Grant List
Represents Grant table in the DB
GET /v1/grants?page%5Bnumber%5D=3&sort=end_date
{ "links": { "first": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1&sort=end_date", "last": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=1392&sort=end_date", "next": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=4&sort=end_date", "prev": "https://cic-apps.datascience.columbia.edu/v1/grants?page%5Bnumber%5D=2&sort=end_date" }, "data": [ { "type": "Grant", "id": "15105", "attributes": { "award_id": "2325532", "title": "SBIR Phase II: A Novel Host-Directed Broad-Spectrum Antiviral and Efficient Immunomodulatory Agent Against Coronaviruses: Lead Optimization Studies", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Technology, Innovation and Partnerships (TIP)", "SBIR Phase II" ], "program_reference_codes": [], "program_officials": [ { "id": 773, "first_name": "Erik", "last_name": "Pierstorff", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-09-01", "end_date": null, "award_amount": 1000000, "principal_investigator": { "id": 31651, "first_name": "Mohammad", "last_name": "Noshi", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 356, "ror": "", "name": "Akanocure Pharmaceuticals, Inc.", "address": "", "city": "", "state": "IN", "zip": "", "country": "United States", "approved": true }, "abstract": "The broader impact of this Small Business Innovation Research (SBIR) Phase II project stems from the development of a virus agnostic drug that can control the current coronavirus pandemic and potentially future pandemics caused by yet unknown viruses. Since 2020, research has been chasing COVID-19 and its variants by reformulating vaccines and developing more antibodies and antivirals, but the virus has always been ahead, mutating so fast to make those approaches obsolete. Because COVID-19 is not going away, and because a dysregulated (toxic) immune response is not unique to COVID-19, and because viral threats will not stop at COVID-19, a virus and variant agnostic drug that can stop the virus from multiplying, can fix the toxic immune response, is easy to administer in an outpatient or pandemic setting (oral), and can be given early or late in the infection cycle is imperative to get ahead of viral threats. In addition to the positive effect on pandemic preparedness and decreasing the pressure on healthcare systems, such drug can positively impact the economy by preventing the devastating health effects that COVID-19 has on the cardiovascular (heart) and nervous systems, which have led to disability claims sharply rising among the working age group.<br/><br/>The proposed project focuses on the lead optimization of a candidate molecule for oral administration against coronaviruses. SARS-CoV-2 infections cause hyperinflammation and autoimmunity leading to multi-organ damage even with mild infections. The damage is cumulative and repeat infections increase the risk of long COVID. These clinical manifestations are due to persistent/chronic infections and dysregulated immune responses. An ideal treatment would not only suppress viral replication but would also restore the immune system homeostasis and healthy immune response. In Phase I, a molecule was designed, synthesized, and shown to be an efficient immunomodulatory and broad-spectrum antiviral. This molecule targets the host rather than the virus which decreases the chances of resistance and makes it virus/variant agnostic, unlike vaccines and direct-acting antivirals. In Phase II, the technical objectives focus on design, synthesis, and testing of analogs with improved drug-like properties for oral administration. Those analogs will be evaluated against several SARS-CoV-2 variants in-vitro, subjected to in-vitro ADME studies, and assessed for their effect on the production of immune mediators in virus-infected cells. The analog with the best profile will advance to in-vivo studies to test its pharmacokinetic and toxicological properties in mice, as well as its efficacy and immune modulations activity in virus-infected animal rodents.<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "12801", "attributes": { "award_id": "2302814", "title": "Collaborative Research: Adaptable Game-based, Interactive Learning Environments for STEM Education (AGILE STEM)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "ECR-EDU Core Research" ], "program_reference_codes": [], "program_officials": [ { "id": 1414, "first_name": "Soo-Siang", "last_name": "Lim", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2023-09-15", "end_date": null, "award_amount": 350000, "principal_investigator": { "id": 28720, "first_name": "Conrad", "last_name": "Tucker", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 243, "ror": "", "name": "Carnegie-Mellon University", "address": "", "city": "", "state": "PA", "zip": "", "country": "United States", "approved": true }, "abstract": "Learners of all ages are expected to be prepared to interact with emerging and technology-driven work environments. In addition, the growing reliance on online learning and its unprecedented and unexpected acceleration due to the COVID-19 pandemic are expected to change the education landscape forever. Thus, there is a need to grow the development of digital platforms for teaching and learning. Emerging technologies such as machine learning and high fidelity simulated environments have the potential to create customized and adaptable learning environments to support STEM learning outcomes. This project serves the national interest by advancing the knowledge about designing and creating adaptable game-based, interactive learning environments for STEM. The inclusion of underrepresented minority and female learners in the design stages of these learning environments, their portability, as well as the capability of these environments to be customized and adaptive have the potential to enhance education equality, engagement, and learning outcomes, and broaden their usability to several STEM domains. Moreover, the narratives and simulation models are inspired by real-world systems. Therefore, the learning environments are expected to enhance the learner’s understanding of complex system concepts that are challenging to understand using traditional teaching approaches and will help build the much-needed skills for the U.S. future STEM workforce. The proposed emerging technologies do not necessarily need access to specialized equipment, which eliminates barriers to scalability and border implementation and use. <br/><br/>The primary goals of this project are to automatically customize and adapt three-dimensional (3D) simulated game-based learning environments to improve engagement, and provide a deeper understanding of their design, development, and deployment, impact on learning and self-regulated learning (SRL) skills, and knowledge transferability from the learning environments to real-life applications. The project addresses the lack of scientific evidence and/or work in the following thrust areas: 1) the potential of reducing the barriers to content generation of 3D simulated game-based learning environments using emerging and advanced machine-learning methods; 2) creating customized content and adaptive 3D simulated game-based learning environments that improve and maintain learners motivation and engagement, enhance learning via instructional assistive content scaffolding, and increase knowledge transferability from game to real-life applications; 3) assessing the effectiveness of the learning environments for all learner groups in online and residential settings; and 4) exploring how learner decision-making and behavior data in the simulated game-based learning environments, and eye-tracking, facial expressions, bio-signals, and usage data, enhance knowledge about the relationships between decision-making/usage and SRL skills development.<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "13057", "attributes": { "award_id": "2150405", "title": "REU Site: Undergraduate Research in Basic and Applied Science of Psychology", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "RSCH EXPER FOR UNDERGRAD SITES" ], "program_reference_codes": [], "program_officials": [ { "id": 1351, "first_name": "Josie Welkom", "last_name": "Miranda", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-06-01", "end_date": null, "award_amount": 347895, "principal_investigator": null, "other_investigators": [ { "id": 29062, "first_name": "Charles A", "last_name": "Scherbaum", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 2223, "ror": "", "name": "CUNY Baruch College", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "This project is funded from the Research Experiences for Undergraduates (REU) Sites program in the Directorate for Social, Behavioral and Economic Sciences (SBE). It has both scientific and societal benefits in addition to integrating research and education. The REU site at Baruch College offers advanced research training in psychological science to undergraduate students who attend Baruch College, Colleges within the City University of New York, or other educational institutions in the New York metropolitan area. Baruch College and CUNY in general boast a diverse student body. Although the recruitment is open to any NSF eligible undergraduate students, this program is designed to increase the representation of minority, low-income, first-generation college students, and disabled students in scientific psychology. Specifically, the program plans to (a) identify early promising minority, disabled, and economically disadvantaged students in the New York metropolitan area, (b) prepare REU students for advanced graduate training in psychology and ultimately for careers in academic settings, (c) develop a pipeline to provide a pool of talented and diverse undergraduate students to become the research scientists of the future, and (d) increase psychological scientists exposure to cultural and minority issues in psychological research. <br/><br/>REU Students in the program conduct independent research under the supervision of their respective REU faculty member in one of the four areas of psychology (i.e., clinical, developmental, industrial/organizational, and social). Each student focuses on planning and executing studies with the intention of presenting papers at professional conferences and submitting manuscripts to peer-reviewed journals. Specifically, REU students develop research questions and hypotheses that are grounded in the literature. In order to answer these newly developed research questions and hypotheses, REU students design research protocols and plan data collection. REU students learn via hands-on experience the value of statistical analysis, use of statistical software to draw inferences about the data, and presentation skills to disseminate the findings gained in their research. Alongside with the conduct of their research projects, REU students complete a series of structured activities aimed at preparing them to apply to graduate school. These activities, such as attending professional development seminars and workshops, participating at colloquium in the field of psychology, listening to invited guest speakers from graduate program admission officers, are coordinated by the Baruch College REU program.<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "13313", "attributes": { "award_id": "2143849", "title": "CAREER: The Spatiotemporal Dynamics of the C. Elegans Intestinal Gene Regulatory Network", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)", "Genetic Mechanisms" ], "program_reference_codes": [], "program_officials": [ { "id": 3491, "first_name": "Stephen", "last_name": "DiFazio", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-03-01", "end_date": null, "award_amount": 1234971, "principal_investigator": { "id": 29392, "first_name": "Erin", "last_name": "Osborne Nishimura", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 323, "ror": "https://ror.org/03k1gpj17", "name": "Colorado State University", "address": "", "city": "", "state": "CO", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2)<br/><br/>Gene regulatory networks direct development, cell identity, and homeostasis. How some gene regulatory networks change from directing organ development in embryonic stages to supporting organ functions in juvenile and adult stages has not been sufficiently explored. Furthermore, the microbiome's influence on the biology of organ systems is just beginning to be appreciated. This project aims to capitalize on the 20-cell Caenorhabditis elegans intestine as a model organ system to determine how intrinsic (gene regulatory network) and extrinsic (microbial) factors influence transcription over developmental time. This project will also support an outreach initiative to introduce community college students to diverse STEM fields, support them through the transfer stage, and assist them in gaining research opportunities in Computational Biology. American Rescue Plan funding of this project supports this investigator at a critical stage in her career.<br/><br/>The gene regulatory network that directs organogenesis of the C. elegans intestine is a classic model system. It culminates in ELT-2 (Erythroid Like Transcription factor), a highly conserved regulator. Using genomics approaches, the proposed work will test whether ELT-2 influences changing gene expression through autonomous mechanisms or in combination with dynamic partners. Specifically, the project will explore the relationship between ELT-2 and its homolog ELT-7. Intestinal microbes greatly impact intestinal biology, yet C. elegans are typically studied in isolation from natural microorganisms. A newly curated C. elegans microbiome resource (CeMbio) affords new opportunities to determine how microbes influence intestinal transcription. By investigating this at the single-cell level, the proposed work will determine how cell identity and the microbiome intersect. Overall, this project will illuminate how organ systems transcriptionally orchestrate biological processes with single-cell precision, over developmental time, and in response to the microbiome.<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "13568", "attributes": { "award_id": "2144751", "title": "CAREER: Efficient, Dynamic, Robust, and On-Device Continual Deep Learning with Non-Volatile Memory based In-Memory Computing System", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Computer and Information Science and Engineering (CISE)", "Software & Hardware Foundation" ], "program_reference_codes": [], "program_officials": [ { "id": 977, "first_name": "Sankar", "last_name": "Basu", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-01-15", "end_date": null, "award_amount": 500000, "principal_investigator": { "id": 8714, "first_name": "Deliang", "last_name": "Fan", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 173, "ror": "", "name": "The University of Central Florida Board of Trustees", "address": "", "city": "", "state": "FL", "zip": "", "country": "United States", "approved": true } ] }, "other_investigators": [], "awardee_organization": { "id": 147, "ror": "https://ror.org/03efmqc40", "name": "Arizona State University", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2).<br/><br/>Over past decades, there have existed grand challenges in developing high performance and energy-efficient computing solutions for big-data processing. Meanwhile, owing to the boom in artificial intelligence (AI), especially Deep Neural Networks (DNNs), such big-data processing requires efficient, intelligent, fast, dynamic, robust, and on-device adaptive cognitive computing. However, those requirements are not sufficiently satisfied by existing computing solutions due to the well-known power wall in silicon-based semiconductor devices, the memory wall in traditional Von-Neuman computing architectures, and computation-/memory-intensive DNN computing algorithms. This project aims to foster a systematic breakthrough in developing AI-in-Memory computing systems, through collaboratively developing ahybrid in-memory computing (IMC) hardware platform integrating the benefits of emerging non-volatile resistive memory (RRAM) and Static Random Access Memory (SRAM) technologies, as well as incorporating IMC-aware deep-learning algorithm innovations. The overarching goal of this project is to design, implement, and experimentally validate a new hybrid in-memory computing system that is collaboratively optimized for energy efficiency, inference accuracy, spatiotemporal dynamics, robustness, and on-device learning, which will greatly advance AI-based big-data processing fields such as computer vision, autonomous driving, robotics, etc. The research will also be extended into an educational platform, providing a user-friendly learning framework, and will serve the educational objectives for K-12 students, undergraduate, graduate, and under-represented students.<br/><br/>This project will advance knowledge and produce scientific principles and tools for a new paradigm of AI-in-Memory computing featuring significant improvements in energy efficiency, speed, dynamics, robustness, and on-device learning capability. This cross-layer project spans from device, circuit, and architecture to DNN algorithm exploration. First, a hybrid RRAM-SRAM based in-memory computing chip will be designed, optimized, and fabricated. Second, based on this new computing platform, the on-device spatiotemporal dynamic neural network structure will be developed to provide an enhanced run-time computing profile (latency, resource allocation, working load, power budget, etc.), as well as improve the robustness of the system against hardware intrinsic and adversarial noise injection. Then, efficient on-device learning methodologies with the developed computing platform will be investigated. In the last thrust, an end-to-end DNN training, optimization, mapping, and evaluation CAD tool will be developed that integrates the developed hardware platform and algorithm innovations, for optimizing the software and hardware co-designs to achieve the user-defined multi-objectives in latency, energy efficiency, dynamics, accuracy, robustness, on-device adaption, etc.<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "12545", "attributes": { "award_id": "2225445", "title": "GEM: Suprathermal and Energetic Ion Heating by Electromagnetic Ion Cyclotron Waves and Magnetosonic Waves in the Inner Magnetosphere", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)", "MAGNETOSPHERIC PHYSICS" ], "program_reference_codes": [], "program_officials": [], "start_date": "2023-01-01", "end_date": null, "award_amount": 0, "principal_investigator": { "id": 28474, "first_name": "Wen", "last_name": "Li", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 168, "ror": "", "name": "Trustees of Boston University", "address": "", "city": "", "state": "MA", "zip": "", "country": "United States", "approved": true }, "abstract": "The focus of this project is to study the ion heating by plasma waves in the Earth's magnetosphere. The electromagnetic ion cyclotron (EMIC) and magnetosonic waves are plasma waves generated by ring current ions in the magnetosphere. These plasma waves could scatter and heat the ions, transferring energy from the ring current to other regions or populations. This project investigates the ion heating process by combining simulations with Van Allen Probes observations. The modeling efforts will reveal the source of ions from wave-particle interaction. Understanding the ion dynamics will help future space missions traveling through the magnetosphere and implementation of the ion-wave interaction effects in space weather prediction. This project will help quantify the ion flux variations in the inner magnetosphere, where many satellites are operating to provide human's essential needs of communication, navigation, and security. This project supports two early-career scientists, a female faculty and a graduate student at Boston University. The Center for Space Physics at Boston University provides an ideal environment for collaboration in space science research, student training and teaching, community engagement, and outreach activities.This project aims to determine the conditions and consequences of resonant ion heating by EMIC and magnetosonic waves through comprehensive satellite observations and numerical modeling. Firstly, a survey of ion heating events will be performed using the Van Allen Probes data. The ion heating events will be categorized by different wave properties and background plasma parameters, to reveal the critical conditions that cause evident ion heating features in the inner magnetosphere. Secondly, a series of quasilinear simulations of the ion heating and scattering effects will be performed during the EMIC and magnetosonic wave events. The simulation inputs are provided by the wave properties and background plasma parameters from the survey to demonstrate the efficiency and energies of ion heating. Thirdly, since the amplitudes of EMIC and magnetosonic waves could be large so that they can break the quasi-linear approximation, the interaction between ions and large amplitude waves will be evaluated using a test particle code. A series of test particle simulations will be performed through varying wave amplitudes to find the threshold beyond which nonlinear effects become important. The ion phase trapping and bunching effects by strong EMIC and magnetosonic waves will also be evaluated to quantify their contribution to ion acceleration at different energies.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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "15106", "attributes": { "award_id": "2412446", "title": "PIPP Phase II: Environmental Surveillance for Assessing Pathogen Emergence (ESCAPE)", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Biological Sciences (BIO)", "PIPP-Pandemic Prevention" ], "program_reference_codes": [], "program_officials": [ { "id": 2558, "first_name": "Joanna", "last_name": "Shisler", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2024-09-01", "end_date": null, "award_amount": 17999995, "principal_investigator": { "id": 25433, "first_name": "Scott", "last_name": "Berry", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 5152, "first_name": "Matthew L", "last_name": "Scotch", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [ { "id": 147, "ror": "https://ror.org/03efmqc40", "name": "Arizona State University", "address": "", "city": "", "state": "AZ", "zip": "", "country": "United States", "approved": true } ] }, { "id": 25432, "first_name": "James W", "last_name": "Keck", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, { "id": 31652, "first_name": "Sarah H", "last_name": "Olson", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 178, "ror": "", "name": "University of Kentucky Research Foundation", "address": "", "city": "", "state": "KY", "zip": "", "country": "United States", "approved": true }, "abstract": "The goal of the Pandemic Environmental Surveillance Center for Assessing Pathogen Emergence (Pandemic ESCAPE) is the timely detection of emergent pathogens across a variety of settings through cost-effective and easy-to-implement environmental surveillance (ES). ES uses environmental samples, to discover and monitor pathogens. Pandemic ESCAPE will advance ES technology, data interpretation, and adoption to promote its widespread deployment across the United States. Pandemic ESCAPE will adopt multiple strategies to tackle this challenge. These include research and engineering to design portable and easy-to-use ES devices, development of new methods for ES and genome sequencing, modeling of disease transmission using ES data, co-production of ES knowledge through community partnerships and participatory science, and engagement through public outreach and education activities. The Center will work closely with public health experts and the private sector to ensure that its solutions are practical and can be easily integrated into existing infrastructure. <br/><br/>The long-term strategic goals of Pandemic ESCAPE are to 1) Create simplified tools to advance environmental surveillance (ES) pathogen monitoring and prediction capabilities; 2) Train the next generation of scientists in ES, emphasizing participation of underrepresented groups; 3) Accelerate the adoption of ES as a pandemic prevention tool for everyone; 4) Communicate ES data effectively, efficiently, and inclusively to support knowledge to action; 5) Empower communities to build local ES capacity; 6) Advocate for pathogen detection and response strategies that include ES. Through collaboration with partners in low resource communities, the Pandemic ESCAPE team will develop the necessary tools to grow an extensive ES network that can be used to monitor for pathogens. Achieving these long-term goals will have a transformative impact on how communities identify, monitor, and mitigate the impact of emerging pathogens.<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "13569", "attributes": { "award_id": "2134864", "title": "Terrestrial Organics since The Oligocene (TOTO): The Rains Down in Africa", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)", "Marine Geology and Geophysics" ], "program_reference_codes": [], "program_officials": [ { "id": 29707, "first_name": "Joseph", "last_name": "Carlin", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2022-01-15", "end_date": null, "award_amount": 613617, "principal_investigator": { "id": 6732, "first_name": "Kevin", "last_name": "Uno", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 29727, "first_name": "Rachel L", "last_name": "Lupien", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 196, "ror": "https://ror.org/00hj8s172", "name": "Columbia University", "address": "", "city": "", "state": "NY", "zip": "", "country": "United States", "approved": true }, "abstract": "Terrestrial Organics since The Oligocene (TOTO): The Rains Down in Africa<br/><br/>Today, nearly 100 million people depend on the lands in the Sahel region, which is highly sensitive to flooding, droughts, and wildfires, putting food and other resources at risk. Africa is also rich in human evolutionary history, including early human fossil sites, evidence for multiple dispersals out of Africa, and the earliest stone tool innovations. Despite the region’s importance for understanding climate change and human evolution, there is a lack of understanding of tropical Africa over long intervals. To that end, the investigators will generate new West African records of rain, vegetation, and fire over the last 25 million years to study changes in the Sahel ecosystem, which runs east-west across Africa south of the Sahara desert, and to quantify the effects of natural cycles in Earth’s orbit and long-term changes in global and regional conditions on ecosystem change and human evolution. The investigators will convene a new African Climate Conference to facilitate knowledge sharing, networking events, and laboratory tours at Lamont to directly combat the long history of the exclusion of African researchers in Western science by forming deep, lasting collaborations.<br/><br/>The Tropics comprise half of Earth’s surface, serve as the global hydrological pump, and contain the world’s largest potential source of methane, yet there is a dearth of data and understanding of tropical climate over the Cenozoic. Tropical Africa, in particular, has been historically under-studied, despite its importance for understanding human evolution, tropical hydroclimate, and terrestrial ecosystem responses to climate change. Projections of future climate scenarios require quantification of past climatic responses to orbital forcings and boundary conditions (i.e., regional albedo, ice volume, global temperature). The investigators will generate new long-term and high-resolution precipitation, vegetation, and fire reconstructions using biomarkers preserved in a marine sediment core that capture the last 25 million years of tropical West African climate. Statistical and time series analyses will evaluate the amplitudes, periodicities, means, and relationships between hydroclimate, ecosystem, and fire proxies through time to decipher the differences in the amplitude of variability in the study windows to characterize sensitivity in the context of various boundary conditions. This project will provide crucial environmental context for the evolution of our earliest ancestors and will inform models of future terrestrial responses to global warming in this highly sensitive region.<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "14336", "attributes": { "award_id": "2125941", "title": "Significant improvements in the development and application of olivine-melt thermometry and hygrometry: new experiments and analytical approaches", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)", "Petrology and Geochemistry" ], "program_reference_codes": [], "program_officials": [ { "id": 6473, "first_name": "Jennifer", "last_name": "Wade", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-08-01", "end_date": null, "award_amount": 414716, "principal_investigator": { "id": 30928, "first_name": "Rebecca", "last_name": "Lange", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [], "awardee_organization": { "id": 169, "ror": "", "name": "Regents of the University of Michigan - Ann Arbor", "address": "", "city": "", "state": "MI", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in part under the American Rescue Plan Act of 2021 (Public Law 117-2).<br/><br/>Basaltic volcanism throughout Earth history has profoundly shaped the evolution of Earth’s crust and atmosphere, as well as the evolutionary path of life itself. In this study, erupted basalts are used as windows into the underlying mantle from which they were formed. The goal is to develop a new thermometer/hygrometer that enables both the temperature and water content of basalts to be readily and accurately obtained. Its ease of use will help generate large data sets, which will allow questions to be addressed about global differences in basalts erupted from diverse tectonic settings and throughout Earth history. The new thermometer/hygrometer will be made available to all interested users as a downloadable excel file. Two UM graduate students from diverse, under-represented backgrounds will work on this project. They will gain a broad range of skills, from expertise in conducting high-temperature and high-pressure experiments, performing thermodynamic calculations, and applying their results to better constrain mantle conditions that lead to partial melting. In addition, undergraduates from the M-STEM program at the University of Michigan (UM) will be recruited to work on this project.<br/><br/><br/>The goal of this project is to continue the experimental calibration a new olivine-melt thermometer that is based on the partitioning of Ni between olivine and basaltic liquids (DNiol/liq), and to further test whether it is independent of dissolved water at both crustal and mantle depths. Currently, the most widely used olivine-melt thermometers (based on DMgol/liq) are strongly dependent on water, and their application to hydrous basalts requires that melt H2O concentrations already be known, which is not always the case. With an H2O-independent thermometer in hand, based on DNiol/liq, it can be applied to olivine phenocrysts in hydrous basalts to obtain accurate temperatures, without prior knowledge of melt water contents. These temperatures can then be combined with Mg-based olivine-melt thermometers to obtain anhydrous temperatures and thus the magnitude of ∆T, the depression of the olivine liquidus due to dissolved water. Experiments will be performed to evaluate whether this depression of the olivine liquidus due to water is linearly and inversely correlated with the partitioning of Ca between olivine and melt (DCaol/liq), as indicated in preliminary work. To extend the calibration of this new olivine-melt thermometer/hygrometer, experiments will be performed on a variety of basaltic compositions over a range of water contents, temperatures, pressures (crustal and mantle) and fO2 conditions. Additionally, it is proposed to apply the new thermometer/hygrometer to a large number of natural basalts from a variety of tectonic settings. The results will shed light on the thermal/hydrous conditions in the mantle during partial melting across a variety of tectonic settings, from subduction zones to mantle plumes to continental rifts.<br/><br/>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.", "keywords": [], "approved": true } }, { "type": "Grant", "id": "14337", "attributes": { "award_id": "2100493", "title": "Collaborative Research: Two-way Coupled Fluid/Particulate Transport in Fractured Media - Bridging the Scales from Microscopic Origins to Macroscopic Networks", "funder": { "id": 3, "ror": "https://ror.org/021nxhr62", "name": "National Science Foundation", "approved": true }, "funder_divisions": [ "Geosciences (GEO)", "XC-Crosscutting Activities Pro" ], "program_reference_codes": [], "program_officials": [ { "id": 7676, "first_name": "Justin", "last_name": "Lawrence", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "start_date": "2021-08-01", "end_date": null, "award_amount": 348253, "principal_investigator": { "id": 30930, "first_name": "Peter", "last_name": "Kang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] }, "other_investigators": [ { "id": 30929, "first_name": "Peter K", "last_name": "Kang", "orcid": null, "emails": "", "private_emails": "", "keywords": null, "approved": true, "websites": null, "desired_collaboration": null, "comments": null, "affiliations": [] } ], "awardee_organization": { "id": 227, "ror": "", "name": "University of Minnesota-Twin Cities", "address": "", "city": "", "state": "MN", "zip": "", "country": "United States", "approved": true }, "abstract": "This award is funded in whole or in part under the American Rescue Plan Act of 2021 (Public Law 117-2). <br/><br/>The contamination of hydrologic systems such as oceans, rivers, lakes, and aquifers with particulates has emerged as one of the most urgent environmental issues of today. Recent field data suggests a clear presence of solid contaminants, such as microplastics and pathogens, in fractured aquifers which make up a significant portion of the world's drinking water supply and in other subsurface media. Understanding and predicting particulate transport in subsurface fracture flows poses both fundamental and practical challenges, as it requires a quantitative understanding of particle/fluid transport across many length scales that range from individual particles to a network of fractures. To overcome these challenges, our research will uncover the physical origin of the coupled particle/fluid transport and its effects on the large-scale particle transport, by combining laboratory experiments, theoretical modeling, and computations both at the particle scale and the network scale. The resultant particulate transport models will greatly improve our predictive capabilities for wide-ranging subsurface processes, which include contaminant transport, geological nuclear waste disposal, hydraulic fracturing, and enhanced geothermal systems. In addition, this project will provide training opportunities for graduate students and post-docs from diverse backgrounds, as well as collaborative educational activities for high school summer interns who will gain project-based experience as part of interdisciplinary teams.<br/><br/>The investigators will explore and quantify the effects of two-way coupled particle/fluid motion on particulate transport in fractured media, across a wide range of scales. Towards this end, they will combine detailed laboratory experiments as well as particle-resolving simulations at the single-fracture scale, with novel upscaling approaches to the fracture network scale. Traditional particulate transport models in subsurface systems treat particles as passive scalars that do not affect the surrounding flow field, although their preliminary experiments demonstrate that particles can actively modify the fluid flow and even trigger hydrodynamic instabilities. By overcoming this deficiency of traditional models, this research project will provide the next generation of large-scale subsurface particulate transport models. Specifically, they will address three research questions: 1) the microscopic origins of the two-way coupling; 2) the hydrodynamic instabilities and dispersion in a single fracture; 3) the effects of two-way coupling on network-scale particulate transport. They will conduct systematic laboratory experiments to characterize particle-scale instabilities and collective particle behavior at the single fracture scale, which will be verified and supplemented by particle-resolving Navier-Stokes simulations of concentrated suspensions in rough fractures. The resulting data will provide effective dispersivities and stochastic rules of particulate motion that capture the two-way coupling effects on particulate transport. These results from the single fracture study will be incorporated into fracture network models, in order to assess the influence of two-way coupling on particulate transport at the network scale and to develop upscaled particulate transport models.<br/><br/>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.", "keywords": [], "approved": true } } ], "meta": { "pagination": { "page": 3, "pages": 1392, "count": 13920 } } }