United States Department of Energy (DOE)

Limit: 3 // Tickets Available: 1 // PIs:
S. Sullivan (Chemical and Environmental Engineering)
X. Dong (Hydrology and Atmospheric Sciences) 

The DOE ASR  supports research on key cloud, aerosol, precipitation, and radiative transfer processes that affect the Earth’s radiative balance and hydrological cycle, especially processes that limit the predictive ability of regional and global models. This FOA solicits research grant applications for observational, data analysis, and/or modeling studies that use observations supported by the Biological and Environmental Research BER, including the Atmospheric Radiation Measurement (ARM) user facility, to improve understanding and model representation of: 1) Aerosol processes at ARM sites; 2) Convective cloud processes; 3) Aerosol and cloud processes from ARM’s Eastern Pacific Cloud Aerosol Precipitation Experiment (EPCAPE); and 4) Mixed-phase cloud and ice cloud processes. All research supported by awards under this FOA is intended to benefit the public through increasing our understanding of the Earth system.

No applicants // Limit: 1 // Tickets Available: 1 

An entity may submit only one Concept Paper and one Full Application to this FOA.

The research and development (R&D) activities to be funded under this FOA will support the government-wide approach to the climate crisis by driving the innovation that can lead to the deployment of clean energy technologies, which are critical for climate protection. Specifically, this FOA will invest in R&D to support continued innovation and cost reduction for high-voltage direct current (HVDC) voltage-source converter (VSC) transmission systems. This investment is intended to enable future grid upgrades required to integrate increasing renewable energy generation on to the grid, both onshore and offshore.EERE expects to make a total of approximately $10M of federal funding available for new awards under this FOA, subject to the availability of appropriated funds. EERE anticipates making approximately 3-4 awards under this FOA. EERE may issue one, multiple, or no awards. Individual awards may vary between $2.5M and $3.3M

No applicants // Limit: 1 // Tickets Available: 1 

UArizona may submit one proposal to the  to the GSI track. UA not eligible for research reactor track.

The Office of Nuclear Energy (NE) mission is to advance nuclear energy science and technology to meet U.S. energy, environmental, and economic needs. DOE intends to facilitate the education and training of nuclear scientists, engineers, and policy-makers through graduate and undergraduate study, two-year programs, and R&D that is relevant to the Department and the U.S. nuclear energy industry in general. Within Nuclear Energy University Program (NEUP), the specific goals of this Infrastructure FOA are: 

• To support, maintain, or enhance the institution’s capacities to attract and teach high quality students interested in nuclear energy-related studies;
• Build the institution’s research or education capabilities; and
• Enhance the institution’s capabilities to perform R&D that is relevant to NE’s mission.

The average GSI award will be approximately $250,000 for the total project period. No Cost Share / 1:1 Cost Match >$250k**. 

No applicants // Limit: 1 // Tickets Available: 1 

UArizona may submit only one Concept Paper and one Full Application.

This Funding Opportunity Announcement (FOA) is being issued by the Office of Energy Efficiency and Renewable Energy (EERE) on behalf of the Advanced Materials and Manufacturing Technologies Office (AMMTO). EERE’s AMMTO collaborates with industry, small businesses, universities, national laboratories, state and local governments, and other stakeholders to advance emerging energyrelated materials and manufacturing technologies to increase domestic competitiveness and build a clean, prosperous economy. This FOA seeks to:

• Strengthen the domestic manufacturing base and associated supply chains, for manufacturing large near net shape (NNS) metallic components through technology development;
• Reduce the U.S. dependence on foreign supply chains to achieve the nation’s clean energy and national strategic goals; and
• Increase U.S. competitiveness, reshore manufacturing, grow the economy, create skilled jobs, and ensure national energy security.

The intent of this FOA topic is to accelerate the development and commercialization of innovative manufacturing technologies to increase the competitiveness of the domestic Near Net Shape (NNS) manufacturing base and strengthen the clean energy manufacturing supply chains. The technical and economic viability of the proposed manufacturing technologies will be established by producing a full-scale component as part of the requirements. The component must be relevant to a clean energy manufacturing application with a weight over 10 tons (20,000 lbs.). Project teams are expected to represent multiple segments of the value/supply chain.

No applicants // Limit: 1 // Tickets Available: 1 

UArizona may only submit one Concept Paper and one Full Application for each topic area of this funding program.

The BIL is a once-in-a-generation investment in infrastructure, designed to modernize and upgrade American infrastructure to enhance U.S. competitiveness, driving the creation of good-paying union jobs, tackling theclimate crisis, and ensuring stronger access to economic, environmental, and other benefits for disadvantaged communities (DACs). The BIL appropriates more than $62 billion to the Department of Energy (DOE) including funding to support investments to build a clean and equitable energy economy that achieves zero carbon electricity by 2035, and puts the United States on a path to achieve net-zero emissions economy-wide by no later than 2050“ to benefit all Americans. As new load and generation come online as the market moves in line with these goals, deploying the projects that will support a more resilient and reliable grid will be critical. At present, aging grid infrastructure leaves the grid increasingly vulnerable to attacks. The increasing frequency of extreme weather events is leading to energy supply disruptions that threaten the economy, put public health and safety at risk, and can devastate affected communities all over the country.

This FOA seeks applications to address these three goals:
1. Transform community, regional, interregional, and national resilience, including in consideration of future shifts in generation and load
2. Catalyze and leverage private sector and non-federal public capital for impactful technology and infrastructure deployment
3. Advance community benefits 

H-J. Kim (Civil and Architectural Engineering and Mechanics) - Topic 7: Decarbonizing Cement and Concrete.
 

UArizona may submit one proposal to this funding program.

The Department of Energy’s (DOE) Office of Energy Efficiency and Renewable Energy announced a $156 million funding opportunity that will advance high impact applied research, development, and demonstration (RD&D) projects to reduce greenhouse gas (GHG) emissions across the U.S. industrial sector. The FOA, led by EERE’s Industrial Efficiency and Decarbonization Office (IEDO), will drive innovation to develop the next-generation technologies required to decarbonize industry, revitalize American manufacturing, create good-paying jobs, and improve community health.

Decarbonizing the industrial sector is critical to achieving the nation’s climate goals, as it is currently responsible for approximately one third of domestic greenhouse gas (GHG) emissions. DOE is building an innovation pipeline to accelerate the development and adoption of industrial decarbonization technologies with investments spanning foundational science; research, development, deployment, and demonstrations (RDD&D); and technical assistance and workforce development. 

IEDO’s efforts in this area are part of DOE’s new Technologies for Industrial Emissions Reduction Development (TIEReD) Program which leverages resources across different technology offices to invest in fundamental science, research, development, and initial pilot-scale demonstrations projects. 

1. H.J. Kim (Civil Engineering-Engineering Mechanics)
2. M. Tfail (Environmental Science) 
3. M. Chertkov (Applied Mathematics)

UA may submit three pre-proposals to this funding program.
 

Applications must focus on addressing basic research challenges motivated by the Energy Earthshots listed above. The scope of the Energy Earthshots are described below. This FOA is a collaborative effort across three SC research programs: Advanced Scientific Computing Research, Basic Energy Sciences, and Biological and Environmental Research. Program descriptions follow below. Multi-disciplinary applications are encouraged, addressing more than one SC research program. Additionally, the following common considerations apply to all Energy Earthshots:

Applicants should consider how innovative high-performance and scientific-computing techniques can contribute to advancing the goals of the proposed research. Applicants should also leverage the applications and software technologies developed by DOE’s Exascale Computing Project (ECP)10 to make use of computing at all scales. Applicants should also consider how to leverage data, software, models, and other information from recent and concurrent activities, including those funded by SC, other DOE departmental elements, and other agencies. SC resources include, but are not limited to, those with the Public Reusable Research (PuRe) Data designation11. Applicants are encouraged to consult the references posted on each Energy Earthshot’s webpage for information on other potentially-leverageable resources. 

V. Yurkiv ( Aerospace and Mechanical Engineering)

The DOE SC program in Basic Energy Sciences (BES) hereby announces its interest in receiving new applications for Energy Innovation Hub projects pursuing multi-investigator, crossdisciplinary fundamental research to address emerging new directions as well as long-standing challenges for the next generation of rechargeable batteries and related electrochemical energy storage technologies. Electrochemical energy storage is typically viewed as the bidirectional interconversion of electricity and chemical potential energy using electrochemistry for the purpose of storing electrical energy for later use, with lithium (Li)-ion and lead acid batteries being representative of the current generation of electrochemical energy storage. Discovery and scientific exploration of new battery chemistries, materials, and architectures for energy storage are encouraged. Research on electrolyzer/fuel cell combinations using hydrogen or hydrocarbons as the chemical storage media are supported elsewhere within DOE programs and are specifically excluded from this FOA. Regardless of materials and electrochemical processes involved, the focus must be on fundamental scientific concepts and understanding for the next generation of batteries and electrochemical energy storage. 

1. A.  Jalilzadeh (Systems and Industrial Engineering)
2. M. Chertkov (Applied Mathematics)
3. S. Missoum ( Aerospace and Mechanical Engineering)

4. D. Moore (Natural Resources & the Environment)

UA may submit four pre-applications as the lead institution in a single- or multi-institutional team. No more than two pre-applications for each PI at the applicant institution are allowed. 

The DOE SC program in Advanced Scientific Computing Research (ASCR) hereby announces its interest in research applications to explore potentially high-impact approaches in the development and use of scientific machine learning (SciML) and artificial intelligence (AI) in the predictive modeling, simulation and analysis of complex systems and processes.

High-performance computational models, simulations, algorithms, data from experiments and observations, and automation are being used to accelerate scientific discovery and innovation. Recent workshops, report, and strategic plans across the DOE have highlighted the research, development, and use of artificial intelligence and machine learning for science, energy, and security. Relevant domains include materials, environmental, and life sciences; high-energy, nuclear, and plasma physics; and the DOE Energy Earthshots Initiative, for examples. A 2018 Basic Research Needs workshop and report on scientific machine learning (SciML) and AI1 identified six Priority Research Directions (PRDs) for the development of the broad foundations and research capabilities needed to address such DOE mission priorities. The first three PRDs for foundational research are a set of themes common to all SciML approaches and correspond to the need for domain-awareness, interpretability, and robustness and scalability, respectively. Of the other three PRDs for capability research, PRD #5 (Machine Learning-Enhanced Modeling and Simulation) and uncertainty quantification are the subject of this FOA. 

No applicants // Limit: 3 // Tickets Available: 3

UA  is limited to no more than three pre-applications, or applications with one for each PI at the applicant institution.

The DOE SC program in Fusion Energy Sciences (FES) hereby announces its interest in applications in the areas of Machine Learning (ML), Artificial Intelligence (AI), and Data Resources for fusion energy and plasma sciences. The goal of this FOA is to support multidisciplinary teams aiming to apply advanced and autonomous algorithms to address high-priority research opportunities across the FES program. Applicants are encouraged to propose research in new systems for managing, formatting, curating, and accessing experimental and simulation data, provided in publicly available databases. Of high programmatic importance are approaches that support the realization of a fusion pilot plant on a decadal timescale.