DOE’s Office of Fossil Energy is the primary sponsor for this HPC4Mtls Program. FE plays a key role in helping the United States meet its continually growing need for secure, reasonably priced, and environmentally sound energy from our abundant fossil energy resources. The Office of Fossil Energy Research and Development (FER&D) Program advances transformative science and innovative technologies that enable the reliable, efficient, affordable, and environmentally sound use of fossil fuels.
Decarbonization of the power and industrial sectors is of renewed interest, and hydrogen is expected to play a role in decarbonizing these sectors. As fossil energy is the source of >95% of hydrogen worldwide and in the U.S., FE technologies in hydrogen production and utilization will play a major role.
FE partners with industry, academia, national labs, and research facilities in transformative science and innovative technologies that enable the reliable, efficient, affordable, and environmentally sound use of fossil fuels. FE supports cost‐shared research, development, and demonstration activities in support of crosscutting next-generation technologies and processes that further the development of advanced fossil technologies. Proposals should provide a realistic assessment of the benefits to the domestic materials supply chain and/or fossil energy application (e.g. power plant).
Of particular interest to AMO are:
- Improving the understanding of the materials impacts including corrosion anderosion effects of gasification of blends of coal, biomass and waste plastics on materials in high temperature regions of a gasifier, including sensitivity analysis of blend percentages and types of coal, biomass and waste plastics in the process feed
- Improving the understanding of the material impacts including hydrogen embrittlement effects of blends of natural gas and hydrogen on materials inpipelines, welded joints or compressors, including sensitivity analysis of blend percentages
- Use of computational databases and machine learning for thermal barrier coating (TBC) development for hot gas path components of combustion turbines firingnatural gas-hydrogenblends or 100% hydrogen
- Improving the understanding of detailed processes in critical focus areas suchasoxidation, corrosion, and electrochemical interactions in Creep Strength Enhanced Ferritic(CSEF) alloys, austenitic alloys and high nickel superalloys
- Use of computational databases and machine learning for catalyst development to synthesize, test, characterize, and scale materials which convert carbon oxidesinto value-added products with increased energy efficiency, higher selectivity, andlowerenvironmental impacts based on a lifecycle analysis relative to conventionalproducts
- Developing machine learning capabilities to predict composition, thermal performance, and mechanical properties of new materials for energy storage
- Developing the capability to predict the mechanical behavior and properties of additivelymanufactured components for use in advanced power cycles suchassupercritical carbon dioxide cycles
1. Materials Supply Chain for Fossil Energy Applications:
- Reducing the cost of ingot production for nickel superalloys suitable for fossil energy applications
- Improving high-temperature mechanical performance for lower-cost alloys ascompared with more costly, high nickel/cobalt alloys
- Overcoming barriers to scale up new material production from grams to kilograms, and from kilograms to tonnes
- Overcoming barriers to the manufacture of components with High Entropy Alloys (HEA)
- Improving speed and quality of welding and other advanced joining methods for nickel superalloys
- Advanced manufacturing of components for fossil energy applications, particularly for repair of existing plant components and modular fabrication of new plants
- Machine learning within the supply chain to lower costs and improve productivity
2. Existing and New Power Plant Applications:
- Predicting material behavior in specific severe environments, such ashigh-temperature, cyclic, or oxidative/corrosive, erosive environments, found in coalgasification systems
- Development of coatings, claddings, and other surface treatments to mitigateoxidation, corrosion, and erosion of high-temperature components
- AI applications for monitoring and diagnostics of power plants focused onmaterials failures such as calculating remaining useful life of components or patternrecognition
- Analysis of thermal fatigue-driven failures, particularly in coal-fired boilersand natural gas combined cycle heat recovery steam generators, to develop and/orvalidate remaining life predictive tools.
- Improving reliability of dissimilar welds between CSEF alloys, austenitic alloysand/or high nickel superalloys
- Overcoming barriers to the manufacture of components for fuel cells
- Developing machine learning capabilities to identify promising new materials fornon-battery energy storage technologies that can integrate with fossil energy powergenerating units