With Department of Energy our main customer, we apply national-security solutions to energy systems. LLNL technologies are employed in energy storage and conversion and the generation, delivery, and efficient use of electric power.
We do power generation and distribution optimization, cyber and physical security.
Design computationally-enabled inverse design is leading to batteries that address grid-level storage.
The development of carbon-reduction reactors will reduce atmospheric CO2 and yield energy byproducts.
We're developing low-friction, high-energy-capacity flywheel systems for a variety of applications.
Some of our current projects we are working on include:
The Grid Modernization Lab Consortium is a massive effort among the DOE and national laboratories to upgrade and harden U.S. energy supply and delivery via analysis, simulation, machine learning, cybersecurity, and improved integration of the electrical grid and gas system.
Natural gas is a critical resource in our economy. In some areas, the electric grid depends on the gas system. LLNL works with Homeland Security and others to learn how these systems cooperate and improve security and reliability.
LLNL supports DOE efforts to understand the intricate U.S. electric power generation, distribution, and user systems. Studies and simulations using techniques such as machine learning promise to improve efficiency, reliability, and security.
Electrochemical carbon-reduction reactors can reduce atmospheric CO2 concentration while creating useful materials like ethylene in the process. Using advanced manufacturing and computational inverse design, engineers create advanced reactor systems that operate at industrially viable throughputs, efficiencies, and cost.
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