Dartmouth College

NSF Awards · FY 2025 · 2025-07

Non-Technical Summary: With support from the Solid State and Materials Chemistry program in the Division of Materials Research, the Aprahamian group investigates the nature of the interaction between a pinch of light-sensitive additives, called switchable molecules, and spiral structures made of liquid crystals - the active components in Liquid Crystal Displays (LCDs). The research focuses on gaining important insights into how the switchable molecules can control the color reflected from the liquid crystal surface. Understanding and harnessing this capability opens the door to the development of different types of low-energy-consuming devices and applications such as smart price tags, anti-counterfeit and cryptography devices, and even adaptive camouflage material. To help disseminate this research and its outcomes with broad audiences, Aprahamian and his group engage in educational and outreach activities, such as the National Chemistry Week, involving high-school and undergraduate students, and use interactive demonstrations to communicate the societal relevance and benefits of this type of fundamental research. Technical Summary: Tuning the photophysical properties of liquid crystals (LCs) using photoswitchable chiral dopants enables a wide range of applications, including smart tags, low-energy displays, and adaptive bandpass filters. The realization of these technologies depends on a fundamental understanding of how dopants interact with the LC host and how these interactions affect the helical pitch of the chiral LC—an essential determinant of its photophysical behavior. With support from the Solid State and Materials Chemistry program in the Division of Materials Research, the Aprahamian group employs halogen bonding to strengthen the interactions between hydrazone-based dopants and the LC host with the goal of improving the chiral information transfer between them, thus enabling precise tuning of the color reflected from the LC surface. The group also develops new chiral architectures, including macrocyclic hydrazones and C3-symmetric scaffolds such as tribenzotriquinacene, to expand the design space and capabilities available to materials scientists. In parallel, they investigate the potential for using switchable dopants to modulate the reflective properties of ferroelectric LCs. In addition to their research efforts, the Aprahamian group engages in educational and outreach initiatives aimed at broadening the impact of their work and communicating the value of fundamental science to broad audiences. 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

Variation in health outcomes for cancer patients has garnered significant national media attention. Recent retrospective cohort studies have reported that cancer health outcomes are improved and more consistent when patients have uniform access to care, highlighting the critical clinical importance of optimizing access to cancer care. Data made available which evaluates access to cancer specialists typically determines access based on a per capita count of individual specialties, which does not adequately capture access to multidisciplinary teams of specialists. A relatively unexplored area of study is the extent to which relationships between cancer specialists can be characterized and then targeted to optimize access to cancer care and improve patient outcomes. By assessing the relationships between physicians based on patient-sharing patterns observed in administrative data, we propose to apply our team’s expertise in network analysis, health services research and cancer care to provide a framework for evaluating patient access to cancer care which recognizes the coordination across medical oncology, radiation oncology, and surgical specialists. We have developed a novel network measure– linchpin score – which identifies cancer specialists who are the only specialist of their kind among their neighbors’ ties. We have demonstrated that patients treated by linchpin oncologists are more likely to have delayed cancer treatment and often experience worse survival. This proposal will build on our prior work by examining how network-based measures of access to cancer care, including linchpin score, are associated with patient healthcare resource utilization and patient experience measures. We will also provide resources to the scientific community in the forms of an R package and an interactive dashboard of aggregate oncology workforce measures. In conclusion, this proposal uses network analysis to capture essential characteristics of access to cancer care, with the long-term goal of using network-guided strategies to improve access to cancer care and patient outcomes.

NIH Research Projects · FY 2026 · 2025-07

PROJECT SUMMARY/ABSTRACT Poor bone quality in the jaw is a significant clinical problem that leads to pain, along with an increased risk of fracture and infection. Multiple clinical conditions may lead to poor jawbone quality, but two of the leading causes are osteoporosis and osteonecrosis as a result of radiation therapy (RT). Osteoporosis affects 200 million people worldwide and while the focus is often on the appendicular skeleton, craniofacial bones, including the jaw, become brittle and diseased. While not as pervasive, head and neck cancer (HNC) is the sixth most common cancer type worldwide with a predicted 30% global increase annually by 2030. RT is the standard treatment for HNC, and osteoradionecrosis (ORN) of the jaw is a frequent and severe complication. Interestingly, the molecular mechanisms underlying the poor bone quality in these two conditions are similar, with cellular senescence and dysregulation of osteoblast to osteoclast management playing a significant role in disease etiology. Senescence is a cellular-level response that restricts aged or damaged cell proliferation and represents a major cause of aging due to genomic instability and telomere damage. Studies have demonstrated an increase in senescent cells as a person ages, contributing to diseases associated with aging (e.g., osteoporosis). Additionally, we have identified a strong correlation between cellular senescence and increased expression of the bone inhibitor sclerostin (SOST). The long-term goal of this project is to tune a novel 3D-printed (3DP) mineral framework infiltrated with cryogel scaffold to resist destructive structural and cellular modulations following radiation in order to improve bone regeneration. We propose the central hypothesis that a combined cryogel scaffold/mineralized 3DP framework will induce osseointegration and bone formation in HNC patients, while modulating senescence caused by radiation. We test this hypothesis through three main aims: i) enhancement of bone formation in the setting of radiation through the fabrication of combined tissue- engineered cryogel/3DP mineral constructs; ii) systematic modulation of in vitro senescence through optimization of scaffold mineralization, with or without the addition of senolytic drugs; and iii) quantification of senescent cells and overall bone healing in an established in vivo osteonecrosis mandible murine model exposed to RT. This approach will allow for the creation of a cost-effective and biologically improved targeted treatment option consisting of uniquely combined mineralized 3DP framework and cryogel technology. The potential to induce osteogenesis and modulate senescence, both in vitro and in vivo, is innovative and impactful mechanistically, where our fabrication expertise and mechanistic knowledge will establish a scaffold capable of stimulating/accelerating bone formation. Further, the innovative impact of the combined scaffolding for modulating senescence has the potential to be highly translational to additional complex bone defects, especially those in aging patients. This will fit a need in the research and clinical community for improved patient-specific treatment options while supporting the NIDCR mission of improving oral, dental, and craniofacial health.

NSF Awards · FY 2025 · 2025-07

The Algebraic Geometry Northeastern Series (AGNES) is a series of biannual conferences in the field of algebraic geometry. The conference is hosted on a rotating basis by an association of universities in the Northeast region. This award supports six AGNES conferences, which will be held at Dartmouth College on November 8-10, 2024, at Rutgers University in Spring 2025, at the University of Massachusetts, Amherst in Fall 2025, at Stony Brook University in Spring 2026, at Brown University in Fall 2026, and at the University of Pennsylvania in Spring 2027. Each AGNES conference has two goals. First, each conference promotes the dissemination of cutting-edge research in mathematics. The centerpiece of each conference is a series of research lectures by top mathematicians; there are also educational talks for graduate students and events which promote new collaborations or development of peer relationships. Algebraic geometry is a field in the mathematical sciences concerned with solution sets of polynomial equations. It has deep connections to many other areas of pure mathematics, such as topology, arithmetic, number theory, differential geometry, dynamical systems, and homological algebra. At the same time algebraic geometry has found important applications in many subdisciplines of applied mathematics, including cryptography, complexity theory, mathematical biology, and computer vision. The scientific scope of AGNES is greatly enriched by lectures from neighboring mathematical subjects, such as arithmetic geometry, dynamics, complex geometry, and computational geometry. Further information about conference events can be found at the website: http://www.agneshome.org/ 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 Myelin has evolved to speed up, finely tune, and increase the metabolic efficiency of electrical signal transmission in the brain. In numerous human diseases, myelin degenerates, ultimately resulting in devastating motor and cognitive impairment. One key reason that this degeneration progresses to functional impairments is the decline in the ability of resident oligodendrocyte precursor cells (OPCs) to generate new myelinating oligodendrocytes and replace the dying cells. To generate new oligodendrocytes, OPCs go through many cellular and molecular checkpoints, coordinating external microenvironmental signals with internal genetic, epigenetic, and metabolic states. Given this complexity, there are still many questions related to how these signals are integrated within the cell to ultimately result in the cell fate decision to transform into a postmitotic myelinating oligodendrocyte or remain a proliferative OPC. Mitochondrial activity has been shown to play important roles in similar fate decisions in other cell types throughout the body in addition to playing major roles in cell death pathways, however, less is known about how these organelles impact OPC fate, oligodendrocyte generation, and oligodendrocyte death in the intact brain. To directly study this, we have developed advanced techniques for high resolution imaging and manipulation of mitochondria throughout the oligodendrocyte lineage. These techniques permit longitudinal analyses of mitochondrial structure, localization, and dynamics in real time all in the live mammalian cerebral cortex. Here we propose to use these approaches to determine how disruptions and alterations in mitochondrial dynamics, characterized by mitochondrial fission, fusion, motility, generation, and degradation, impact OPC fate and oligodendrocyte survival. These experiments will be performed in the context of development, adulthood, aging, and in demyelination models, thus revealing the precise role mitochondria play in oligodendrocyte generation, plasticity, death, and regeneration. Ultimately, these studies will reveal multiple aspects of cell metabolism with a mitochondrial lens providing a critical foundation to understand this multifunctional organelle in oligodendrocyte physiology and pathology.

NSF Awards · FY 2025 · 2025-07

This award will fund about 10 U.S.-based graduate students for attending the IEEE Secure Development conference (SecDev 2025) in October 2025. Research on software security usually focuses on detecting vulnerabilities in software and attacks on resources. However, there is little attention to how programmers can develop secure software from the ground up. The SecDev conference aims to continue its mission of providing a forum where researchers, practitioners, and decision makers can meet to discuss ideas that focus on building security into deployed systems, on topics including development libraries, tools, or processes to produce systems resilient to certain attacks; formal foundations that underpin a language, tool, or testing strategy that improves security; techniques that improve the scalability of security solutions for practical deployment; and experience, designs, or applications showing how to apply cryptographic techniques effectively to secure systems. Student participation in SecDev has a number of benefits, allowing them to meet with researchers and leaders in the community to advance both their on-going research and their career development. Funding participation for students who would otherwise be unable to attend also serves larger goals of widening the talent pool of professionals and researchers focused on addressing challenges of developing critical secure systems and services. To this end, the conference will widely advertise the availability of support for students who need funding to attend, to increase the range of personal and institutional backgrounds of potential attendees. Students will be selected based on the quality and fit of their research to the goals of the conference, their financial need, and the benefit they are likely to gain from attending; the selection committee will also ensure that students from a wide range of institutions, including lower-resourced institutions that are less well-represented at academic conferences, can participate. 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 Epithelial ovarian cancer (EOC) is the most common type of ovarian cancer, accounting for 90% of diagnosed cases.6 The standard of care for EOC involves cytoreductive surgery (CRS) to remove as many lesions as possible, or to “debulk” the cancer, followed by chemotherapy. The success rate of CRS is highly variable (25% to 90%) because not all patients are ideal candidates for CRS.1-4 Consequently, non-ideal patients receive suboptimal treatment, which incurs the need for additional procedures, and increases both morbidity and cost. Predicting the success rate of CRS in patients is challenging due to limited screening techniques for assessing the spread of cancer.4,6 Cytalux (pafolacianine, OTL38) is clinically approved for intraoperative guidance of ovarian cancer, but its diagnostic ability is limited by off-site binding in lymph nodes and non-specific background, and it has not been used for preoperative screening.18,19 To overcome this limitation, we aim to develop a novel fluorescence pre-operative screening tool to assess the tumor burden and guide CRS treatment planning. To accomplish this goal, we will develop a novel, minimally invasive laparoscopic paired-agent imaging (PAI) workflow to determine the degree of cancer metastases in EOC. PAI is a molecular fluorescence imaging technique that enhances contrast between cancerous and normal tissue by ratioing the signal from tumor- targeted and non-specific fluorescence probes, thus reducing off-site and non-specific fluorescence. The first aim is to identify a targeted and an untargeted fluorescent agent pair for specifically targeting folate receptor-𝛼 (FR-𝛼) ovarian cancers. We will study the pharmacokinetic and diagnostic accuracy of three targeted (OTL38, mirvetuximab, and a novel anti-FR𝛼 scFv) and untargeted agent pairs to determine the optimal pair with the highest diagnostic performance for identifying lesions. Additionally, the three pairs will be of varying molecular size to examine its impact on clearance, binding affinity, and diagnostic accuracy. The second aim is to develop an integrated dual channel fluorescent laparoscope for in vivo imaging and diagnosis of EOC. The laparoscopic system will be tested and characterized using optical phantoms and in vivo EOC mouse models. The proposed training plan is sponsored by Dr. Kimberley Samkoe, an expert in quantitative fluorescence molecular imaging and experience in translational imaging methodologies. The overall goal of the training plan is to provide the PI, Sanjana Pannem, with foundational skills for pursuing a career in the biomedical industry. The fellowship training plan involves gaining clinical knowledge of the ovarian cancer workflow (Dr. Wilkinson- Ryan), optical imaging system development (Dr. Elliott), development of targeted proteins, (Dr. Ackerman), the selection of imaging agents for clinical translation (Dr. Samkoe), and broadening expertise in software development for visualizing and analyzing fluorescence images (Dr. Paulsen). Additionally, professional skills will be developed through mentorship, attendance of scientific conferences in the biomedical imaging and ovarian cancer fields, and participation in accelerators to gain entrepreneurial experience.

NSF Awards · FY 2025 · 2025-06

This award supports a collaboration between Princeton University and Dartmouth College to explore how self-generated magnetic fields can persist and disperse in turbulent astrophysical plasmas. Astronomical observations of our Galaxy and clusters of galaxies indicate ubiquitous cosmic magnetic fields at the micro-Gauss level, or about one-millionth of the Earth's magnetic field. While weak, such magnetic fields appear to be pervasive and are dynamically important in the Universe even though astrophysical sources of magnetic field generation are often neither steady nor persistent. This collaborative project will use theoretical and numerical modeling approaches to address how present-day galaxies and galaxy clusters not only came to host dynamically important magnetic fields, but also maintain those fields. Such study of the sustenance and longevity of magnetic fields in a turbulent plasma constitutes a key research frontier in plasma astrophysics and basic plasma science. The award will also support an ongoing program of biennial summer schools on plasma astrophysics and astrophysical fluid dynamics for undergraduate and early graduate students. These schools enhance the infrastructure for plasma science research and education in the US by attempting to remedy the relative lack of fluid and plasma physics education in US physics and astronomy curricula. This project will use a combination of analytical theory and a suite of cutting-edge fluid-based and kinetic numerical simulation models to elucidate the decay and diffusion of dynamo-generated magnetic fields in a plasma. The models will take into consideration topological and physical constraints related to magnetic helicity, the plasma particles' adiabatic invariants, and kinetic plasma micro-instabilities. The ultimate goal of this project is to be able to predict the decay laws and the final relaxed state of the magnetic field, including their dependence on the material properties of the plasma. The project will also investigate how magnetic fields that are expelled from spatially localized astrophysical bodies into the intergalactic or intracluster medium subsequently disperse spatially and become volume-filling, and how the kinetic micro-physics of such weakly collisional plasmas helps or hinders this process. This collaborative project will train three graduate students across the two institutions in plasma physics, theoretical astrophysics, and scientific computing, aiding the development of a globally competitive STEM workforce in the US. 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

Plants comprise 80% of the total biomass on the planet and 50-90% of the human diet. Thus, understanding how plants grow and develop is critical for the success of the human population. As in all multicellular organisms, plant cells must communicate with each other to form boundaries between tissues and ultimately establish a body plan. Unlike animal cells, plant cells are surrounded by walls permanently locking cells to their sisters. The cell wall not only establishes boundaries between single cells but also dictates that organ development results from cell expansion that must be coordinated with neighboring cells in the organ. This proposal will investigate how small molecules made by the plant orchestrate organ formation. This project will also contribute to the public’s understanding of plant biology and inspire the next generation of scientists. A teaching program will be launched in rural high schools centered around active learning activities that will enhance student’s knowledge of agriculture and plant science. An annual public science fair will highlight how microscopy propels scientific discovery. Sulfated peptides are a subset of plant peptide hormones involved in regulation of organ formation. These peptides are recognized by plasma membrane-bound receptor-like kinases that contain an extracellular leucine-rich repeat. While many of the peptides and receptors are conserved, it has been challenging to narrow down peptide-receptor pairs and their functions due to the large number of peptides and receptors encoded in seed plant genomes. With a more reduced set of peptides and receptors, the non-seed model plant species Physcomitrium patens provides a unique opportunity to take a genome-wide approach to investigate receptor function. Furthermore the P. patens genome is readily and rapidly edited using CRISPR-Cas9 genome editing, making it possible to perform genome-wide screens of peptide and receptor function. Coupling CRISPR-Cas9 genome editing with forward genetics approaches and proximity labeling the project will map out signaling modules from novel peptides to downstream effectors. The project will provide training opportunities for students from high school through graduate school as well as post-doctoral researchers. 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 In the U.S., legal cannabis is frequently advertised as an effective treatment for mental health problems such as anxiety and depression – particularly online. States that have legalized cannabis have not implemented regulations to address this type of advertising. This project aims to investigate the influence of psychotherapeutic advertising claims (PAC) and mental health warning labels (WL) on online cannabis purchasing behaviors among light-to-moderate cannabis users with symptoms of depression and/or anxiety. The specific aims are to determine if PAC increases cannabis purchasing intentions and if a mental health WL can mitigate this effect. A realistic online cannabis shopping experience will be simulated using the digital “Platform for Online Evaluation of Marijuana Marketing and Sales” (POEMMS). The study will employ a between-subjects experimental design by randomizing 2,000 participants to one of four online stores that vary in PAC and WL content: (1) a control claims (CC) only store, (2) a PAC store, (3) a WL store, and (4) a PAC and WL store. Participants will browse and select items as if making real purchases. Analyses will examine three primary outcomes to determine the influence of PAC and WL on purchase behaviors: (1) total milligrams of THC purchased, (2) average potency (%THC) of products, and (3) overall number of products purchased. The long- term objective is to inform evidence-based cannabis policy and regulatory strategies by understanding the impact of cannabis marketing on vulnerable populations. This research is relevant to public health by addressing the potential risks associated with misleading cannabis marketing, which may lead to increased use and exacerbation of mental health symptoms among individuals with depression and anxiety. The project leverages a multidisciplinary team with expertise in addiction, mental health, epidemiology, and digital health technology. The findings have the potential to inform the development of targeted interventions and policies to reduce harms associated with cannabis advertising, ultimately contributing to better health outcomes and more effective regulation.

NIH Research Projects · FY 2026 · 2025-06

PROJECT SUMMARY First responders are at risk of substance use from exposure to frequent, chronic job-related stressors. Among all first responder career types, Emergency Medical Services (EMS) clinicians have the highest prevalence of chronic stress, mental health problems, and substance use. Cross-sectional studies suggest that higher stress exposures have been associated with higher substance use in first responders, including EMS clinicians. Stress responses can be effectively managed through positive self-regulatory strategies, but the majority of EMS clinicians struggle to cope effectively which increases the risk of maladaptive substance use. Few studies have examined alcohol use among EMS clinicians and no studies have examined cannabis use in any first responders, however cannabis and alcohol are two of the most commonly used psychoactive substances in the U.S. with 16% and 53% of adults reporting past 30-day use, respectively. While studies to date in EMS clinicians have only used cross-sectional survey methods, a within-person approach is needed to capture intensive longitudinal data through ecological momentary assessments (EMAs) within real life environments and test temporal relations between key momentary risk factors for substance use. This study will recruit a national sample of 110 full-time EMS clinicians who completed the preliminary study in partnership with the U.S. National Registry of EMTs and endorse using cannabis and/or alcohol >2 times per week. Participants will complete EMAs at 5 semi-random times per day for 28 days which will contain validated measures on stress, self-regulation, and substance use. Multilevel structural equation models will be used to identify acute within-person temporal impacts between dependent and independent variables in three specific aims: (Aim 1) stress and self-regulation, (Aim 2) stress and substance use (cannabis, alcohol, and nicotine), and (Aim 3) self-regulation and substance use. The main hypotheses are that individuals experiencing more stress based on their own daily average will report lower self-regulation, and individuals experiencing more stress or less self-regulation will be more likely to report substance use. This exceptional mentor team has expertise in substance use and self-regulation (Drs. Stanger and Marsch), intensive longitudinal data methods (Dr. Jacobson), first responder stress and coping (Dr. Watson), national EMS recruitment and engagement (Dr. Panchal), and local EMS community engagement (Dr. Gray). The training plan outlines four short-term goals: (1) interface with EMS clinicians, (2) train on intensive longitudinal analysis, (3) learn about digital therapeutics, and (4) career development and grant writing. This work will inform Mr. Plaitano’s long-term goal of becoming an NIH-funded investigator using intensive longitudinal designs to identify key momentary risk factors for substance use and using these findings to design, pilot, and evaluate future digital health interventions.

NSF Awards · FY 2025 · 2025-05

Recent floods in the rural inland riverine areas of the United States have tested communities in those regions. This project examines how communities vulnerable to flooding respond to compounding disasters of inundation and other ecological stressors. Specifically, the project explores whether the social, technical, and ecological drivers of land-use dynamics in contexts of inland riverine flooding are influenced by localized mutual aid networks. It is well documented that first responders and other officials encounter communication difficulties in the context of flooding events. The researchers ask whether mutual aid and other networks establish obligations and responsibilities that enable recovery and mitigation efforts. The research produces a community-based floodplain mapping tool to improve communication and collaboration across scales in disaster response, recovery, and mitigation. The tool is shared with local communities. The project expands participation in STEM learning for community science youth fellows, undergraduate, and graduate students. Dissemination plans improve engagement with community science and improve the public’s understanding of science and the scientific method. This project is jointly funded by Cultural Anthropology and the Established Program to Stimulate Competitive Research (EPSCoR). This project studies how rural communities respond to overlapping disasters of flood water inundation, and a range of other ecological stressors. In preliminary research, investigators have seen that community members, local responders, disaster response agents, and others do not have easy ways to communicate before, during, and after flooding. This is in part due to lack of shared language, and lack of adequate tools for collaboration across these different groups. This project studies processes of response, recovery, and mitigation work in these river valleys. The team conducts on-the-ground in these rural areas on land-use regulation and practice during and after floods; and how social forces, economic realities, and technical infrastructure shape the impacts of land use. This project focuses on how communication, responsibility, and collective community assistance works after disaster. The researcher will conduct behavioral observation at community meetings; interviews with river corridor and floodplain managers, other rural extension and food security stakeholders, and regional planning commission officers; a survey (n=500) on perceptions of optimal land and river use and risks with residents in three floodplain communities; and archival analyses to gather longitudinal data on flood risk and resilience. The project advances scientific debates about land use practices in rural floodplain contexts, asking whether municipal-level policies of zoning in upstream and downstream contexts influence community responses to flooding. 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 Accelerated growth in early childhood increases risk for obesity, a leading cause of morbidity and mortality. Identifying factors that influence early programming of growth and adiposity is critical for addressing the current obesity epidemic. This is especially important for rural populations, which have a higher burden of obesity in the U.S. Metal exposures disproportionately impact rural populations and increasingly have been associated with adiposity in childhood. However, underlying mechanisms are largely unknown. Breastfeeding protects against childhood obesity and supplies bioactive compounds to the infant that contribute to metabolic programming, which may be altered by environmental toxicant exposures. Human milk is a particularly rich source of microRNAs (miRNAs), which regulate gene expression and play key roles in developmental programming and energy homeostasis. These miRNAs primarily originate in the mammary epithelium and are highly stable when carried by extracellular vesicles and particles (EVPs). Experimental studies have demonstrated that milk-derived miRNAs survive digestion and reach peripheral tissues involved in weight regulation. Preliminary findings from our group indicate that prenatal exposure to metals contribute to accelerated growth in infancy and that human milk miRNAs with known roles in adipogenesis and energy homeostasis are highly sensitive to these same exposures during sensitive windows of mammary gland remodeling (periconception and pregnancy). The proposed research will test the hypothesis that metal exposures during these windows of susceptibility alter the miRNA composition of human milk due to perturbed mammary gland remodeling, contributing to accelerated growth and adiposity in early childhood. We will test these hypotheses in the New Hampshire Birth Cohort Study (NHBCS), a rural pregnancy cohort of private well users in northern New England that is particularly vulnerable to metals exposure. To assess the generalizability of results, we will conduct validation analyses in the Mother’s Milk Study, an urban cohort of Latino mother-child dyads in Southern California. In exploratory analyses, we will use a systems biology approach to integrate other components of the human milk matrix (microbiome, metabolomics, macronutrients, cell composition) to gain a more holistic understanding of human milk miRNA contributions to early growth. Small RNA-sequencing will be used to comprehensively profile miRNAs in EVPs isolated from 400 NHBCS human milk samples collected approximately six weeks postpartum. Genome-wide DNA methylation will be profiled for the cellular fraction of the same milk samples to measure cell composition. Findings from the proposed research will improve understanding of the contributions of an understudied class of epigenetic regulators in human milk to metal impacts on early growth. These results may inform preventive interventions and clinical guidelines that promote human milk quality and reduce early life disparities in obesity.

NIH Research Projects · FY 2026 · 2025-04

PROJECT SUMMARY Systemic sclerosis (SSc) is an autoimmune disease associated with high mortality rates. Current disease- modifying therapies have had limited success in improving clinical outcomes and symptoms. The main clinical manifestation of SSc is skin fibrosis, which results from complex changes in transcriptional and signaling pathways in the skin. Through transcription factor activity network analyses using genome-wide data from the skin, the runt-related transcription factor 1 (RUNX1) has been identified as a key regulator in the skin of individuals with diffuse cutaneous systemic sclerosis (dcSSc). RUNX1 is overexpressed in various human cancers, autoimmune diseases, and fibrotic conditions; however, the specific contribution of RUNX1 to the pathogenesis of SSc skin fibrosis remains unknown. Notably, an association between the severity of dermal fibrosis and increased RUNX1 expression levels has been found in skin biopsies of individuals with SSc. Single- cell RNA sequencing (scRNA-seq) data from the skin of patients with SSc demonstrates enrichment of RUNX1 in fibroblast. We developed a 3D tissue model — called self-assembled Skin Equivalent (saSE) — that incorporates patient-derived fibroblasts and monocytes and shows overexpression of RUNX1 similar to that observed in patients’ biopsies. Our central hypothesis is that RUNX1 is necessary for the cellular transition that results in the generation of the profibrotic myofibroblasts population in SSc. The primary objectives of this study are: (i) to establish the function and molecular mechanism(s) of RUNX1 in SSc-specific fibroblast populations, with the aim of elucidating how RUNX1 drives the activation of dermal fibroblasts, leading to matrix remodeling, increased matrix deposition, and enhanced contractility; and (ii) to assess the impact of inhibiting RUNX1 in a novel, in-vitro SSc skin equivalent model (saSE) in order to determine the effect of RUNX1 inhibition on profibrotic phenotypes and SSc-specific fibroblast populations through single-cell sequencing. The successful completion of this study will provide valuable insights into the mechanistic role of RUNX1 in SSc skin fibrosis. Anticipated outcomes include understanding how RUNX1 influences SSc-specific fibroblast populations, evaluating the effectiveness of inhibiting RUNX1 in reducing pro-fibrotic characteristics in a patient-derived skin equivalent model, and uncovering cellular heterogeneity and gene expression patterns through single-cell sequencing. By combining bioinformatic analyses, an innovative in-vitro 3D skin-like tissue model, and advanced sequencing technologies, this research will shed new light on the role of RUNX1 and its therapeutic potential in SSc dermal fibrosis. The environment at Dartmouth College is ideal for the proposed research, with an innovative, collaborative, and well-equipped research infrastructure that promotes cutting-edge scientific inquiry. Together with the outlined training plan, the proposed work will support my career plan of becoming an accomplished researcher in the field of molecular systems pharmacology and translational therapeutics.

NIH Research Projects · FY 2025 · 2025-04

Hearing loss has been considered a risk factor for Alzheimer’s disease (AD), but the underlying mechanism remains elusive. A “bottom-up” hypothesis has been suggested, where peripheral or cochlear damage at the “bottom” of the auditory pathway accelerates AD pathophysiology by sensory deprivation. This hypothesis is attractive because it suggests interventions to improve hearing might slow or prevent progression towards dementia. Alternatively, a “top-down” relationship may exist where protein deposition within the brain at the “top” of the central auditory processing pathway impairs the brain’s ability to process sound. Our group studies how conditions that produce diffuse brain damage, such as HIV infection, affect the brain’s ability to process complex sounds (central auditory processing). The results show a relationship between performance on central auditory processing tests and cognitive function in individuals living with HIV. This finding led to a NIH-funded supplement to our HIV work to examine these associations in AD. AD is the leading cause of dementia and is defined by the presence of cerebral amyloid-β plaques and tau neurofibrillary tangles. Our results from the supplement show that amyloid-β plaques and tau tangles detected by PET correlate better with central, rather than peripheral, auditory test results in a sample containing both mild cognitive impaired due to AD and cognitively unimpaired individuals. The present project will expand this work and assess the relationship of both peripheral and central auditory test performance to longitudinal amyloid-β and tau tangle deposition in the brain. The relationship to cognitive performance will also be examined. If the “bottom-up” hypothesis is correct, individuals with poor peripheral hearing at baseline, but age and hearing level appropriate central auditory test results, should show a faster rate of protein accumulation over time compared to those who do not. If the “top-down” hypothesis is correct, poor baseline central auditory test performance, relative to age and peripheral hearing function, should show a strong relationship to the rate of brain protein deposition. These findings could provide a mechanistic understanding of the relationship of performance on auditory tests to AD pathophysiology. Also, auditory tests are objective, straightforward, and relatively insensitive to educational and socioeconomic status. If they predict, or correspond with, anatomic disruption in AD, they may be useful for assessing disease progression or the response to treatment over time. The proposal will leverage, and enroll participants into, the TRIAD cohort, a longitudinal biomarkers-based cohort at the McGill University Research Center for Studies in Aging. Participants in this cohort, have PET imaging to detect amyloid-β and tau protein aggregation. In addition to imaging, neurocognitive testing is performed and biosamples (including cerebrospinal fluid) are collected. These data, combined with the auditory tests, will provide the unique ability to determine the relationship between auditory function and multiple biomarkers associated with AD.

NSF Awards · FY 2025 · 2025-03

The human brain is constantly confronted with sensory inputs from multiple modalities. To form a coherent perceptual experience, these distinct sensory signals need to be integrated even though they are received by distinct sensory systems. One possibility is that these signals are combined on the basis of spatial location. In most of our natural experience, the source of sensory signals that are related come from the same location, making it an ideal basis on which to integrate information to form a coherent perception of the world around us. The work proposed here aims to test whether spatial location serves this function for visual and auditory attention. The proposed work tests this mechanism in several tasks and for attention driven by the stimuli, internal control, and prior experience. The project also includes the development of an EEG methods boot camp and other outreach efforts that may aid in workforce development and increase public awareness of the research. In detail, prior research demonstrating spatial selectively for both visual and auditory attention has often been taken as evidence for a ‘supra-modal’ spatial attention system that is tuned to operate similarly across the different senses. The current proposal aims to test key tenets of this spatial attention theory focusing on audiovisual interactions using a combination of psychophysics and EEG. First, it aims to examine the time course of spatial exogenous attention and assesses whether cross-modal attention follows similar temporal dynamics as unimodal attention. Second, it aims to investigate the interactions between exogenous cross-modal attention and endogenous, sustained visual-spatial selection. Finally, the proposed works aims to quantify how selection history in one modality (e.g., audition) affects the spatial prioritization in another modality (e.g., vision) using incidental learning paradigms. The results of the proposed studies have the potential to bring forward a new understanding of how multimodal information is processed and integrated in the brain to support effective stimulus processing, advancing current models of attention and multisensory integration. 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

Distance computation and estimation are among the simplest tasks performed daily by billions of humans and machines worldwide. They are also crucial steps in various optimization algorithms including routing, network design, and information clustering. Compared to distances between higher-dimensional data in abstract spaces, distances in real-life networks possess additional structures which often lead to extremely efficient algorithms that are impossible to achieve otherwise. This project aims to develop novel methods to represent, compress, and sketch distances on networks when geometry is present. This is a timely response to the ever-growing need to summarize massive geometric data. By focusing on simple and practical algorithmic solutions, the project provides a useful toolbox for algorithm designers, addressing important open questions at the frontier of human knowledge. In addition, the integrated education and mentoring plan sets the goal to enhance mathematical literacy and critical thinking skills among local college and high-school students in the New Hampshire and Vermont area. Geometric constraints on graph metrics arise from the interaction between the graph and its ambient space that often comes with simple topological or Euclidean structures. The project focuses on various types of geometric metrics, such as planar distances, p-norms (i.e., a norm on suitable real vector spaces given by the pth root of the sum – or integral – of the pth-powers of the absolute values of the vector components) and their generalizations, and hop distances on geometric shapes. These metrics are common in applications like computer graphics, vehicle routing, and shape analysis, and they also appear implicitly in string editing in bioinformatics and configuration spaces in robotics. The main theme is to design a robust and versatile distance sketching toolbox using geometry, with a tradeoff option between accuracy and efficiency, while remaining lightweight in resource usage. The techniques are involved and rely on the interplay between different research fields, such as metric embeddings, topological graph theory, and geometric algorithms, aiming to study optimization from a graph partitioning perspective. These tools will then be used to tackle problems where current algorithmic solutions are inefficient, inaccurate, or nonexistent. The long-term goal is to provide a systematic way to examine distance-related problems, choose the most effective tools, and estimate resource usage before implementation. This project is jointly funded by Algorithmic Foundations 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 · 2025-03

This project builds an artificial intelligence (AI) infrastructure that enhances access to computational power, datasets, and models that support research on social policy and poverty. It will develop a novel trustworthy AI infrastructure that will 1) integrate, curate, and process diverse policy-related data sets; 2) develop and facilitate access to novel AI models that can learn from existing policies, providing insights such as what makes a program successful; and 3) open new areas of research and scholarship, creating multi-disciplinary communities of policymakers, economists, computer scientists, and government and non-government organizations to better address these societal challenges. This project demonstrates how the resources made available through the National Artificial Intelligence Research Resource (NAIRR) Pilot program can be employed to address a major social challenge - poverty. The effort develops a novel, trustworthy AI infrastructure that combines the power of foundation models (FM) with the reasoning capabilities of probabilistic graphical models (PGM) for evidence-based poverty eradication research. This project mitigates several technical challenges related to data, models, and their evaluation, providing foundational and use-inspired advances by: 1) Developing novel methods to build a knowledge database from diverse unstructured poverty eradication literature, such as academic literature and impact evaluations; 2) Combining the linguistic capabilities of LLMs with the reasoning capabilities of a PGM to answer policy-relevant questions; and 3) Developing methods to identify, quantify, and mitigate biases that may be induced in the system, to ensure that these systems are safe and trustworthy when deployed. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-03

This I-Corps project is focused on the development of small robots suited to navigate commercial row-crops in-season and autonomously, enabling them to produce higher yields with fewer resources. In an era of narrowing profit margins and labor shortages, robotic equipment offers the potential to improve agricultural production. Autonomous nursery robots enable management strategies that are not possible with conventional equipment. For example, nitrogen fertilizer can be applied periodically across a plant's lifecycle, reducing stress, enhancing yield, and minimizing material loss through leaching and volatilization. Other applications include foliar feeding, weeding for reduced herbicide use, and field-variable nutrient assessment. These robots also collect data that farmers can use to refine strategies, transforming intuition into data-backed insight. This capability reduces waste, aligns farming with sustainability goals, and meets market and regulatory demands. Additionally, these lightweight robots reduce anthropogenic soil compaction, a common consequence of traditional heavy machinery, promoting healthier soil. This I-Corps project utilizes experiential learning coupled with a first-hand investigation of the industry ecosystem to assess the translation potential of the technology. This solution is based on the development of novel, tactile-based perception and navigation systems designed to allow small off-road robots to operate in messy, stalky row-crop environments like under-the-canopy of a cornfield. This tactile navigation system supplements traditional visual methods, providing redundancy against sensor occlusion and feature extraction difficulties in the presence of weeds and leaves. Nearby stalks and obstacles can be detected and localized in the robot's periphery using tactile sensing, allowing for autonomous navigation even when visual data is unavailable. Robots equipped with this system can autonomously navigate through production cornfields entirely blind, detecting and positioning plants with accuracy. In-season management strategies can be unlocked with a robust navigation system. Early trials demonstrate that yield can be improved by ~10%, using ~20% less fertilizer when the robot spoon-feeds fertilizer to corn slowly over time, providing a clear indication of the economic potential of the technology. 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 · 2025-03

Aspergillus fumigatus (Af) is a common environmental mould that can cause high-mortality mycoses, such as Invasive Pulmonary Aspergillosis (IPA). Disease caused by A. fumigatus has remained significantly difficult to diagnose due to physical limitations of sample collection and limited diagnostic methods, meaning Af-mycoses are often not definitively, if ever, diagnosed until disease has progressed to a severe state. Contemporary clinical diagnosis of A. fumigatus disease relies on non-culture-based methods of organism detection including Platelia and FungiTell microplate assays to detect fungal galactomannan antigen and beta-glucans respectively. However, the extent to which heterogeneity in A. fumigatus clinical isolates impacts disease diagnosis has not been studied. Numerous clinical observations over the years strongly suggest significant heterogeneity in A. fumigatus morphologies that I hypothesize impacts diagnostic results. Our lab has previously identified that increased expression of a subtelomeric gene hrmA via SNP D304G (strain: HrmAREV) is sufficient to induce a clinically observed hypoxia-fit morphologies (H-MORPH) of A. fumigatus. H-MORPH is clinically relevant as strains exhibiting this morphology can be isolated from patients, however it remains unknown how this morphology impacts the ability to detect and diagnose IPA. My preliminary data suggests that the lab-generated H-MORPH HrmAREV exhibits increased levels of both beta-glucan and galactomannan antigens compared to isogenic N-MORPH strains in vitro. My central hypothesis is that H-MORPH isolates will result in the increased ability to detect and diagnose IPA both in vitro and in vivo. To address this central hypothesis, I will pursue the following two aims: 1.) I will test the hypothesis that the H-MORPH associated gene, hrmA, regulates antigenic extracellular polysaccharide composition, and 2.) I will test the hypothesis that HrmA induction increases the ability to diagnose in vivo infection using contemporary clinical diagnostic markers. As we have previously identified that HrmA has a weakly predicted RNA recognition motif (RRM) I hypothesize HrmA mediates the alteration of the extracellular polysaccharide profile through post- transcriptional RNA modulation, which I will probe with targeted RNA immunoprecipitation. After determining the extracellular polysaccharide composition, I will use N- and H-MORPH strains in vitro and in vivo to determine how morphology impacts detection using clinical diagnostic Fungitell and Platelia microplate assays. In my approach, I will combine genetics, biochemical assays, and clinical microbiology diagnostic assays to determine the role of HrmA in A. fumigatus clinically relevant diagnostic antigen production. Overall, the experiments outlined in this proposal will identify a role for the fungal specific gene, hrmA, in modulating fungal biology through translational implications of disease as it relates to a clinically relevant morphotype of A. fumigatus, while providing me with important pre-doctoral training in fungal genetics, biochemistry, bioinformatics, and clinical microbiology.

NSF Awards · FY 2025 · 2025-02

This doctoral dissertation project examines sustainability initiatives among corporations in the private sector. Sustainability initiatives are common and contextualized by concerns about the environment and resource management. Tradeoffs may arise, however, between environmental and economic considerations, and these tradeoffs can shape the implementation of corporate sustainability initiatives. This project provides an ethnographic study of the workers, including both company employees and independent contractors, who design and implement the initiatives along supply chains. The study explores the extent to which workers’ social relationships, backgrounds, practices, and values contribute to variation in their attempts to make corporate supply chains more transparent and environmentally sustainable. While providing a training opportunity for an early-career scientist, the findings of this project provide feedback to the organizations and individuals who are advancing and monitoring corporate sustainability. In contrast to previous scholarship that examines the governance of corporate sustainability at the level of firms and organizations, this study focuses on the experiences and orientations of individuals who engage with sustainability initiatives at multiple stages along a supply chain. As a multi-sited ethnography, it uses interviews and observations of a sample of individuals and settings to infer the practices and knowledge that constitute sustainability work and the variability that arises from factors such as material conditions and social relationships. The project also elucidates the extent to which value is heterogeneously attributed to the outputs and processes of sustainability labor. The empirical findings of this project contribute to labor geographies, science and technology studies, and scholarship on political ecology. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-02

How do brains, and a brain structure called the hippocampus in particular, learn from one experience and apply that learning to a different situation? This ability to generalize is at the core of our success in adapting quickly to a wide variety of new situations, and in making efficient use of limited experience, but how brains do this is still unknown. By observing how neurons change their activity during learning, how subsequent replay of that activity supports these changes, and capturing these changes in computational models, this project aims to uncover universal principles of how brains extract generalizable knowledge from experience. To accomplish this goal, the investigators build a new experimental setup in their lab that allows them to use recently developed neuroscience tools to precisely monitor brain activity of mice in a cognitive learning task. Because these powerful new technologies generate vast amounts of data, many researchers would like to use them but do not yet have the expertise how to do so. To address this issue, the investigators develop and freely share tutorials and resources to make these new technologies more accessible for other researchers, and teach methods for how to process and analyze such data at neuroscience summer courses. The hippocampus is widely implicated in generalization and inference, i.e., the efficient use of limited experience in novel situations, but how these processes are realized in the activity of neurons remains unclear. Prior animal work on the neural basis of these cognitive processes has primarily focused on spatial navigation experiments, contrasting with an extensive body of associative learning experiments in animals and humans which generally use discrete stimuli. To bridge this gap, the investigators build and validate an experimental setup for head-fixed, acute Neuropixels recordings in mice learning about discrete odor stimuli. The setup then is used to test theoretically motivated questions about a) the role of hippocampal replay in generalization and inference, b) changes in representational similarity during structure learning, and c) the role of dopamine and acetylcholine in signaling prediction errors that are thought to drive representational updating. In parallel, the investigators develop freely available tutorials and documentation for the preprocessing and analysis of Neuropixels data to facilitate the adoption of this technology by other researchers, and teach these methods at neuroscience summer courses. 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 · 2025-02

Project Summary. The advent of molecular therapies for cancer and autoimmunity have led to a rise in the number of serious infections caused by environmental microbes, exemplified by invasive aspergillosis (IA). While Aspergillus fumigatus is normally a benign environmental saprophyte, this ubiquitous mold can cause life-threatening invasive disease in the setting of leukopenia and/or high dose corticosteroid treatment. Fungal pathogenicity in leukopenic or corticosteroid-treated populations is historically thought to be a global property of all environmental A. fumigatus strains, based on their common property of reaching terminal airways and growing at human body temperatures. Recent bedside to bench research from our laboratories is challenging this long-standing paradigm of A. fumigatus strain-agnostic pathogenicity. Patients undergoing pharmacologic inhibition of Bruton’s tyrosine kinase (BTK) for lymphoid malignancies have an unexpected risk for IA. However, murine model studies to define the mechanism of A. fumigatus susceptibility during BTK inhibitor therapies revealed a striking fungal strain-specific pathogenicity. Standard pathogenic reference strains that are highly virulent in murine models of leukopenia or corticosteroid treatment failed to cause disease in BTK- deficient or -inhibited models. However, clinical isolates from BTK therapy patients initiated invasive disease and caused host mortality. Immunologic studies revealed that BTK inhibitors (BTKi) such as Ibrutinib surprisingly blunted myeloid antifungal activity, specifically the function of neutrophil NADPH oxidase and primary granule exocytosis. Our working hypothesis is that A. fumigatus strain-specific pathogenicity in the setting of BTKi is mediated by alterations in the fungal genetic network responsible for susceptibility to NADPH oxidase- and degranulation-mediated killing. In this proposal, we propose two aims to define the A. fumigatus strain-specific pathogenicity determinants responsible for IA in the setting of BTKi therapy. In aim 1, we utilize novel whole genome protein kinase, phosphatase, and transcription factor null mutant collections to define the genetic network responsible for fungal cell viability during interactions with host neutrophils. Preliminary data identified 3 protein kinases and 1 protein phosphatase whose function mediated susceptibility to neutrophil killing. These key regulatory proteins will be utilized to define the genetic network mediating neutrophil fungal killing susceptibility. In Aim 2, we leverage our novel collection of A. fumigatus isolates from patients on BTKi therapies. Preliminary whole genome sequencing data of these isolates identified a loss of function allele in the same protein phosphatase identified in our genetic screen in Aim 1. Further studies will detail the pathogenesis of these clinical isolates in our BTKi murine models and conduct mechanistic genetic analyses to pinpoint the key A. fumigatus pathogenicity determinants driving IA in this specific host setting. Our proposed studies are expected to reveal unexpected novel fungal pathogenicity determinants in the host setting of precision medicine therapy that is rapidly being employed in the clinic for the treatment of cancer.

NIH Research Projects · FY 2026 · 2025-01

PROJECT SUMMARY Eukaryotic cells tightly control their size to maintain proper cell physiology. Defects in cell size control can lead to developmental infidelity and disease. One mechanism for accurate cell size control is the coupling of cell growth and division. We use the fission yeast, Schizosaccharomyces pombe, which has a reproducible rod shape and strong genetic tools to study cell size control. In fission yeast, a cell size checkpoint delays entry into mitosis (the G2/M transition) until cells have grown to a critical size threshold. This checkpoint acts through activation of the cyclin-dependent kinase Cdk1 in complex with its cyclin subunit Cdc13. Recent work has shown that the nuclear concentration of Cdc13/cyclin increases over time, providing a mechanism to promote increased Cdk1 activity as cells grow. Nutrient limitation is known to reduce cell growth rate and cell size at division, meaning that the size control system monitors and responds to nutrient levels. It is not known how the Cdc13 time-dependent nuclear accumulation for cell size control is regulated under normal and modified growth conditions. The central hypothesis is that two factors are regulated by nutrient availability which connects size and the environment: time-dependent accumulation of Cdc13 in the nucleus and the threshold concentration of Cdc13 that promotes mitotic entry. To test this hypothesis, I will first determine the regulatory mechanisms of Cdc13 nuclear accumulation by measuring rates of nuclear import, nuclear export, and degradation. I will utilize a combination of live-cell microscopy techniques including photobleaching and photoconversion methods. Second, I will define how altered nutrient limitation modulates Cdc13 nuclear accumulation and its regulation. I will quantify the nuclear accumulation of Cdc13 under different nutrient conditions, as well as explore the role of the nutrient sensing pathways, such as AMPK and Greatwall-Endosulfine, in setting a PP2A threshold for the control of Cdc13 nuclear accumulation. The proposed work will establish a systems-level understanding of cell size control and how it can be tuned by environmental conditions. In addition to the significant scientific contributions this work will make in the field of cell size control, I will also gain invaluable technical skills, knowledge, and communication experience.

NSF Awards · FY 2025 · 2025-01

NON-TECHNICAL SUMMARY This CAREER award supports computational and theoretical research for modeling crystallization in semicrystalline polymer blends, such as recycled commodity plastics. In these blends, crystallization is impacted by phase separation between different polymeric species during processing, which results in undesired final morphologies and degraded material properties. The inferior properties of recycled plastics make them less competitive than virgin polymers, leading to a low recycling rate. Understanding and quantitatively modeling crystallization in these phase-separated polymer blends is key to enhancing their material properties and potentially helping resolve the environmental crisis caused by plastics. The PI plans to combine computer simulations and theoretical tools to directly probe how different polymers crystallize near the interfaces in phase-separated blends. The project will also reveal the effects of interfacial compatibilizers, which can bridge different polymer domains across the interfaces, on the sample mechanical properties. Based on the molecular simulation results, the team will construct a numerical simulation algorithm to predict crystallization near the interfaces in polymer blends, which will permit efficient prediction of material structures and properties for semicrystalline polymer blends. Overall, the research will help guide the development and optimization of a wide range of semicrystalline polymers, including recycled plastics and functional polymers. The education and outreach components of this project will provide training on basic programming skills and simulation techniques to high school, community college, and undergraduate students via a series of in-house designed open-source training modules. To disseminate knowledge about polymer sustainability and recycling to the general public, including K-12 students, the research team will develop a novel mobile app. This app will utilize machine learning to recognize commodity polymers from recycling symbols and then introduce their molecular information and recycling strategies to the users. TECHNICAL SUMMARY This award supports the development of a multi-scale framework for quantitatively modeling polymer crystallization, one of the grand challenges in polymer physics. Motivated by the lack of a mechanistic understanding of crystallization in polymer blends, the research will reveal the crystallization mechanism for semicrystalline polymer blends and develop a novel computational approach for predicting polymer crystallization in phase-separated blends. Specifically, the project consists of four interrelated aims: 1) predict the free energy landscapes of crystallization for polymer blends, including polyethylene (PE) and isotactic polypropylene (iPP), 2) reveal the crystallization mechanism near phase-separated interfaces for PE/iPP and semiflexible bead-spring mixtures, which mimic other semicrystalline blends, 3) elucidate the effects of amorphous stress transmitters near interfaces, including entanglements and additives such as block copolymer compatibilizers, on the sample mechanical properties, and 4) develop a phase-field model to predict the semicrystalline morphologies of polymer blends after a long crystallization time. By predicting the crystallization, semicrystalline structures, and mechanical properties, this project will lay the foundation for optimizing the properties of recycled polyolefins, and in turn, promote a more sustainable plastics industry. The multi-scale approach will also guide material design for other materials, such as (semi)conducting polymers, for which the electronic properties are governed by tie chains and interfaces. The broader impact of the research includes providing training and education on computational and theoretical research to high school, community college, and undergraduate students using in-house designed open-source training modules. These training modules will prepare students for performing simulations and data analysis to solve research problems. The PI team will also develop a phone app to promote polymer recycling and sustainability. This app can identify the type of plastics by scanning the recycling symbol using the phone camera. After identification, the app will introduce the molecular features and properties and the recycling strategy and challenges of this polymer. The PI will use the mobile app in outreach activities to help enhance public awareness of sustainability. STATEMENT OF MERIT REVIEW 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.