Lawrence Livermore National Laboratory (LLNL) researchers continue to capture key Department of Energy (DOE) Technology Commercialization Fund (TCF) grants with three new project grants announced in 2024.
This year's TCF program focuses on funding projects aimed at delivering clean energy solutions to the market - using new technology commercialized from DOE national labs to meet current U.S. climate goals such as lowering energy costs and achieving net-zero carbon emissions by 2050. The funding will support projects related to seismology, carbon dioxide removal and using simulations to create clean jet engines.
"It's important for national labs and industry to collaborate in order to mature technological innovations in mission-driven areas such as clean energy, and TCF is a pivotal program in enabling that," said Matthew Garrett, director of LLNL's Innovation and Partnerships Office (IPO). "Our team looks forward to supporting the collaborations needed to advance these technologies toward commercialization."
Under this year's TCF program, LLNL researchers will receive about $5.76 million, with $4.31 million from the DOE and $1.45 million from the Lab's Innovations and Partnerships Office and industrial partners. The DOE funds are provided through its Office of Technology Transitions.
Aiding carbon capture with real-time forecasts of seismicity
Carbon capture and storage (CCS) projects are one avenue researchers are exploring in efforts to reduce global emissions.
However, to scale geologic carbon storage technologies for commercial use in managing fossil energy emissions, advanced seismic monitoring is required to ensure efficient and proactive mitigation of potential induced seismic activity.
Real-time monitoring and accurate forecasting of induced seismic event detection and location would enable operators to proactively address risks and swiftly respond to adverse events, improving community safety and helping to build confidence in CCS.
Under this TCF project, LLNL, Oak Ridge National Laboratory (ORNL) and Instrumental Software Technologies Inc. (ISTI) researchers will collaborate in an effort to develop a real-time, machine learning pipeline with the goal of reducing latency by 20%, classifying earthquakes and non-earthquake sources as well as providing real-time forecasts of induced seismicity hazards and the production of high-precision historic seismic event catalogs.
Led by Kayla Kroll, research scientist and deputy group leader of LLNL's Seismology Group, the team will work under a 24-month, $1.81 million grant from DOE. Its partner, ISTI, will provide $451,000 in matching in-kind funds.
Optimizing site locations of carbon dioxide removal facilities
A key factor in successfully deploying carbon dioxide removal (CDR) technologies is selecting the right locations for the biomass carbon removal and storage (BiCRS) and direct air capture (DAC) facilities.
Elements to consider include technology performance, local feedstock variability, local resources and infrastructure, regional economic factors along with impacts of the CDR facility's scale, co-location with other industries and social legitimacy.
Under this TCF project, LLNL, ORNL, Phoenix Energy, Mote, AirMyne and WrightWay Energy Innovations researchers will collaborate in an effort to develop a dynamic framework for optimizing location siting for BiCRS and DACS facilities using feedstock-driven process modeling, spatial intelligence and smart co-location strategies.
The project also aims to create a versatile toolset that can be used to help communities identify the best CDR projects suited for local characteristics and help CDR developers pinpoint optimal deployment locations. Once developed, the toolset would offer comprehensive perspective on environmental impact, economic viability, technical performance and social considerations by location.
Led by Wenqin Li, a staff scientist in the energy utilization and delivery group in the Computational Engineering Division, and Simon Pang, deputy group leader of materials in the Energy and Climate Security Group, the team will work under a 24-month, $2 million grant from DOE. Its industry partners will provide $500,000 in matching in-kind funds.
Advancing detailed jet engine simulations
To reduce the climate impact of aviation, gas turbine designers are looking to accelerate the design cycle for the creation of new reliable, efficient and clean jet engines.
Under this TCF project, LLNL and GE Aerospace researchers will collaborate to reduce the computational cost of predictive gas turbine combustor simulations through the generation of small, accurate chemical reaction models and efficient graphical processing unit chemistry solvers. The goal is to reduce the time-to-solution for industry relevant simulations by more than 50%.
The ability to drive down the model size and computational cost while maintaining accuracy will be a key enabler for GE Aerospace and others in the jet turbine industry to design next-generation combustors and help the U.S. meet future sustainability and emissions goals.
Led by Russell Whitesides, a group leader of LLNL's Computational Engineering Division, the team will work under a 24-month, $500,000 grant from DOE. Its partner, GE Aerospace, will provide $500,000 in matching in-kind funds.
--Melissa Lewelling
