University of Hawaii

NSF Awards · FY 2025 · 2025-01

The global biodiversity crisis is a central problem facing humanity, yet we lack the means to assess biodiversity at the pace of the Earth's changing environment. For this project, rapid assessment technologies will be integrated at the landscape and island level to forecast unseen change in high-impact insect and spider populations tracked by their DNA. The project goal is to infer processes that shape biodiversity and its decline, and how these processes might be captured remotely across different scales and degrees of human impact. In the Hawaiian Islands, the velocity and extent of non-native plant invasions in ecological landscapes will be measured using satellite, helicopter, drone, and ground-based monitoring systems. Those metrics will be combined with assessments of insect biodiversity at the same sites generated from rapid, high-throughput environmental genomic analyses. Outcomes will aid land managers with actionable solutions, building on the ongoing activities of the research team and working with the Pacific Regional Invasive Species and Climate Change (Pacific RISCC) Management Network. Results will be translated for the general public through the web-based ESRI ArcGIS StoryMap. The researchers will provide mentoring for undergraduates, graduate students and a postdoc at the University of California Berkeley, the University of Maryland, and the University of Hawaii Hilo, the latter of which is a primarily undergraduate serving institution that helps meet the needs of Pacific Islanders. Products will include the development of a learning module and toolkit for students to adopt new skills of data analysis and visualization for communicating biodiversity and remote sensing data. Using the model system of the Hawaiian Islands, the project will couple high-throughput arthropod biodiversity sequencing and remote sensing imagery to examine correlated shifts across two orthogonal gradients set within the same native forest type. The first gradient is a geological chronosequence, from 0-5 million years, across which arthropod communities increase in diversity and become more ecologically specialized. The second, intersecting, gradient is composed of a landscape matrix that runs from native to heavily invaded forest habitats on each island. At plot scales, whole arthropod communities will be sampled using genetic signatures from high-throughput sequencing to test models of community assembly over extended ecological-to-evolutionary time, and hence infer the changing roles of key processes of filtering, competition, and neutrality, through time. The models will predict trajectories of disassembly in the face of rapid biotic change. Arthropod community analyses will be coupled with remote sensing imagery at scales ranging from regional (archipelago; satellites), to area (leeward slope of one mountain; helicopter), to plots within heterogeneous landscapes (drone imagery and airborne and ground lidar). The different remote indicators of change in the ecosystem (spectral properties, leaf and water content, nitrogen content, plant stress) will be integrated by using structural equation models (SEMs) to identify candidate parameters that reflect arthropod community dynamics in rapidly changing island forest systems. Joint species distribution models will be used to integrate data across scales. This research will test the predictability of remote sensing data for explaining the spatio-temporal variability of biodiversity and its resilience to anthropogenic modification. In addition to training at the undergraduate, graduate and postdoctoral levels, products will include the development of a learning module and toolkit for students to adopt new skills of data analysis and visualization for communicating biodiversity and remote sensing data. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-01

This conference grant will provide critically needed financial support for non-tenured early career researchers to attend the AGU Chapman Conference on Caldera-Forming Eruptions at Basaltic Volcanoes, taking place in Hilo on February 9-14, 2025. Participant support costs (travel, registration, lodging) cover the attendance of >25 early career researchers, including postdoctoral researchers, graduate and undergraduate students from Hawaiian and other US-based institutions. This conference builds upon a prior Chapman conference held in Hawai'i in 2012, which examined the state of knowledge about Hawaiian volcanism and also a recent review article on the 2018 eruption (Anderson et al. 2024). The big picture questions driving the conference include: (1) What are the similarities and differences among basaltic Caldera Rift Eruptions (CRE)? (2) How is magma transported in basaltic rift volcanoes, and how do magmatic- tectonic systems interact before and during large CREs? (3) How and why do basaltic calderas collapse? (4) What are the hazards due to large CREs, and can these eruptions be effectively forecast? (5) How do large CREs alter volcanic systems, and how do they recover? Tackling these questions will promote scientific progress by aiding in synthesizing the community’s understanding of some of Earth’s most active volcanic systems, by identifying outstanding open questions, and planning future research directions. This conference grant supports scientists in their early stages of professional development, from college undergraduates to researchers who recently graduated with doctoral degrees to attend the AGU Chapman Conference on Caldera-Forming Eruptions at Basaltic Volcanoes. The aim is to provide these early career scientists a highly interactive conference that will serve as a springboard for them to (1) get to know and better understand some of Earth’s most active volcanic systems, (2) have an opportunity to meet and mingle with volcano researchers from all over the world, and (3) inspire or reinforce volcano career paths, particularly in the case of college students. The funds obtained through this grant promote equity and inclusivity in science by sponsoring students and researchers that could not otherwise attend because of the significant costs associated with registration, travel and lodging. Workshops, discussion panels, working groups, professional development seminars, and non-technical social events will encourage community- and network-building and both formal and informal interactions among researchers. A key aspect of this conference is its interdisciplinary nature, with specialists from very different fields coming together to focus on key unanswered questions about volcanoes in Hawai'i and elsewhere in the world. Supporting attendance of scientists in the making will help foster a future generation of volcanologists that can better understand and interpret vast, complex data streams to better anticipate volcanic eruptions and their hazardous impacts on local 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.

NSF Awards · FY 2025 · 2025-01

This project provides funding for the Research Vessel Kilo Moana to conduct oceanographic research missions supported by the National Science Foundation. The oceanographic research vessels of the Academic Research Fleet (ARF), operated by the academic institutions within the University-National Oceanographic Laboratory System (UNOLS) framework are multi-use facilities used to expand knowledge of the ocean environment. The surface work of these ships is complemented by human-occupied, remotely operated, and autonomous undersea vehicles and sensors that provide vital tools to understand the oceans and their resources. These seagoing research and educational facilities enable scientists and students to study natural phenomena and train future scientists while on board state-of-the-art oceanographic research vessels utilizing high-quality instrumentation. The ship operators will also conduct learning activities for students and the general public including hands-on demonstrations of marine science research guided by faculty, students and ship crew members. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-01

This award will support a workshop on Parallel Algorithms and Data Structures at the University of Hawaii, Manoa, March 17-21, 2025. Parallel Algorithms research is an important topic, since parallel computing hardware is omnipresent in many application domains, whether based on multicore processors, graphic processing units (GPUs), or other emerging structures, but most current algorithms research is still following the single-processor sequential model. The workshop will bring about 40 researchers together, including 15 doctoral students, to identify, formalize, and attempt to solve problems in parallel algorithms and data structures. It will contribute both to the research progress of the field and the research involvement of the doctoral students. The University of Hawaii is a Pacific-Islander-serving institution in an EPSCoR state. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-01

Yeasts are important in industry, impact human health and food safety, and play critical roles in ecosystems. Yeasts’ simple body shape, and unique foraging strategies enable them to colonize habitats where few other organisms can survive, and where few scientists tend to search for fungi: such as within lichens, in streams and pools, and in high salt environments. It is estimated that scientists have discovered only 1% of the yeast species thought to exist on earth. This gap in knowledge of yeast diversity and distributions makes it difficult to understand the evolutionary history of the fungal tree of life, including mushrooms, medicines and symbionts upon which human livelihoods rely. Systematically collecting and describing these yeasts facilitates accurate identification of pathogens, and of the cryptic biological diversity comprising “microbiomes” that reside inside plants and animals. This project will focus on isolating and describing yeasts in the Basidiomycete class Pucciniomycotina, which are only distantly related to baker’s and brewer’s yeasts, and much less studied. The research will leverage the environmental diversity of Hawaiʻi, and the evolutionary diversity of zoo animals to maximize recovered yeast diversity from plant, animal, and environmental samples. The project will use a combination of genome sequencing, physiological data, and culture characteristics to publish formal descriptions and phylogenetic analysis of hundreds of novel species. The research will assess whether, and to what extent, yeasts co-evolved with their animal hosts. New insights into yeast diversity will be used to predict global species diversity, host/habitat specificity, and diversity hotspots. The project will increase the participation and research capacity of underserved groups (particularly Native Hawaiian and Pacific Islanders) via support for postdoctoral and student researchers, and formal training opportunities. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-01

This research will measure the deformation of the seafloor off Kīlauea volcano, Hawaiʻi at four sites for a 4-year period. Underlying the flank of the volcano is a nearly horizontal fault that is similar to the major earthquake faults at subduction zones. This study site makes a good natural laboratory to study this type of fault. This study also will reoccupy several sites last measured in 2004 to get a 20-year record of deformation. Over this time, the fault has experienced a major earthquake, on-going quiet creep, and a volcanic eruption in 2018. The combined deformation record will be 5 years of horizontal motion and 20 years of vertical uplift. Results will show where the fault slipped and how that slip is connected with earthquakes, sliding between earthquakes, and non-earthquake slip events. This research on Kīlauea's deformation will improve seismic and tsunami hazard assessments both in Hawai’i and at subduction zones. This project will train a graduate student. The data and products will contribute to community outreach and education efforts. This project will support deployment of a seafloor geodesy network of 4 GNSS-Acoustic sites on the submarine south flank of Kīlauea volcano on the Big Island of Hawaiʻi to measure horizontal displacement rates along a profile above the Kīlauea décollement. Pressure surveys, reoccupying benchmarks previously measured in 2004, will determine the 20-year cumulative and the current vertical deformation rates. This structure has experienced regular slow-slip events, a major (Mw7.2) earthquake, persistent aseismic creep, and a pressure change within Kīlauea’s magmatic system following the dramatic 2018 eruption and summit collapse. Understanding which combination of seismic and aseismic slip processes occurring on discrete sections of the fault, and how they transfer stress, is critical to understanding the evolving stress state of the structure. Measuring deformation will answer several important questions: 1) What is the geometry of the fault system offshore? 2) Where does slip connected with earthquakes, interseismic creep, and slow-slip events occur? 3) What processes control stress transfer within the offshore fault system? 4) How do these tectonic processes respond to or impact volcanic events? A better understanding of the mechanical and dynamical behavior of Kīlauea’s submarine décollement will improve seismic and tsunamigenic hazard assessments both here and at subduction zones which have similar structures and active processes. This project will train a graduate student in seafloor geodesy, and the data and products generated by this project will contribute to community outreach and education efforts. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-01

Understanding what drives the evolution of new species is a central question in biology. Groups of species that have recently evolved provide a good system for trying to understand the genetic changes that led to establishment of new species. This research combines the fields of genomics, developmental biology, ecology, and physiology to examine a new lineage of flowering plants in Hawaiʻi in the genus Bidens (family Asteraceae). The project will generate new genome assemblies and experimentally identify the genetic and developmental changes responsible for leaf, fruit/seed, and flower evolution in this group of species. This project will also provide training in inter-disciplinary evolutionary concepts and approaches for undergraduates, graduate students, and postdoctoral researchers, including those from underrepresented groups; improving the scientific workforce in the United States by preparing them to strongly contribute to scientific research, education, and/or technological advancements. This project will use newly developed genome sequencing methods to infer the broader evolutionary history of Polynesian Island Bidens, along with continental relatives. The updated understanding of how Bidens reached remote Pacific islands and diversified will provide the backbone for comparative evolutionary genomics of our six target species (three Hawaiian endemics and three continental). Comparing these genome sequences and differences in gene expression will allow us to identify the genetic changes that contribute to the unique ecological and morphological diversity of the Bidens adaptive radiation. Concurrent with the other objectives of the project, undergraduate students at UH Mānoa (a Native Hawaiian serving institution) will receive year-long internships in Hawaiʻi and short-term exchanges at Auburn (AU) and Wisconsin (UWM) via AHi-WiRE; Auburn-Hawaiʻi-Wisconsin-Research Exchange to receive training in plant evolutionary genomics. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-01

Today, cosmology stands at a crossroads, with surveys of Type Ia supernovae revealing multiple indications of potential new physics beyond what is predicted by the standard cosmological model. At the University of Hawaiʻi (UH), two of the most productive supernova surveys, Pan-STARRS and ATLAS, are currently being operated. However, advancing cosmology research using these data requires a large team of experts to tackle complex challenges related to data quality, systematic uncertainties, and parameter inference. Duke University astrophysicists have played a pivotal role in nearly all recent and next-generation cosmology surveys. This proposal aims to establish a collaboration between UH and Duke University, creating a robust support system that positions UH cosmologists as leaders in the field. The collaboration will address some of the most profound questions in cosmology today, such as whether the growth of structure and locally measured expansion of the Universe is consistent with the standard model, and the nature of dark energy. In pursuit of these goals, the project will also partner with high school programs in North Carolina and Hawai‘i to introduce diverse students to STEM research. These programs include 1) Maunakea Scholars, 2) Hawaiʻi Student/Teacher Astronomy Research (HI-STAR), and 3) Duke Cosmology Development Via In-situ Learning and Study. Currently, cosmology is at a pivotal moment, with Type Ia supernova (SNe Ia) surveys positioned to either confirm or challenge recent indications of new physics beyond the ΛCDM cosmological model. This project outlines a research collaboration between UH and Duke University to create a support system that will empower UH cosmologists to lead the next decade of cosmological parameter measurements. The collaboration will leverage UH-led supernova discovery surveys, which will significantly reduce key systematic uncertainties in cosmological parameters by combining calibration systems and supplementing future surveys with enhanced cadence and color data. However, addressing complex challenges related to data quality, systematic uncertainties, and parameter inference will be crucial. Given Duke University’s critical role in nearly all recent and future cosmology surveys, it serves as the ideal partner for this collaboration. The project will focus on assembling and validating low-redshift SNe Ia samples, providing a critical anchor for higher-redshift data. To guide the work, the collaboration will include four one- to two-week visits to Duke University, spaced every six months, involving a postdoctoral scholar and a UH graduate student. The overarching scientific goal will be to determine, over the next decade, whether the ΛCDM model accurately describes the Universe. Additionally, the project will partner with existing high school programs in both North Carolina and Hawai‘i that introduce diverse students to astronomy. These programs include 1) Maunakea Scholars, 2) HI-STAR, and 3) Duke Cosmology Development Via In-situ Learning and Study. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2025 · 2025-01

The Haleakala Neutron Monitor Workshop will be held in Honolulu, Hawaii, in January 2025. The workshop will bring together approximately 50 participants from Hawaii, mainland USA, Thailand, Mexico, and other countries to celebrate the installation of two neutron monitors at the Haleakala summit. These monitors provide unique capabilities for observing galactic cosmic rays and solar neutron particles, contributing valuable data for studying cosmic ray physics, atmospheric interactions, and radiation hazards. This workshop will bring together experts, early-career scientists, and engineers to foster collaboration, exchange knowledge, and address key scientific questions about particle propagation, solar events, and nuclear interactions in Earth’s atmosphere. The five-day workshop, to be held at the University of Hawaii at Manoa and Haleakala, will feature plenary talks, technical sessions, and a site visit to the Haleakala summit for a ribbon-cutting ceremony and tour of the Daniel K. Inouye Solar Telescope (DKIST). The final day will focus on exploring synergies between neutron monitor data and DKIST’s solar science objectives. Early-career participants will have the opportunity to present research in plenary sessions and engage with senior scientists, building connections across neutron monitoring, space weather, and atmospheric 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 2024 · 2024-12

With support from the Environmental Chemical Sciences Program in the Division of Chemistry, Emily Marron at the University of Utah and Daniel McCurry at the University of Southern California and their students will study chemical processes occurring in wastewater treatment, specifically, when chlorine is added to water to remove harmful bacteria and viruses. However, the addition of chlorine to wastewater also results in the production of unintended chemical byproducts that may be toxic. This project will characterize the reaction of chlorine with alcohols, such as methanol (wood alcohol) and ethanol, which are present in wastewater, to produce aldehydes, such as formaldehyde and acetaldehyde, reactive compounds that can have deleterious biological properties, particularly in adducting biomolecules, including nucleic acids and proteins. Understanding the chemistry of aldehyde production from alcohols and chlorine is important to minimize the formation of these chemicals during wastewater treatment. In the face of climate change and drought, communities across the United States lack reliable sources of drinking water. Re-using wastewater (sewage) is an option to increase water supply in areas facing water stress. Wastewater reuse involves many treatment steps to ensure the water is safe to drink. Undergraduate researchers from both institutions will contribute to the work and inform the scientific community about the project findings through social media. During wastewater reuse, oxidation with ozone or chlorine to inactivate pathogens and transform chemical contaminants can form toxic low molecular weight compounds including aldehydes. While aldehyde generation from ozonation of wastewater is well understood, the kinetics, mechanism of formation, and potential precursors during chlorination are largely unknown. This project will investigate the formation of aldehydes from the chlorination of an overlooked group of precursors: alcohols. Preliminary experiments have demonstrated that methanol can be oxidized to formaldehyde by chlorine under conditions relevant to water treatment. Alcohols such as methanol and ethanol are frequently used as a supplemental carbon source during conventional wastewater treatment, and are likely present in water reuse operations. Additionally, alcohols are routinely used in environmental chemical research for stock solution preparation under the assumption that they are inert with respect to chlorine. The goals of this project include determining the kinetics, products, and mechanism of aqueous alcohol oxidation by chlorine, the development of a new method for quantifying trace alcohols in complex aqueous matrices, and its application to quantify alcohols in wastewater effluent and their contribution to observed aldehyde formation. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-11

The project will determine how microbes change the response of their host organism to climate change. This research focuses on Hawaiian honeycreepers, a diverse group of birds. Honeycreepers are important in sustaining Hawaiian ecosystems and the cultural identity of indigenous Hawaiians. However, over half of the species have gone extinct, and most of the remaining species face imminent extinction. The driver of this extinction crisis is an introduced avian malaria parasite transmitted by an invasive mosquito species. Government and community partners are working together to suppress mosquitoes and prevent avian malaria transmission. Mosquitoes are being suppressed by releasing sterile males into the environment. These males are sterile because they have a bacterium that lives inside their cells. When male mosquitoes with these bacteria are released, they mate with wild females and decrease their reproduction. However, ecological knowledge gaps may limit the plan’s efficacy. This project will fill these gaps by determining where to release of these male mosquitoes on the landscape and how to increase their mating success following release. This project has broad implications for the management of mosquito-borne diseases, including those that affect human health. In addition, this project will engage in workforce development with native Hawaiians to help restore natural resource management agency to this indigenous group. The central hypothesis of this research is that microorganisms underlie the response of macroorganisms to a changing environment. This hypothesis is tested using mosquito populations of the avian malaria vector, Culex quinquefasciatus, across gradients in temperature and humidity that vary dramatically with elevation in Hawaii. The first aim clarifies the landscape-scale Cx. quinquefasciatus population dynamics by using metagenomic data to infer whether the mosquito holobiont covaries with elevation in a Hawaiian forest, a pattern consistent with local adaptation or acclimation of the holobiont to environmental regimes. In addition, genomic data and stable isotope tracking will be employed to resolve the connectivity of Cx. quinquefasciatus populations across this mountainous landscape to understand mosquito dispersal and its ramifications for the spread of microbial symbionts, including avian malaria parasites. The second aim manipulates the microbiome component of Cx. quinquefasciatus to understand its impact on adult mosquito phenotypes that influence the performance of the mosquito in its environment. Through controlled laboratory, microbiome transplantation, and common garden experiments, this work will clarify how the mosquito microbiome influences mosquito fitness in cool, high elevation environments where they currently cooccur with native Hawaiian honeycreepers. The third aim monitors the implementation of incompatible insect technique on Kauai, Hawaii to suppress Cx. quinquefasciatus populations in Hawaiian honeycreeper habitat. This effort will document the efficacy of this technique and inform mathematical models that will be used to hone future incompatible insect technique implementation in Hawaii and beyond. This project is jointly funded by the Divisions of Environmental Biology and Integrative Organismal Systems through the Partnership to Advance Conservation Science and Practice Program. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-11

Science education research shows that incorporating attention-grabbing concepts and experiences—phenomena—in science classes has the power to engage and inspire young learners. However, many elementary teachers, including those in small rural schools, may not have access to or the support to enact high-quality phenomenon-centered curriculum materials and resources in their science teaching practice. This project aims to address this problem of practice by designing, implementing, and investigating a professional learning approach that supports rural elementary teachers and administrators in incorporating local phenomena-driven science learning experiences in their classrooms. Participants include teacher-administrator triads from elementary schools in rural communities located in Maine, Montana, and Hawai’i. Through professional learning initiatives, the project will support third to fifth-grade teachers in incorporating locally and culturally significant, place-based phenomena into their science teaching. By tapping into the transformative potential of dedicated teachers utilizing a place-based phenomena-driven approach in science teaching, the project can provide insight into how rural educators use professional learning experiences to promote shifts in their science teaching practice in ways that prioritize students' communities and cultures and brings relevancy and authenticity to students’ science learning. This project is driven by the overarching goal of supporting teachers and their administrators in rural schools to prioritize students' cultures and communities in scientific sense-making through adaptation of phenomena. Investigators seek to better understand the processes and mechanisms by which adopting and internalizing this priority happens by a) exploring individual teacher change in pedagogical design capacity, and b) uncovering and describing each unique nexus of teacher, student, administrator, and researcher interactions that may facilitate change in rural schools. By exploring these goals in multiple rural communities across three geographically and culturally diverse states, the project team aims to understand the underlying common mechanisms of the adoption and adaptation of new pedagogical initiatives in rural spaces as well as the unique local and cultural contexts that contribute to diversified, place-specific implementation trajectories. The project team will use a comparative case study design to investigate how rural educators and their administrators use a suite of professional learning experiences to promote shifts towards phenomena-driven science teaching and learning in their schools. Professional learning experiences will build the pedagogical design capacity of rural third through fifth grade teachers to incorporate locally and culturally important, place-based phenomena into their science teaching through phenomenon adaptation to better prioritize students’ communities and cultures in the scientific sense-making processes. Triads consisting of two teachers and one administrator per school from 3-5 schools in each of three largely rural and culturally diverse states—Maine, Montana, and Hawaiʻi—will participate in a three-year professional learning system of support to promote growth in pedagogical design capacity for scientific sense-making and place-based phenomena adaptation. By examining the professional learning system as it unfolds, researchers will identify patterns in commonalities and differences across the three geographically and culturally diverse rural states to elicit findings and implications that may be applicable in a broad range of rural contexts. The Discovery Research preK-12 program (DRK-12) seeks to significantly enhance the learning and teaching of science, technology, engineering and mathematics (STEM) by preK-12 students and teachers, through research and development of innovative resources, models and tools. Projects in the DRK-12 program build on fundamental research in STEM education and prior research and development efforts that provide theoretical and empirical justification for proposed projects. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-11

The transition to sustainable energy storage is crucial for reducing dependence on fossil fuels and achieving decarbonization goals. Lithium-ion batteries play a pivotal role in this effort, powering a wide range of applications from portable electronics to electric vehicles. The surge in battery demand requires enhancements in energy storage performance and safety features beyond the current capabilities of lithium-ion batteries. Notably, thermal runaway, a critical safety issue where the battery overheats uncontrollably, has been encountered in several incidents involving mobile phones and electric vehicles. This issue, along with the growing need for higher charging rates and greater energy density, underscores the challenges of battery degradation. This project aims to enhance our understanding of the degradation mechanisms associated with the thermal properties of lithium-ion batteries. This fellowship will provide the PI with a unique opportunity for training, research, and establishing a sustainable partnership with collaborators at the University of California, Berkeley (UCB) and Lawrence Berkeley National Laboratory (LBNL). Advanced local thermal characterizations achieved through this project will provide valuable insights, contributing to the development of higher-capacity, more durable, and safer lithium-ion batteries. This Research Infrastructure Improvement EPSCoR Research Fellows project will provide a fellowship to an Associate Professor and training for a graduate student at the University of Hawaii at Manoa. Extensive research into lithium-ion batteries has been conducted to enhance battery performance, such as specific energy, power, and cycle life. However, local thermal properties, which critically influence electrochemical reactions and battery integrity, have received considerably less attention. This fellowship project will enable local thermal property measurement of battery electrodes using custom-designed scanning thermal probes. These probes will be manufactured at Marvell Nanofabrication Lab at UCB. In addition, through comprehensive assessments of electrochemical behaviors and crystal structures, this project will bridge a critical knowledge gap in degradation mechanisms of lithium-ion batteries by correlating local thermal properties with the physical and chemical processes. The experience gained through this project will transform the PI’s career by providing formal training on batteries, granting access to the state-of-the-art facilities, and ultimately opening new research directions in batteries. Further, this fellowship will deepen the existing collaboration and initiate new ones with researchers at UCB and LBNL. Outcomes from this fellowship include generating course materials, joint journal papers, and competitive collaborative proposals. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-11

This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). The devastating impacts of global warming and ocean acidification (OA) on rocky intertidal ecosystems are expected to increase as the oceans continue to warm and acidify. Further, loss of critical foundation species as a result of anthropogenic stressors lead to changes in local conditions that alter ecosystem functioning. While data exist on the physiological response of individual organisms to OA and warming in rocky systems, far less research has been conducted on community and ecosystem-scale metabolic responses. The proposed work provides a critical step in understanding how altered environmental conditions affect ecosystem functioning in rocky intertidal systems through the combination of controlled laboratory studies, field experiments, and a synthetic modeling approach integrating experimental results with pre-existing time-series data. The proposed work is focused on the overarching question: How does shifting environmental variability and loss of foundation species interact to affect ecosystem functioning in rocky intertidal communities? The PI is integrating research with ecological and quantitative educational opportunities including classroom and hands-on training in lab/field methods in marine ecology, and data science and coding bootcamps for undergraduate students. Importantly, these opportunities financially and educationally support traditionally underrepresented students at one of the largest minority-serving institutions in the country. This project provides support for intensive mentoring and training for 35 undergraduate students (25 in data science and 10 in field/lab science, all paid), 2-3 masters students, and hands-on marine ecology opportunities in the classroom (~125 students). In addition to formal education, the PI is collaborating with an artist-in-residence to communicate science to the broader public through interactive and immersive art installations in Los Angeles. Because rocky intertidal systems provide important ecosystem services including food production, coastal protection, and tourism, it is critical to understand how warming (both air and ocean), acidification, and altered community states affect reef-scale ecosystem metabolism. While information exists on responses of a variety of individual intertidal taxa to temperature stress, ocean acidification, and habitat loss, there is notably less on the response of ecosystem metabolism (e.g. NEP and NEC) to these stressors. This proposed work is focused on a series of conceptual knowledge gaps and tests mechanisms through which different warming regimes, lowered pH, and community disturbance lead to altered community metabolism and ultimately affect ecosystem function. Specifically, this study: 1) Describes community thermal performance curves of multiple ecosystem functions under differing pH conditions in experimental mesocosms, 2) characterizes drivers of ecosystem functioning (e.g. Net Ecosystem Production [NEP] and Net Ecosystem Calcification [NEC]) in situ using natural changes in environmental variability before and after a disturbance, and 3) integrates 16 years of publicly available community composition and environmental time-series data with lab and field data to hindcast ecosystem metabolic rates and predict how ecosystem metabolism may change in the future. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Peer-to-peer collaboration plays a vital and multifaceted role for PhD students: it helps students acquire new research skills and improve their publication records; it creates networks that provide professional support; and it helps students develop many of the key workplace skills for jobs both inside and outside of academia. Opportunities for building such research communities are severely limited or even nonexistent at small, geographically isolated institutions, where research groups are too small and specialized to lead to such collaborations, and where distance and geography limit contact with outside research groups. This National Science Foundations Innovations of Graduate Education (IGE) award to the University of Hawai’i at Mānoa will pilot and investigate an innovative model for using designed research communities to overcome some of the professional challenges faced by mathematics PhD students at geographically isolated institutions. The core idea is to form research communities for mathematics doctoral students at geographically isolated institutions via a semester-long mentored research experience and follow-up activities. This project will pilot the formation of three research communities over the course of the grant, each combining several students from the University of Hawai’i Mānoa Mathematics Ph.D. program with visiting students from other institutions. To build a lasting community, the interactions will be multidimensional: the centerpiece will be an intensive, collaborative research project, but this will be buttressed by professional development related to teaching and outreach. This project will investigate the extent to which these designed research communities can provide some of the known benefits of peer-to-peer collaboration. Specifically, the project will measure the effect of this intervention on short-term benefits (e.g., feelings of belonging, motivation) and long-term benefits (e.g., persistence, job placement rate). This model has the potential to lead to many innovative possibilities for graduate education at isolated locations. The Innovations in Graduate Education (IGE) program is focused on research in graduate education. The goals of IGE are to study, pilot, test and validate innovative approaches to graduate education and to generate the knowledge required to move these approaches into the broader community. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

An unprecedented opportunity to advance understanding of the biological rules that govern the diversity and dynamics of life now exists thanks to the large quantity and variety of data that are becoming increasingly available. This goal of understanding biodiversity dynamics is enabled at a critical moment when human systems are disrupting those very dynamics. However, the scientific and computational tools needed to derive understanding from data are still missing. Such tools need to be accessible to a broad community of users, thereby catalyzing involvement and innovation. This project will (1) build a computational model for multiple aspects of biodiversity-species abundance, genetic, functional, and phylogenetic; (2) use and refine this model by testing major hypotheses about the generation and maintenance of biodiversity in three exemplar systems; (3) make the model accessible to the scientific community by building an open-source platform to prepare diverse data sources and run the model; and (4) create pedagogically effective courses and workshops to enable students, researchers, and stakeholders from many backgrounds to understand biodiversity theory and the data science tools needed to test those theories with data. The Rules of Life Engine (RoLE) model will be a mechanistic, simulation-based hypothesis-testing and data synthesis framework enabling scientists with multi-dimensional biodiversity data to generate and test hypotheses about the processes driving biodiversity patterns. The RoLE model will apply new techniques in machine learning to fit models to high dimensional, cross-scale data. The model will simulate eco-evolutionary community assembly building from individual-based ecological and genetic neutral models with added non-neutral, trait-based competition and environmental filtering. New species and traits will arise through long time scale evolution in the meta-community and rapid evolution in the local community. Population genetics and species abundances in the local community will be modeled through birth, death, immigration, and mutation. The project research team will refine and illustrate the use of the RoLE model by testing four hypothesized rules of life across three bio-geographic systems for which multi-scale biodiversity data are now available. The hypotheses address the relative roles of immigration versus speciation in community assembly, how species interactions influence diversity, how different assembly histories determine the strength of species interactions, and whether/how systems come to equilibrium. The project leaders have established a network of 14 collaborators, including the National Ecological Observatory Network, who will use the RoLE model in their diverse systems and propagate wider adoption. In order to further reduce barriers to use, the RoLE model framework will be made available as open source software, including an R language Shiny App interface with standardized metadata outputs to promote reproducibility and sharing. The insights gained from the RoLE model are of direct relevance to conservation, e.g., whether or not communities are assembled primarily by speciation or immigration strongly determines their response to anthropogenic pressures and optimal conservation management. To encourage participation in quantitative biodiversity research, the project leaders will develop a massively open online course through the Santa Fe Institute?s Complexity Explorer program using the RoLE model as an interactive teaching tool. In conjunction with Data Carpentry and Software Carpentry, the research team will also provide an in-person data science training workshop. Results from the RoLE project can be found at https://role-model.github.io. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

There are two main challenges when it comes to software efficiency and scalability on modern systems: taking advantage of multiple processors to get enough data to processors and keeping them occupied with work throughout the computation. The first challenge is known as parallelism, and the second one is known as I/O-efficiency or cache-efficiency. The goal of this project is to understand the power and limitations of various existing models of parallel and I/O-efficient computation and to apply the gained knowledge to discover new techniques for designing data structures that are both parallel and cache-efficient. Data structures are essential to simplifying software development and contributing to code reuse. This project will produce a number of parallel cache-efficient data structures, hence contributing to the overall goal of simplifying software design and increasing code reuse on modern high-performance systems. The project will also offer paid research training opportunities for undergraduate and graduate students. To achieve this goal, the project will proceed along four main thrusts of investigation. (1) Fractional cascading is a classical data structuring technique and a multi-way distribution framework is a fundamental technique for designing I/O-efficient algorithms. The project will incorporate fractional cascading into the multi-way distribution framework, combining parallelism with I/O efficiency. (2) (Partial) persistence in a search tree allows multiple queries to be performed independently of each other despite the updates modifying the search tree between the queries. The project will develop a parallel construction of (partially) persistent B-trees, hence providing a simple way of achieving query parallelization on dynamic B-trees. (3) Amortized analysis is a powerful data structuring technique. The project will extend this technique to the parallel computational models that support I/O efficiency. (4) Finally, the project will prove a number of lower bounds for data structures in parallel and I/O-efficient models of computation, contributing to our collective understanding of the power and limitations of these models. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-10

Artificial intelligence (AI) is increasingly used in cyber-physical systems (CPSs) that directly sense and interact with the environment to help them react to large, real-time data that comes in a variety of formats. However, the security and safety of AI models, and the privacy of the data used to build them, can be attacked. There is some research on AI model safety in other domains, but in CPSs the nature and scale of attacks on AI models may change because of their connection to the wider environment. This project will support planning a large-scale proposal to increase the security and privacy of AI-enabled CPSs. This will involve developing foundational knowledge and systematic tools to understand and defend against the unique risks of AI-enabled CPSs. It will also involve creating an engineering and education community capable of using that knowledge and those tools to build safer, more secure systems that help society better-interact with the world. The planning project is led by an interdisciplinary team with expertise in AI, machine learning, and CPS security. To better understand the challenges across a variety of CPS contexts, and provide resources for both expertise and deployment, the research team will collaborate with experts from a number of CPS domains, including space science, healthcare, transportation, and water resource management. The team will also work with stakeholders in education, business, the wider academic community, and government to inform questions and activities related to the project's education and workforce development goals. Planning activities include a series of biweekly seminars, quarterly newsletters, and symposia; these will support frequent communication and coordination around developing both the proposal itself and team required to execute it. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

In recent decades, a concerted movement to document and revitalize endangered languages through educational efforts have saved such languages from extinction. However, progress has not kept up with endangered language community needs in modern society. Endangered languages often lack words for some modern science and technology concepts, and there is a growing need for educational materials in these languages. With recent advances in natural language processing, low-resource languages and endangered languages have been largely neglected. This project develops new user-facing language technologies for an endangered language, starting with machine translation and language models, which in collaboration with the language communities aids in preservation and revitalization. This project first collects, cleans, and consolidates texts and dictionaries from online sources, along with data from a digital repository of language data housed at the University of Hawai'i. Next, machine translation systems are trained on available data augmented with techniques such as backtranslation and methods from computational etymology and are applied to translate text materials both into and out of the endangered language. Due to differences in orthography, methods to develop a consistent orthography are also investigated. Finally, language models are developed to enable future computational study of low-resource and endangered languages. This project not only positively benefits the community of endangered language speakers under study, but also serves as a case study for applying and developing language technologies to preserve and revitalize other low-resource and endangered languages around the world. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This project involves the creation of artificial intelligence (AI) models that make predictions about health events like substance use and stress-related blood pressure spikes using data from smartwatches like FitBit, Apple Watch, and other wearables. The innovation of this project comes from training personalized models that learn exclusively from each person’s wearable data. Recent advances in AI methods allow us to train these models to understand each user’s individual biosignals patterns related to heart rate, movement, and other signal recordings using large amounts of unlabeled data that are recorded when the user wears the device. This should, in theory, enable us to refine these models to learn to predict relatively complex recurring health outcomes like stress and blood pressure spikes using much fewer labeled examples than what would have previously been necessary. We will test this paradigm in two user studies related to stress-related hypertension and substance use detection. The status quo for machine learning consists of the development of a one-size-fits-all model which is usually trained on data coming from one group and tested on data from another disjoint group. However, the advent of self-supervised learning makes it possible to learn from vast unlabeled multimodal data streams recorded from a single individual, allowing for a pretrained model which learns feature representations which are specific to the baseline temporal dynamics of a single entity’s data streams. This project seeks to understand how such personalized self-supervised learning on multimodal data streams can be used to overfit, in a positive manner, a machine learning model to the unique patterns of an individual’s sensor readings, thus enabling model personalization and prediction of traditionally difficult or subjective targets. To make these artificial intelligence (AI) innovations practically useful and because these personalized models still require on the order of tens of annotations to converge, we propose to develop novel human-computer interaction (HCI) techniques which are tightly integrated into the AI workflow to facilitate reliable and effective yet minimal annotations of the adverse health event of interest from the end user. We will evaluate this paradigm on two separate health conditions with differing data types and nuances: (1) substance use and craving measurements and (2) stress-related hypertension, each predicted using multimodal passively collected consumer wearable and smartphone data streams. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

This research team will study planet formation by characterizing the carbon monoxide (CO) gas in disks that surround new-born stars. This volatile gas may stick on grains and pebble-sized solids far away from the star within the disk, moving with them as they drift towards the star, where they may be released due to its heat. Using infrared spectroscopy to sense CO in the inner disk and millimeter images to sense CO in the outer disk, the team will probe, respectively, the planet-formation region and where most of the disk material exists as in a ‘reservoir’. Three graduate students will be trained in telescope observing and data modeling at the PhD level, and two undergraduate students will be involved in high level research. Calibrated datasets and open-source codes will be made publicly available. A new course on radio astronomy for undergraduate astronomy majors will be developed. There will be broader outreach to local middle and high schools through summer programs and campus visits, and to the community at large through public events. Recent observations and simulations suggest that CO chemistry is being impacted by dynamical and chemical processing. Patterns between the derived CO column densities in the terrestrial planet forming zone (e.g., < 5 au) and in the outer bulk gas reservoir probed at ALMA-wavelengths will be sought. The program will use data from world-class ground-based observatories: the Atacama Large Millimeter Array (ALMA) in Chile; and the Keck observatory and the Infrared Telescope Facility in Hawaii. The collaboration leverages the strengths of the three participating institutions to provide the most complete picture to date of the volatile content of protoplanetary disks. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

In recent years, the Alpha Magnetic Spectrometer (AMS-02) on the International Space Station has reported detecting several antideuteron and antihelium nucleus candidates. The existence of cosmic antideuterons in the reported energy range might be the first sign of dark matter annihilation or decay, or of physics beyond the standard model of particle physics. However, it could be explained by astrophysical background effects. This project will profoundly advance the understanding of cosmic antinuclei by analyzing an extended AMS-02 data set with state-of-the-art machine-learning analysis techniques and complementing their interpretation with data from the fixed-target SPS Heavy Ion and Neutrino Experiment (NA61/SHINE) at the Super Proton Synchrotron (SPS) at the European Laboratory for Particle Research (CERN). The group will provide a hands-on computer programming outreach program for underrepresented high school students from economically disadvantaged backgrounds in cooperation with the University of Hawaiʻi at Mānoa's Office of Student Equity, Excellence, and Diversity. They are also developing strategies for increasing Science, Technology, Engineering, and Mathematics (STEM) education efforts for mature adults. The AMS-02 collaboration reported detecting several antideuteron and antihelium nucleus candidate events in approximately equal amounts in the energy region of a few GeV/n. However, no coherent theory exists that can explain a) the existence of any detectable antihelium flux in the Galaxy and b) that the number of antideuterons is comparable to the number of antihelium nuclei. AMS-02’s antideuteron candidates in the few-GeV/n region will be studied with new reconstruction and analysis methods, and systematic Galactic propagation uncertainties will be addressed by interpreting AMS-02’s nuclei measurements, and systematic uncertainties in the astrophysical antideuteron background production will be reduced with new and existing proton-proton collision data from NA61/SHINE in the energy range most relevant to cosmic rays. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

The origin and evolution of the Universe on the largest scales is one of the most profound questions in astrophysics today. A team of scientists at the University of Hawai'i will continue and substantially expand the Hawai‘i Supernova Flows survey. They will use than 3,000 new Type Ia supernovae to map the largest structures in the Universe to 300 Mpc, tripling the volume currently surveyed. The survey will enable them to put strong constrains on the expansion of the universe (H0) and the growth of large-scale structure over time. The results of this work will be made accessible to the public through videos, interactive models, and virtual reality. In addition, the team is committed to increasing education and engagement opportunities in Hawai’i by 1) enabling stronger connections to high school students via HI STAR, 2) connecting Maunakea telescopes to undergraduate courses at UH Hilo on Hawai i island, and 3) providing impactful internship opportunities for talented Hawai‘i undergraduates. The Hawai‘i Supernova Flows survey currently combines high-cadence optical light curves from ATLAS with near-infrared (NIR) light curves from UKIRT in the North. The proposed work will add ATLAS and LSST in the South for full-sky coverage. The primary goal of this proposal is to map the largest structures in the Universe to 300 Mpc, tripling the volume currently surveyed. This work will compliment and extend the Rubin Observatory’s Legacy Survey of Space and Time (LSST) by building a low-redshift sample where LSST photometric non-linearity or saturation is a factor. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

NSF Awards · FY 2024 · 2024-09

A scientific team is undertaking archaeological research to better understand how variation in patterns of household interaction, activities, social roles, and relationships within and between communities lead to the emergence of regionally-integrated socially complex societies with different developmental dynamics. The organizing principles of some complex societies have their roots in strongly developed social, economic, and/or other kinds of differences between households. Archaeology is ideally suited to provide information about the relative contributions of differences in household wealth, prestige, ritual or religious activities, and productive pursuits in shaping patterns of interaction and interdependence through the many centuries it may take for complex societies to emerge. Determining what kinds and degrees of differentiation combined to form ancient complex societies with particular developmental profiles clarifies the processes responsible for patterns of organization seen in modern societies. This research will contribute to fuller understandings of cross-cultural variability in early complex society development, by increasing the sample of well-studied examples that can be laid alongside cases that arose in multiple regions for detailed comparison of their social dynamics. Regional-scale settlement survey determines how large and populous one early historic community was, and if other settlements were drawn toward it to facilitate interaction of their inhabitants. Field mapping and excavation of domestic features and artifact assemblages elucidate aspects of its organization, and the organization of outlying settlements, as well as provide characterizations of any variation in standards of living, prestige, ritual and productive activities between the households that comprised them. The project fosters scholarly collaboration, and provides training for university students and cultural heritage authorities, including those from historically underrepresented groups. Analyses of data generated by the project appear in students' theses and dissertations, as well as inform cultural heritage conservation and mitigation policies. The project disseminates its findings to multiple stakeholders through established scientific channels and community outreach programs. Partnerships with visual artists and videographers document the project's process of fieldwork and laboratory analysis from which alternative forms of archaeological storytelling will be developed to further public engagement with open 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 2024 · 2024-09

The University of Hawai‘i at Mānoa (UHM) and University of Washington (UW) Materials Research Science and Engineering Center (MRSEC) partnership, Materials Research and Education Consortium (MRE-C), will engage researchers to foster key materials science breakthroughs in clean energy and sustainability necessary to solve the critical challenges facing geographically isolated island communities such as Hawaiʻi. These challenges include heavy reliance on imported fuels for electricity and transportation, resource and waste management, soil erosion, and ocean contamination exacerbated by climate change. This PREM aims to: (1) Enhance workforce development (2) boost research capacity in materials for clean energy and sustainability; and (3) integrate cultural knowledge and insights to materials education in alignment with UHM’s aspirations as a Hawaiian Place of Learning. MRE-C is uniquely positioned to significantly increase local participation in materials science and STEM careers due to the high Native Hawaiian population at UHM (16%) and in Hawaiʻi (21%) compared to U.S. mainland (0.2%). The introduction of new materials science classes will enrich the academic experience for STEM students, offering a wider array of course options and career pathways. The PREM K-12 education effort will have an enduring impact in schools, with the curricula use continuing beyond outreach periods, ensuring the sustained growth of the materials science and STEM pathway. This project is partially supported by co-funding from the Established Program to Stimulate Competitive Research (EPSCoR) and Sustainable Chemistry from the Office of Strategic Initiatives (OSI) in the Directorate for Mathematical and Physical Sciences (MPS). MRE-C creates a pathway to recruit, retain, and graduate cohorts of participants through activities anchored on the M.O.R.E approach (Mentoring, Outreach, Research and Education), training more than 60 undergraduate and graduate scientists and engineers ready for emerging material science and STEM workforce opportunities. MRE-C research is organized into three unique, interrelated thrusts: 1) Advanced Nanomaterials for Energy Conversion and Storage pushes the boundaries of new material structure and property information consequent to nanoscaling and doping of hard materials and chalcogenide perovskites that can lead to advances in energy technologies, including solar and hydrogen fuel cell-based systems, accelerating Hawai‘i's transformation to clean energy; 2) Sustainable Materials for Island Communities addresses the challenges of sustainable resource management in island communities by developing new hybrid composites, biodegradable materials to improve resource utilization and ensure ecological, and economic sustainability; 3) Materials Acceleration via Synergistic AI-Driven Automation of Experiments and Simulations develops a modular materials acceleration platform infrastructure that applies to structured materials built from nanocrystal building blocks to provide solutions to sustainability challenges. UHM’s expertise in materials syntheses and unique capabilities in X-ray diffraction, hydrogen sorption, and thin films deposition will be complemented by UW resources through virtual and in-person exchanges. UW will advance UHM research culture and capacity through transfer of expertise and pertinent resources for automation of research processes and large data sets, syntheses of nanomaterials and biomaterials, and integration of advanced computations synergistic with experimental discovery. The partnership will develop materials courses and K-12 workshops incorporating local Hawaiian cultural perspectives to increase the place-based value of curriculum to both institutions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.