Grants and Contracts Details
The overarching hypothesis of D3TaLES (Data-enabled Discovery and Design to Transform Liquid-based Energy Storage) is that truly novel advances in the discovery and design of liquid-based energy storage materials will require synergistic efforts that both create new domain knowledge in the field and capitalize on the mass collection, creation, and analysis and modeling of curated data via tools such as machine learning (ML). Our mission to answer this challenge will be achieved through the construction of an interdisciplinary network of collaborators in the EPSCoR jurisdictions of Kentucky and Iowa that have expertise in materials design, characterization, and deployment; high-throughput computation; autonomous experimentation; and data analytics and ML. Our vision is that our synergic research, infrastructure, and workforce development activities will allow Kentucky and Iowa to be critical hubs to address the growing energy storage capacity needs that will fuel the 21st century U.S. economy. Intellectual Merit: D3TaLES establishes an interdisciplinary, collaborative team to rapidly explore and describe molecular-architecture–environment–property relationships to develop new liquid-based energy-storage materials. We will combine domain knowledge in materials creation and characterization with emerging best practices in data science and ML to advance discovery and design principles in liquid-based energy storage materials. Such advances cannot be accomplished by experts in their respective fields alone, as the questions that need to be answered can only be addressed through concerted, synergistic efforts. The three main objectives of D3TaLES are: i) determine solvation environment of redox-active materials at a function of molecular structure, state of charge, and environment; ii) link analyte solubility to solvation at high concentrations as it impacts solvent and analyte structures and phase transitions in traditional and ionic liquids; and iii) design and deploy a data-driven autonomous computational-experimental approach to explore the impact of molecular architecture and IL composition on energy storage metrics. Broader Impacts: The research and infrastructure developments produced by D3TaLES will afford new routes to discover and design liquid-based energy storage materials, with the knowledge and materials providing the capability to transform EES across all scales of energy storage needs.The development of an open-access, curated database that contains data from D3TaLES and literature scraping will enable other researchers across the globe to build on and add to the knowledge developed by D3TaLES, offering the potential to facilitate expedited creation and deployment of new EES materials. D3TaLES presents opportunities for extensive training and workforce development that will have wide-ranging impact within the academic units and local communities in the Kentucky and Iowa EPSCoR jurisdictions and across the broader U.S. energy sector and economy. The Academy for Collaborative Leadership (ACL) will prepare early-career faculty in EPSCoR states to build and lead diverse groups of researchers and serve as the next-generation of academic research-center directors. Postdoctoral, graduate, and undergraduate researchers will be trained beyond their disciplines, with a focus on training chemical and physical scientists on the application of data science, ML, and autonomous experimentation. Undergraduate students, particularly those hailing from primarily undergraduate institutions (PUI), will be afforded experience that connects fundamental research within social context to increase the likelihood of their participation in the STEM workforce. Further, as Kentucky and Iowa are predominantly rural states, we will focus on the recruitment of undergraduate students from these communities to work in the research laboratory, and provide training for these students to return to their communities and discuss their scientific pursuits with the general public.
|Effective start/end date||9/1/20 → 8/31/22|
- National Science Foundation: $1,287,055.00
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