a priority. However, to accomplish this, we must overcome lack of knowledge regarding flea biology, particularly the detailed processes of the flea host response to infection. But genetic tools enabling such research into this knowledge gap are absent. Towards this goal and to enable previously inaccessible, yet essential, mechanistic research into understanding the transmission biology of flea borne plague in future studies, this proposal aims to develop RNAi-mediated gene silencing methods for Xenopsylla cheopis, a primary flea vector of plague. The biggest hurdle to effective RNAi-mediated silencing in any arthropod is achieving delivery of exogenous double-stranded (ds) RNA into the cell cytoplasm to induce specific gene silencing by targeting homologous mRNAs. No one effective delivery method is currently broadly applicable to all arthropods, requiring that methods be tested and optimized. Having identified X. cheopis gene target/s in the IMD immune signaling response are specifically implicated in response to Y. pestis infection, appropriate gene targets are now available to which RNAi strategies can be developed and tested. Our preliminary experiments demonstrate significant silencing of the IMD gene by electroporation and microinjection methods of dsRNA delivery. Therefore, in Aim 1 we will determine the most feasible dsRNA delivery method that enables a high degree of and sustained gene suppression in flea gut- specific tissue (the site of a Y. pestis infection), as well as low mortality in fleas. In Aim 2 we will use the most effective method identified to determine if IMD pathway silencing modulates Y. pestis infection rates and burdens in fleas. The proposed development of a genetic tool to expand research into flea borne plague lies within a part of the NIH’s mission to develop fundamental knowledge that will assist in reducing the burden of infectious diseases on human health.

NIH Research Projects · FY 2026 · 2025-08

Project Summary The delivery of small molecule therapeutics across the blood brain barrier (BBB) is difficult, making the development of therapies for neurological diseases very challenging. Even if the drugs or nanoparticles cross the impaired BBB following brain injury, targeting key cells involved in the brain diseases, such as, neurons present significant challenges. Targeting neurons is specifically complex since they are far lower in number and less phagocytic in nature compared to the glial cells. Moreover, neurons exist in a variety of types that perform specific functions in the brain which makes targeting specifically the injured neurons more difficult. We have designed and developed a novel tailor-made 2-deoxy-D-glucose (2DG) based glycodendrimer nanoplatform (2DG-D) that addresses these challenges by targeting and delivering drugs to neurons selectively at the site of brain injury. Our preliminary data suggest that the fluorescently labeled 2DG-D demonstrates neuronal targeting and specifically localizes within the neurons across the BBB at the site of injury in the brain from systemic administration in a mouse model of pediatric traumatic brain injury (TBI). The 2DG-D technology is designed to selectively deliver high payloads of drugs to affected neurons and microglia across the BBB, and to simultaneously achieve in vivo stability, high water solubility, ease of scalability, and flexibility in single or multiple drugs delivery. Our unique platform builds on our expertise in designing clinically relevant nanomaterials for drug delivery applications. We further show that a single systemic dose of a conjugate of 2DG-D and pioglitazone (Pio) a PPAR- γ agonist (2DGD-Pio) improves behavioral outcomes and neuroinflammatory responses in a pediatric mouse model of TBI. Pio is an anti-diabetic drug being widely investigated for brain diseases, including TBI. However, its poor aqueous solubility and peripheral side-effects are a concern that can be addressed using 2DGDN mediated targeted delivery. The goal of this R01 proposal is to develop a neuron-targeting 2DGD-Pio conjugate and validate the efficacy in pediatric TBI model to treat, preserve, and restore neuronal function, with significant implications for other brain disorders. Our ultimate long-term objective is to develop scalable, systemic 2DGD-drug therapies with improved efficacy and reduced systemic side effects that can be used not only for TBI but other brain diseases as well. We will achieve our goal through the following three aims: Aim 1: demonstrate reproducible synthesis and evaluate mechanism of uptake of 2DG and 2DGD-Pio conjugates; Aim 2: assess in vivo biodistribution, pharmacokinetics and toxicity of 2DG and 2DGD-Pio; and Aim 3: short and long-term efficacy of 2DGD-Pio conjugate in a TBI mouse model.

NIH Research Projects · FY 2025 · 2025-08

Project Summary Corneal neovascularization (CoNV) is a sight-threatening condition characterized by the growth of peri-corneal blood vessels into the normally avascular cornea, disrupting its normal anatomy and leading to corneal opacity. CoNV occurs in various corneal pathologies, including congenital corneal diseases, contact lens-related hypoxia, inflammatory disorders, chemical burns, limbal stem cell deficiency, and corneal graft rejection. Current treatments include medication and surgery. Options include amniotic membrane transplantation, argon laser, photodynamic therapy, fine needle diathermy, cautery, and pharmacotherapies such as topical steroids, immunomodulatory agents, calcineurin inhibitors, and non-steroidal anti-inflammatory drugs (NSAIDs). However, these are not consistently effective, often have adverse effects, and limited clinical efficacy. Cornea transplantation is considered as utmost solution for CoNV, but existing neovascularization at the border of the cornea may rapidly invade the new graft if left untreated. There is no curative therapy available for CoNV necessitating the need to develop novel therapeutic approaches. Growth factors such as vascular endothelial growth factor (VEGF), and platelet derived growth factor (PDGF), play key roles in the regulation of angiogenesis. Moreover, Src family kinase is the main player in angiogenic signaling cascades activated by these growth factors. Attenuating angiogenesis with inhibitors such as Dasatinib (Dasa) with dual PDGF receptor and Src family kinase inhibiting effects is a promising approach but suffers from drug delivery challenges and side-effects. We synthesized a unique trehalose-based dendrimer (Tre-D), that selectively targets blood vessels in cornea when administered via subconjunctival (SCJ) injection in a rat alkali burn model of CoNV. The Tre-D technology is designed to deliver anti-angiogenic therapies selectively to the blood vessels in cornea with reduced side-effects, and simultaneously achieve in vivo stability, low immunogenicity, high water solubility, ease of scalability, and flexibility in single or multiple drugs delivery. Importantly, a single SCJ administration (1µg, 50µL) of a conjugate of Tre-D with Dasa (Tre-D-Dasa) significantly suppresses neovascularization in rats with alkali burn induced CoNV compared to the free Dasa and Tre-D controls. Building on these positive preliminary results, and the pathology specific targeting of the Tre-D technology, the goal of this R01 proposal is to develop Tre-D-Dasa and validate its efficacy to treat pathological neovascularization. This will be achieved through the following specific aims: Aim 1: Synthesize and characterize Tre-D-Dasa and Tre-D-Dasa-Cy5 conjugates; Aim 2: Assess biodistribution, pharmacokinetics (PK), and toxicity of Tre-D-Dasa in the alkali burn rat CoNV model; and Aim 3: Determine the dose-response efficacy of Tre-D-Dasa in two clinically relevant models of CoNV (rat alkali burn and suture induced CoNV models).

NSF Awards · FY 2025 · 2025-08

Cyber-physical systems (CPS), for example, autonomous vehicles and delivery drones, consist of computational units tightly integrated with their physical environments. They are often built using small, constrained platforms and multiple control tasks shape the common platform. Thus the computation that is available to each control task is limited and may vary over time, which threatens to compromise the quality of control. This project will address this challenge through co-design of control algorithms and real-time scheduling techniques for control tasks. The new control algorithms developed in this project will be robust to early termination, with guarantees on the quality of control, and the scheduling frameworks will be capable of dynamically adapting scheduling decisions in response to changes in computational demand. The developed techniques will be applied to automated drone delivery in collaboration with industrial partners. The hand-on experimentation plan enables technology transfer to commercial delivery applications, as well as provides a valuable educational tool for engineering students studying robotics and autonomous systems. The approach will target optimization based control algorithms, such as model-predictive control and apply novel solvers based on state-of-the-art Robust to EArly termination oPtimization (REAP). The core idea of REAP is to construct a continuous-time dynamical system whose trajectory converges to the optimal solution, while a sub-optimal and feasible solution is guaranteed even in the event of early termination. Towards achieving this, the project will investigate i) closed-loop stability guarantees and discrete-time implementation; ii) proactive and safe real-time scheduling in CPSs; iii) cooperative computation-aware distributed model predictive control; and iv) control of systems subject to time-varying constraints. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-08

This IRES project develops internationally educated students for leadership roles in cybersecurity and Artificial Intelligence (AI) research in globalized societies. This objective is achieved through a synergistic partnership between Washington State University (WSU) and Sweden’s Linköping University (LiU), leveraging the leadership-class cybersecurity research programs at both universities. This project supports U.S. students for a fifteen-week research experiences at LiU, with a cohort of six to eight students participating in the program each year. Students have access to Sweden’s high-performance computing and visualization centers and take classes using English as the language of instruction. Professionals with expertise in AI and cybersecurity are in high demand among domestic and multinational corporations, as these skills are essential to ensure security of data, connections, and critical infrastructure. The IRES cohort will be augmented with an equal number of Swedish students, separately supported by Sweden, by pairing each U.S. student scholar with one LiU student, fostering deeply international research exchanges and collaborations. The resulting multinational community of scholars establishes cross-cultural professional networks and contributes to long-term research relationships. Through these networks the participating American and Swedish students elevate their preparation to operate successfully in the cybersecurity and AI fields at the highest international levels, expanding Sweden’s and the United States’ resilience against cyberattacks from malicious agents. As AI applications expand within a rising number of Internet-connected multi-faceted devices, ensuring the integrity, privacy, safety, and security of the data generated by billions of interconnected devices has become extremely challenging, complex, and critical. These cyber systems are pervasively targeted by sophisticated adversaries, who seek and exploit system vulnerabilities. Thwarting such attacks supports the cybersecurity priority interests of both the U.S. and Sweden. Securing cyber devices sustains national security and reflects strategic goals to maintain leadership in cybersecurity and AI innovation. The pursuit of these goals advances cybersecurity, drives technological innovation, and addresses the global shortage of skilled cybersecurity professionals. Accordingly, the IRES student scholars’ research centers on contributing to security technologies that can protect AI-augmented government, industry, and private cyber installations. In their research projects, the scholars investigate robust, secure, and trustworthy machine learning (ML) algorithms with enhanced security, anomaly-detection and privacy-preserving features tailored for diverse systems, including healthcare, autonomous vehicles, and smart cities. The IRES student scholars develop innovative cryptographic techniques designed to defend against the unique threats posed by AI applications in cyber environments. The techniques include advanced methods such as differential privacy, structure-preserving encryption, and secure multi-party computation. Key outcomes of this research include the application of cryptography schemes in real world problems and data to analyze large-scale machine learning models. This work will not only enhance the overall robustness and reliability of these environments but also address emerging challenges such as secure data sharing among interconnected devices and real-time threat detection across diverse systems. This globally significant emphasis aims to expand scientific knowledge and bolster data security amidst evolving threats, particularly those arising from the growing use of AI in our daily lives. By engaging in this work, students gain a comprehensive understanding of advanced attack vectors and develop secure, privacy-preserving techniques to effectively counter such threats. It is anticipated that the IRES student scholars’ research can further contribute to defy the activities of adversaries, fortify our resilience, and sustain the geopolitical competitiveness of U.S. enterprises and initiatives, domestically and overseas. Such an outcome is regarded to be an impactful societal contribution. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-08

PROJECT SUMMARY Research in my lab focuses on neural regulation of stress responses. Living organisms are constantly challenged by internal and external insults. Over- or underreacting to these insults may compromise health and longevity; thus, deploying appropriate stress responses to counter these attacks is critical. In contrast to our growing understanding of how stress is sensed and responses are initiated, our understanding of how overreactions are sensed and responses are attenuated is limited. This is largely because the regulation of stress responses is usually cell non-autonomous and involves multiple organs, with the nervous system, a highly complex and difficult to dissect system, often being the master regulator. We use Caenorhabditis elegans for our studies because it is one of the simplest organisms with a nervous system, and neural control of many stress responses occurs homologously in this model. With this system, we have discovered and characterized specific neural regulatory circuits that control stress responses to pathogen infection, warm temperatures, and oxidative stress. Pertinent to this R35 application is the neuroimmune regulatory pathway mediated by the neuronal G protein-coupled receptor NPR-8. We have found that the tripeptide proline-glycine- proline (PGP), derived from collagen degradation, binds NPR-8 in AWB, AWC, and ASJ amphid sensory neurons to suppress innate immunity against pathogen infection. Such regulation is achieved by inhibiting the expression of collagens with defense activity, forming a negative feedback loop to limit the intensity of the innate immune response. Based on these findings, we hypothesize that pathogen infection induces collagen degradation in the host to produce PGP that binds to NPR-8, activating the NPR-8 neural circuit that inhibits the immune response to maintain immunological homeostasis. This NPR-8-dependent neuroimmune regulatory pathway can be used by the host to limit or dampen overreaction of immunity or resolve the immune response after infection is cleared. This pathway provides a platform for deciphering the neuronal and molecular mechanisms that limit innate immune responses in a whole animal. Building on this platform, we propose to dissect neural signaling in the NPR-8 pathway and examine the immunomodulatory role of collagens in host defense. Specifically, we will elucidate how neuroimmune regulatory signals are initiated, how the signals are transmitted within the neural network, and how the signals are transduced from the neural network to non-neural tissues, such as the intestine, where the infection and defense often take place. We will also examine how collagens are remodeled and how they function in cell signaling in defense. Our goals are to understand neural signaling in neuroimmune regulation and decipher the neural-collagen regulatory mechanism that modulates pathogen infection outcomes. Since excessive immune responses have been linked to a myriad of human health conditions, our studies will facilitate the development of more effective treatments for innate immune disorders and infectious diseases.

NSF Awards · FY 2025 · 2025-08

Volcanic eruptions eject ash into the atmosphere, which can be hazardous to air travel, infrastructure, and human health. Most ash particles are small, and they can travel thousands of kilometers away. In many eruptions, ash particles combine into larger clusters, so they fall from the eruption cloud closer to the volcano. Large clusters can also break up (or "disaggregate") into smaller particles, which can alter where the ash falls. Electrical forces, moisture, and flow turbulence are factors that determine the formation or disaggregation of ash clusters. The effect of clustering is critical to make accurate forecasts of volcanic hazards. Most models do not include clustering and no models include disaggregation. This project will use experiments that help scientists examine ash clusters to quantify the fallout of volcanic ash. Results will help produce more accurate predictions of ash fallout for hazard assessments. Hands-on demonstrations of this research will be shared at the Oregon Museum of Science and Industry (OMSI). This project focuses on ash disaggregation, using detailed experiments to develop improved computational models of ash fallout. Our research team will use high-speed visualization of particle impacts, measuring their collision behavior directly. Tests will examine a variety of three-body collisions within a humid chamber, considering conditions relevant to volcanic ash clouds. Particles will range in size, material, and porosity, similar to actual clusters. The measurements will determine the quantitative likelihood of disaggregation. These results will be integrated into a volcanic plume model, providing more accurate predictions of ash fallout for hazard assessment. In addition, the findings will be presented to the public through a series of hands-on demonstrations at the Oregon Museum of Science and Industry (OMSI). 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 project aims to serve the national interest by investigating conditions under which innovative teamwork practices can improve metrics related to students' success in engineering programs. Teamwork is key to engineering success, but little is known about how faculty can effectively facilitate teamwork experiences. Therefore, this Level 2 Engaged Student Learning project plans to advance understandings of practices for effective teamwork for all students. By studying the effectiveness of these innovative practices, the project seeks to contribute to increasing the numbers of students who graduate with engineering degrees. It is anticipated that the research will provide vital and explicit evidence for how specific teamwork facilitation practices influence persistence in engineering by generating empirical evidence of the multidimensional effects of these innovative teamwork practices on engineering students' experiences and perceptions. This has the potential to contribute to a future in which undergraduate engineering students are fully engaged through development, testing, and use of teaching practices and curricular innovations that aim to engage students and improve learning and persistence in STEM. Analyzing how these practices affect factors related to persistence in engineering, and understanding faculty members' experiences utilizing these practices, could lay the groundwork for large-scale institutional improvement in engineering education. The goals of this project are to implement and assess a teamwork intervention and document the effects on students relative to factors influencing persistence in engineering. The project team plans to conduct a nationwide survey and interviews with engineering faculty members about their perceptions of and experiences with facilitating teamwork. Control data will be collected by administering a survey at the beginning and end of the semester in ten courses; the same courses will then receive a teamwork intervention, with the survey repeated to compare pre- and post-intervention results on student success and persistence metrics. Additionally, faculty will be interviewed to examine their experiences, perceptions, and challenges related to implementing the intervention. It is anticipated that characterizing the experiences of faculty will result in research-based plans for refining and scaling up the intervention and associated materials in the future. By developing research-based materials to improve engineering learning environments, partnering directly with faculty developers from around the country, and broadly disseminating the results, this project has the potential to have both national and local impact. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-07

Project Summary Our twelve years of research has led to the discovery of triptonide (TN) as a promising non- hormonal male contraceptive agent (Nature Communications, 2021, 12:1253). In addition to its excellent potency and proven oral bioavailability, TN does not cause discernable toxic effects in either mice or monkeys at its minimum effective dose. All available data strongly suggest that TN is worth further investment to develop it as a viable non-hormonal male contraceptive drug candidate. Taking advantage of the R61/R33 funding mechanism, we propose to conduct several Investigational New Drug (IND)-enabling studies to collect data required by the FDA for official IND application. Specifically, we will conduct non-GLP toxicity and safety pharmacology studies to identify the maximum tolerated dose (MTD) followed by a six-month repeat dose toxicity study using MTD and minimum effective doses (MED) in male Sprague-Dawley rats in the R61 phase. In addition, deep learning-based pathological and RNA-seq-based transcriptomic analyses will also be performed. The data will not only guide and corroborate the GLP-compliant toxicity and safety pharmacology studies proposed in the R33 phase, but also provide molecular insights for any potential phenotypes observed. In the R33 phase, we will work with Pharmaron Inc. to perform non-GLP toxicity studies in dogs, in vitro secondary pharmacology, and GLP-compliant repeat-dose toxicity and safety pharmacology studies all as part of a package of studies intended to move triptonide into a Phase I clinical trial.

NSF Awards · FY 2025 · 2025-07

This doctoral dissertation research project investigates human-environment dynamics by examining how land use relates to mobility and group knowledge. The project considers higher altitude environments as well as the economic and social value of natural resources. Examining these dynamics in a broader range of environments advances our understanding of the ways in which human groups become progressively tied to landscapes, resources, and subsistence systems. The project supports student mentoring and training in STEM research. The researchers combine lithic technological, raw material sourcing, and geoarchaeological analyses with ethnographic and geologic data in order to relate the physical properties and geologic histories of the landscape to their use. Previous research has focused on a limited number of landscapes that do not capture the full spectrum of mobility, land uses, and seasonal activities. This research goes beyond tracing stone raw material movement by contextualizing movement of stone tools through the evaluation of stone tool use within the broader lithic, social, and ontological landscapes. 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

Advances in machine learning (ML) have opened up new possibilities for accurate predictions in various fields. To ensure the reliability of these predictions, especially in high-stakes decision-making scenarios, theory and tools need to be developed that provide confidence intervals. This research project aims to create innovative methods for quantifying uncertainty in complex systems, allowing for more informed and confident decision-making. One key aspect of this work is designing efficient collaboration between humans and machines, where artificial intelligence (AI) produces a set of possible solutions and human experts select the best option. For instance, in medical diagnosis, these tools will enable doctors to identify potential health risks by generating a short list of likely diagnoses, with the correct answer guaranteed to be included among them. Through a five-year program combining cutting-edge research, education, and community engagement, the researcher will develop novel algorithmic and theoretical frameworks to improve predictive accuracy and trustworthiness across various applications. To share the results broadly, the researcher will publish research papers, present at conferences, and provide tutorials on uncertainty quantification and safe ML deployment. This project aims to create a new framework that seamlessly integrates conformal prediction principles into ML model training procedures. This integrated approach will enable the production of small uncertainty sets with rigorous guarantees, facilitating the safe deployment of ML models and efficient human-ML collaboration. To achieve this goal, the project will focus on three interconnected research areas. First, develop calibration methods that can provide reliable assessments of confidence intervals using two complementary metrics: conformity scores from trained classifiers and label ranks. Second, establish principled training objectives and optimization algorithms for conformally training deep neural network classifiers. Third, develop conformal calibration techniques tailored to large language models (LLMs) and optimize their fine-tuning procedures using a novel framework. These methods will address the unique challenges posed by LLMs while ensuring robust performance in high-stakes applications. This research will be applied to real-world domains, including adaptive experimentation for design optimization, cybersecurity, health monitoring, smart agriculture, and elderly care. The team will collaborate closely with domain experts to ensure that our solutions meet the needs to tackle pressing societal problems. The developed algorithms will be freely available through open-source software, enabling widespread adoption by academia and industry. The team also plans to engage with the broader community through education and outreach initiatives, including a novel Ambassador program to encourage underrepresented minority students in computer science, a short summer course on uncertainty quantification for engineers and scientists, and a partnerships with existing programs to recruit students in computer science. 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

With the emergence of computational storage devices and smart storage solutions, new system-level support is needed to enable data-driven scientific applications to efficiently access and utilize underlying compute and storage resources. This project contributes by creating a new basic toolchain and system technologies for such systems and by evaluating them with representative scientific applications and data analytics. It has the potential to impact other scientific domains because data-driven scientific applications are used in many scientific and engineering domains, including national security, power system reliability, and food security. The project will provide research training in Very Large Scale Integration (VLSI) and AI for undergraduate students and provide them with an educational pathway to pursue advanced degrees. This collaborative and interdisciplinary project seeks to bring experts in computer systems, field-programmable gate arrays (FPGAs), high-performance computing (HPC), and domain scientists together to design and implement a virtual computational storage system λ-HDF5. The project is driven by real use cases and built on state-of-the-art HPC and machine-learning cyberinfrastructure. The project has three specific goals. First, the project will develop an HDF5-compatible interface and provide support for a wide variety of computer kernels. Second, it will identify, dispatch, and execute compute kernels on faster devices across multiple I/O layers in HPC systems. Third, it will efficiently manage co-located raw data and pre-processed data on distributed and heterogeneous storage devices. Scientific applications using λ-HDF5 for data management can benefit from accelerated data ingestion pipelines. λ-HDF5 also makes computational storage devices more accessible to users in scientific computing communities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2025 · 2025-06

PROJECT SUMMARY/ABSTRACT Cannabis use among young adults has increased dramatically over the past decade, with nearly 1 in 3 young adults in the U.S. reporting past month use. Young adulthood is a high-risk period for the development of substance use problems in general and a subset of young people may be at especial risk: those with chronic pain. Chronic pain is a major public health concern associated with significant morbidity and mortality. Although underrepresented in pain research, epidemiological surveys and systematic reviews suggest that up to 20% of young adults experience recurrent or persistent pain problems that are associated with a wide range of negative outcomes, including poor sleep, physical activity limitations and reduced quality of life. Due to widespread beliefs about its pain-relieving properties, young adults with chronic pain may be using cannabis to manage their symptoms. Although cannabis has garnered considerable attention as a potential treatment for chronic pain, its therapeutic potential—especially in young adults—remains unknown. Further, the impact of naturalistic cannabis consumption on functional outcomes, including pain-related impairment, physical (in)activity, and sleep is poorly understood. The overall objective of the proposed study is to holistically examine how cannabis use is related to pain and functioning (i.e., pain-related disability, physical (in)activity, sleep) in the daily lives of young adults with chronic pain. The proposed research will use an innovative 6-month longitudinal measurement burst design to capture momentary experiences and changes over time in a projected sample of N = 60 cannabis-using young adults with chronic pain. We will examine relationships between naturalistic cannabis use, pain perception and functioning in participants’ daily lives during three 2-week ecological momentary assessment (EMA) periods each separated by approximately 8 weeks. This approach will enable the research team to track intraindividual change including nuanced daily associations and longer-term change with less burden to participants. We will test how daily pain and functioning vary as a function of cannabis use at the momentary and daily level and whether these relationships (as well as cannabis use patterns) change over time. The results of this study will allow us to determine the conditions under which cannabis may improve or impair daily functioning and well-being among young adults with chronic pain. These findings will directly inform the development of a larger study to identify adaptive and maladaptive cannabis use patterns of young adults and the longer-term impact of cannabis use on pain and pain-related functioning. Our ultimate goal is to identify and test novel targets or critical time points for effective chronic pain and substance misuse prevention, both of which represent national research priorities.

NIH Research Projects · FY 2026 · 2025-05

Project Summary Physical activity (PA) is a cornerstone of human health and well-being; however, its implementation as a viable treatment and preventative option for alcohol use disorders (AUDs) remains understudied. This is underscored at the social level by the ~26% of adult U.S. citizens that report binge drinking and the mere 3% of citizens who manage to meet daily U.S. PA guidelines. Here, we will better evaluate this relationship by testing the role of voluntary PA in reducing binge-like ethanol drinking in a unique genetic risk model of drinking to intoxication, the High Drinking in the Dark (HDID-1) mouse line. Both PA and alcohol use create neural remodeling across interconnected brain regions belonging to the mesocorticolimbic system. This neural network comprises of interoceptive brain regions – those responsible for the processing and translating the internal body state [such as the insula cortex (IC)] - aversion-related brain regions [such as the basolateral amygdala (BLA)] and brain regions important for reinforcement [i.e., the ventral tegmental area (VTA)]. Here, we plan to retrogradely trace the nucleus accumbens (NAc) - the central point of convergence for this system – and determine which neural inputs are engaged following binge-like drinking and PA. Prior wheel-running (WR) work has characterized cFos using slice-based immunohistochemistry, but only in male rodents. Considering stark sex differences in humans and rodent PA levels, this application addresses a major gap in the literature. cFos immunoreactivity (IR) will be used in combination with a retrograde tracer (rAAV2-retro-GFP) to reliably characterize and trace the neural inputs to the NAc. We hypothesize that distinct reinforcement and interoceptive-related NAc projections (e.g. IC, and extended amygdala) will be disrupted/disengaged following binge-drinking and that WR will act to potentiate neural circuit communication and modularity. The IC relays relevant interoceptive information to limbic regions, such as the NAc, and influences motivated behaviors (like PA and alcohol use). Optogenetically stimulating the IC Æ NAc projection reduces aversion resistant drinking in male rats. To evaluate the role of the IC Æ NAc projection in binge-like drinking and PA, this R00 will test whether chemogenetically silencing or activating the IC Æ NAc circuit [using designer receptors exclusively activated by designer drugs (DREADDs)] will modulate these important behaviors. We hypothesize that chemogenetically silencing the IC Æ NAc projection will decrease binge-like ethanol drinking in sedentary mice and prevent a recently characterized decrease in binge-like intake following PA. In contrast, we hypothesize that chemogenetically activating the IC Æ NAc projection will decrease ethanol intake (in sedentary mice) and further attenuate ethanol intake in wheel-running mice. Taken together, the goals of this proposal are 1) to determine the efficacy of voluntary physical activity (PA) to reduce binge-like ethanol drinking in a genetic risk model for harmful drinking and 2) to identify mesocorticolimbic circuits important for binge-like drinking and PA and 3) test a neural mechanism central to PA as an adjunctive treatment option for AUDs.

NSF Awards · FY 2025 · 2025-05

The U.S. healthcare system typically focuses on diagnostics using expensive analytical equipment in centralized hospital-based laboratories. Although these tests have high degrees of accuracy, the equipment requires trained personnel to operate and maintain. There is growing interest in other types of diagnostic tests for (i) the monitoring of pandemics, (ii) routine screening in clinics or offices, (iii) national security, and (iv) personalized medicine and at-home diagnostics. To realize effective decentralized testing, this NSF CAREER project will develop ready-to-use sensing platforms and prototypes through the functionalization of 3D-printed material. Using 3D printing for the development of analytical devices allows for rapid optimization, superior reproducibility, and mass production. This project also has a strong educational component with a focus on encouraging high school students and undergraduate students to contribute to chemical research. Moreover, this program aims to broaden participation in engineering through outreach activities. This NSF CAREER project focuses on the development, interrogation, and utilization of fully printed, calibration-free solid-contact potentiometric systems. The project will take advantage of the inherent benefits of additive manufacturing (i.e., 3D-printing), (i) extreme reproducibility, (ii) control over spatial dimensions, (iii) diverse material compatibility and (iv) mass production capabilities towards the development of highly stable, low-cost and mass producible ion-selective and reference electrodes. The unique properties of methacrylate-based membranes (e.g., tunable ion-mobility and hydrophobicity) will be exploited towards achieving low detection limits, enhanced selectivity and intrinsic biofouling capabilities. The project's main research objective is to develop reliable solid-contact potentiometric systems that not only overcome current analytical limitations encountered by traditional sensors but are fabricated using technologies that are conducive to mass production. The project also aims to exploit 3D-printing towards the fabrication of efficient calibration-free solid contact potentiometric sensors, stable and robust reference electrodes, enzymatic biosensors and the development of next generation bio(sensing) technologies for use at the point-of-care. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NIH Research Projects · FY 2026 · 2025-05

PROJECT SUMMARY/ABSTRACT The American Indian and Alaska Native (AI/AN) population is increasing 3 times faster than the US population overall. By 2050, it is predicted that 1 in 3 AI/AN Elders will be diagnosed with Alzheimer's disease and related dementias (ADRD). Despite advances in ADRD research among non-Hispanic Whites, little is known about the prevalence and risk factors for ADRD in AI/AN populations. This is in part due to low participation of AI/ANs in ADRD research. The National Institute on Aging and the Alzheimer's Association have issued calls for an increase in minority participation in ADRD research. However, success has been evasive in efforts to recruit AI/AN populations into ADRD studies, particularly studies including biomarkers. Failure to include AI/ANs in biomarker or ADRD research further contributes to ongoing health disparities in ADRD research and healthcare outcomes because biomarkers are crucial in an accurate and timely diagnosis, and also play an important role in ADRD drug development. To increase AI/AN participation in ADRD research that includes biomarkers, it is critical to understand how to effectively communicate about biomarkers and genetic research with AI/ANs. This information can be used to create effective communication and recruitment material for ADRD research. In this study titled “Communicating Heath Advancements from Native GEnetics Research (CHANGE Research)” we will apply a multi-method approach to assess AI/ANs perceptions and knowledge of ADRD research and communication preferences. Using this information, we will create culturally tailored information material to educate AI/ANs about ADRD and biomarkers to promote their enrollment into ADRD research. Our Specific Aims are to: 1) partner with the United Indians of All Tribes Foundation to conduct a survey of 500 AI/AN adults about their knowledge and perceptions of biomarker research. Survey domains will also include preferences for health information, information seeking and opinions regarding AI/AN representation in ADRD research; 2) interview AI/AN adults regarding cultural barriers and facilitators to participating in ADRD research involving biomarkers. We anticipate that these interviews in conjunction with the survey results from Aim 1 will provide insights on barriers and facilitators to participating in research involving biomarkers and effective methods to communicate about ADRD research and biomarkers; and 3) create culturally tailored educational material and conduct a pilot study to demonstrate feasibility of a future randomized controlled trial. This innovative application provides an opportunity to discover critical information about how to communicate about biomarkers and ADRD research with AI/ANs and answers the National Institute on Aging's call for research to better understand effective strategies for recruiting minorities into ADRD research and communicating health messages that are appropriate for diverse populations.

NSF Awards · FY 2025 · 2025-05

The environmental can significantly impact human food practices, particularly in small-scale societies whose lifeways are closely linked to the animal and plant resources they depend on for survival. This project examines how people in small scale societies adapted their food practices to changes in the environment. Archaeological data can address this question because it provides information on past food practices, which can be integrated with palaeoclimatological records to assess the impact of environment changes on food practices over time. In collaboration with local communities. researchers study a diverse range of dietary remains preserved at archaeological sites to provide a holistic perspective on human diets and document food practices at the individual level. The resulting data have value to communities working to mitigate the impact of environmental changes on culturally important traditional foods. The community-based outcomes of this project provide opportunities for enhancing tribal engagement and scientific collaboration. This investigation develops new methods for identifying food practices in the past and contributes to the education and training of students in these methods as well as in community engagement. This study produces a fine-grained record of hunter-gatherer dietary practices through analysis of plant and animal food remains in human feces preserved at archaeological sites. Dietary data is integrated with high-resolution palaeoclimatological data to evaluate the impact of environmental changes on hunter-gatherer subsistence. This study examines how environmental changes impacted (1) the availability of food resources, and (2) the decisions that hunter-gatherers made about which food resources to pursue. Changes were variable across time and space and there are indications that the impact of oscillations on subsistence practices was variable at different sites. This project seeks a detailed analysis of this variability through a comprehensive study of human dietary choices integrated with high-resolution palaeoclimatological data. This study examines evidence that food practices at sites changed with environment fluctuations. 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 · 2025-05

The Phytochemical Society of North America (PSNA) will hold its 64th annual meeting on June 24 – 28, 2025 at York University in Toronto, Canada. Typically, the conference attracts between 120 and 160 attendees. This grant will support registration, travel, and accommodation costs of U.S.-based scientists to attend the PSNA 2025 conference. Research presented at the PSNA meeting has potential applications for the improvement of human health. These include the development of plant-based foods with enhanced nutritional and health properties, anti-cancer drugs, and other pharmaceuticals. Other benefits to society comprise the sustainable production of biofuels and high value plant-based industrial products. The primary goal of the conference is to bring together scientists from North America and other parts of the world to disseminate unpublished data and share new trends in the field. Historically, this has led to the formation of new collaborative relationships, grant applications, and scientific exchange between participating laboratories. A key feature of this conference is the promotion of trainees by providing students and post-doctoral fellows with opportunities to compete for speaker slots. This meeting will support trainees by providing best presentation and poster awards as judged by a panel of conference attendees. Networking and professional development of junior scientists will be facilitated through panel-guided career workshops for early career scientists. Among PSNA members, there is a long tradition for the study of plant biochemistry, chemistry, and natural products (e.g. food and fiber sources; specialty chemicals, oils, and resins; nutraceuticals; and plant defense chemicals). Symposia planned for the 2025 PSNA conference will include diverse topics such as “Metabolic Engineering and Plant Synthetic Biology”, “Gene Discovery and Functional Plant Genomics”, “Plant Immunity and Microbiome Interactions”, and “Chemical Ecology and Plant-Organismal Interactions”. PSNA 2025 is also planning breakfast events focused on Career Development. A workshop for postdocs will be organized by the PSNA Young Members Committee as facilitated discussion on career development in academia, government, and industry. Based on advice by the PSNA Young Members Committee, the graduate student workshop will focus on how to cope with stress in graduate school and mentor-mentee relationships. A voluntary and fully-anonymous survey will be used to collect information during and after the conference to obtain information on attendee demographics and feedback on what worked or did not work well for them (symposia, poster sessions, workshops) and for suggestions for improvement. 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 · 2025-05

This project brings together experts in molecular programming (MP) to develop a comprehensive 10-year plan for the field. Molecular programmers create computers that run on molecular interactions, rather than electricity, enabling computer programs to control physical matter. MP is a potentially transformative technology with diverse applications, including: (i) intelligent medicines that autonomously diagnose and treat diseases, (ii) high-density data storage, (iii) dynamic biosensors, (iv) nanofabrication, (v) soft robotic actuation, and (vi) chemical automation. Despite its potential, MP remains a relatively small and fragmented research field, with most efforts isolated within individual labs and relatively little inter-institutional coordination. This project will help accelerate the field of molecular programming by defining landmark research objectives across MP and developing novel collaborative frameworks beyond the single-lab research model to pursue these objectives. The project aims to foster large scale collaborations within molecular programming (MP) by first broadly surveying the field, then hosting an intensive in-person technology roadmapping workshop to outline landmark enabling technologies that are missing within MP, and finally following up with a novel inter-institutional collaborative research framework to pursue the roadmap collectively. Primary objectives are to: (1) define the field of “molecular programming” in the context of other related fields, (2) establish “lifetime” goals and applications for the field, (3) evaluate the current state of MP capabilities, (4) develop a ten-year technology roadmap of missing technologies within MP, (5) outline massively-collaborative research mechanisms to pursue the technology roadmap, (6) expand industry partnership and workforce development, and (7) broaden leadership and participation within the field. By creative a cohesive vision for the next decade, this project will significantly accelerate the field of molecular programming and will promote technological breakthroughs with applications in medicine, data storage, and programmable matter. 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 · 2025-04

With the support of the Macromolecular, Supramolecular and Nanochemistry Program in the Division of Chemistry, Professor Kevin Kittilstved of the University of Massachusetts Amherst will study the formation of clusters that can be used as precursors for preparing semiconductor nanocrystals or quantum dots. Semiconductor nanocrystals are useful for a wide range of optoelectronics, sensing, and biomedical imaging applications. The deliberate incorporation of a small amounts of chemical impurities (or dopants) into the semiconductor nanocrystals introduces tunable functionality and novel properties. This research aims to gain a thorough understanding of the formation mechanism of doped semiconductor clusters and to develop a bottom-up synthetic approach to enable precise control of the dopant level and distribution. This project will contribute to the preparation of a skilled workforce in STEM fields by training graduate and undergraduate students in chemical synthesis and characterization using sophisticated techniques. Members of the Kittilstved group supported by this funding will be involved in developing and executing a hands-on lab experience for the Eureka! Program organized by Girls Inc of Holyoke and the College of Natural Sciences at the University of Massachusetts Amherst. To facilitate effective collaboration amongst group members, Dr. Kittilstved and his research team will engage with the various research mentoring and professional development workshops available through the Graduate School at the University of Massachusetts Amherst. The long-term goal of this project is to establish the chemical parameters that promote precise doping of targeted impurity ions within magic-size clusters, which are known to be critical metastable precursors in the synthesis of quantum dots, nanowires, and nanoplatelets. To achieve this goal, the team led by Dr. Kittilstved will first examine the effect of transition metal dopants in mononuclear precursors and multinuclear CdS-based molecular clusters on the formation mechanism of magic-size clusters and determine what chemical factors promote stepwise assembly of molecular clusters into a precisely doped magic-size clusters. In conjunction with the synthetic aspect of this study, this team will use conventional and state-of-the-art spectroscopic and analytical methods to characterize dopant speciation in the magic-size clusters, to study the kinetics of magic-size cluster formation, and to follow the evolution of the electronic structure from the molecular to the quantum confinement regime. This research strives to provide fundamental knowledge to inform the rational design of high-quality and homogeneously doped designer semiconductor nanostructures for spin-based electronics or optoelectronics applications. 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 · 2025-04

This CAREER project studies the impacts of a strengths-based approach to communities. The research seeks to operationalize, develop, and test a community-driven unit of measurement of community strength. The research develops a data-driven conceptual framework that provides an understanding of the needs of communities over time. Broader impacts of the research include the development of a validated and generalized toolkit to measure community strength for use in clinical and educational settings. The collaborative research design strengthens relationships between anthropological, public health and medical scientists. The research also develops the scientific workforce through training of undergraduate, graduate, and professional students in mixed methods research and collaborative science. To understand and measure the impacts of a strengths-based community approach and to develop a validated toolkit, the investigators, in years 1-2 of the project, use a mixed methods approach for data collection and validation. This includes focus groups and semi-structured interviews, qualitative tracking of community strategies, and a measurement tool that progressively tracks community outcomes over time. In years 3-5 of the project, investigators create and test a curriculum developed with community partners that will be piloted in medical schools and public health contexts. The impact of the curriculum will be evaluated using an existing evaluation toolkit and the final product will be made freely available via open-access venues for use by all communities and educational settings. Research findings advance scholarship in medical anthropology and public health. 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 · 2025-04

This project aims to serve the national interest by improving teaching and assessment methods used for team projects in undergraduate computing education. By requiring students to collaborate in the development of a software product, team projects provide students with authentic learning experiences that prepare them for careers in the computing profession. In undergraduate education, a key challenge is to assess individual contributions to team projects. This project plans to develop a novel teaching and assessment approach in which students compile individual portfolios documenting and reflecting on their completed project tasks relative to the outcomes they address. Instructional staff and peers then assess a sample of each student’s portfolio entries against appropriate performance indicators associated with the learning outcomes targeted by the team project. Since the framework will be readily adaptable to any team project, the approach can be used for team projects in any STEM degree program. This Level 2 Engaged Student Learning project will thus help advance undergraduate STEM education by improving the ability to assess students engaged in team projects. Using a rigorous empirical approach that involves computing instructors at multiple institutions, computing students, software professionals, and a learning scientist, this project will iteratively develop and validate (a) an assessment framework to gauge attainment of student learning outcomes targeted by collaborative software development projects; and (b) a pedagogical approach that integrates the assessment framework into computing courses. By aiming to improve assessment methods for team projects, the framework will contribute to the development of exemplary practices in undergraduate STEM education. Through their participation in the framework, students will enter the workforce with better self-knowledge and documentation of their skills, thus helping employers to integrate new hires into positions that align with those skills. The framework will be designed to be flexible enough to facilitate its adoption across a broad range of STEM courses. Moreover, the framework aims to assess students' attainment of a variety of learning outcomes in addition to those captured by traditional assessments. In so doing, it aims to help broaden the participation of STEM students from different backgrounds. By documenting, reflecting on, and receiving feedback on their individual attainment of learning outcomes in team projects, students will be better prepared for employment in the professional workforce, where team projects are a central activity. The NSF IUSE: EDU Program supports research and development projects to improve the effectiveness of STEM education for all students. Through the Engaged Student Learning track, the program supports the creation, exploration, and implementation of promising practices and tools. 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

NON-TECHNICAL SUMMARY To advance the exploration of space, learning how to control liquids in the absence of gravity is essential. On Earth, the flow of liquid is mostly controlled by gravity. In the absence of gravity, capillary forces (surface tension) govern flow. In space, water in a glass would not remain conformed to the shape of the glass. In space, water’s shape is driven by capillary forces, and would cover all sides of the glass and form a blob over all surfaces. The absence of gravity also means the absence of buoyancy. On Earth, a closed bottle of water with some air would have the air on top, but in space, the air bubbles could be anywhere inside the bottle and have any size. This project focuses on molten metallic alloys, which are a liquid useful for brazing and soldering in space for repair of damaged surfaces (due to impact of micrometeoroids and space debris), as well as for construction in space. Such alloys melt and solidify gradually. The goal is to control the concurrent melting and capillary flow of a molten alloy in microgravity and predict the resulting microstructure of the bond. This project is ensuring durable bonding for repair and construction in space man-made habitats and impacting the ability to control other liquids in space and on Earth. TECHNICAL SUMMARY It is observed that near-eutectic binary alloys, subject to concurrent melting and capillary/gravitational flow, are prone to flow-induced segregation whereupon it solidifies into two very different microstructures. The extent of segregation varies, apparently depending on the processing conditions as well as on the geometry of the capillary flow. This project consists of: (i) a series of experiments performed on the U.S. International Space Station with simultaneous ground-based experiments, and, since the melting/flow solidification process cannot be observed directly – (ii) a detailed mesoscale modelling program of the process (phase field computations). The objectives of the project are to: (i) understand the detailed physical mechanisms of segregation during capillary flow under both microgravity and terrestrial conditions. Focus is being afforded to the effects of gravity, temperature gradients, peak temperature, and interaction of diffusion-controlled melting and flow of the melt. This activity also allows for the formulation of the mathematical/computational theory needed to operationalize this understanding. (ii) apply this theory to the design of methodologies for brazing and soldering in both space and terrestrial materials bonding.The new theory and predictive models being produced in this work utilize a phase field formulation of the capillary flow under conditions of void formation and is being verified through the experiments capturing the differences in microstructure of the re-solidified melts obtained in microgravity and under terrestrial conditions. In addition to brazing metals, the results will be relevant for capillary phenomena involving low temperature soldering as well as processes related to bonding of ceramics and metals at high temperatures. Furthermore, the findings of this project are leading to better understanding of capillary phenomena involved with multilayer metal deposition in advanced technologies such as additive manufacturing via selective laser melting. Educational broader impacts include the addition of new modules to the existing graduate courses at Washington State University and the University of Kentucky, research experience for undergraduate students, and outreach to high school students. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.