NSF AI Disclosure Required
NSF requires disclosure of AI tool usage in proposal preparation. Ensure you disclose the use of FindGrants' AI drafting in your application.
CAREER: Modeling two-phase flow, multi-lithologic melting, and chemical disequilibrium with uranium-series isotopes
NSF
About This Grant
This project aims to explore the origins of magmas using computer models that predict the chemical makeup of lavas, particularly for isotopes that preserve information about rates of melting and magma transport in the Earth’s mantle layer. The project tests for the role of alternative mantle rock types in generating magma, and for the importance of chemical diffusion during magma transport. Questions about magma origins are fundamentally important to our understanding of dynamic global processes and plate tectonics, including the origins of new oceanic crust produced by volcanic eruptions. The project further aims to develop a computer modeling program housed at the University of Nebraska to train the next generation of geoscience computer modelers, and to increase public engagement and literacy with STEM through broader outreach. Modeling techniques and tutorials will be hosted and managed online in an open-source code repository and educational library. The roles and importance of recycled mantle lithologies in mantle melting and basalt generation and of the influence of slow chemical diffusion on multi-lithologic partial melting remain unclear. Uranium-series disequilibria in lavas may provide a method for identifying lithologic source heterogeneity, but U-series modeling remains complex and difficult to replicate. The overall research goal of this study is to test multi-lithologic melting and diffusive exchange through the development of new, open-source modeling packages that predict U-series disequilibria in basalts, and to ground-truth that modeling effort by comparison of existing U-series data with measurements sensitive to the presence of pyroxenite in the melting regime. The educational goals are to incorporate the modeling work into lessons for existing and new geoscience courses and to create and curate digital lessons and training tutorials and share them via an online program. The rationales for this work are to advance the understanding of mantle melting processes, train a future cohort of sophisticated geoscience modelers, and develop widely-accessible and reproducible melt modeling tools that can be integrated into community research and teaching efforts. The outcomes of the project will be amplified through the development of archived, open-source, cloud-hosted modeling code packages. 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.
Focus Areas
Eligibility
How to Apply
Up to $217K
2027-05-31
One-time $749 fee · Includes AI drafting + templates + PDF export
AI Requirement Analysis
Detailed requirements not yet analyzed
Have the NOFO? Paste it below for AI-powered requirement analysis.