Applying science and technology to improve national energy security, protecting the environment and providing for U.S. economic competitiveness
Energy-Saving Applications of Chemical Reactors
Combining additive manufacturing (AM) with multiscale modeling, Livermore researchers are rapidly cycling the design and testing of modular electrochemical reactors with enhanced performance. The versatility and precise control offered by 3D-printing makes it possible to tailor reactors to specific applications and operating environments. The innovative work aims to transform the way many products are manufactured and has the potential to give U.S. industry a competitive advantage in chemical manufacturing. Reactors are used to convert selected molecules into valuable industrial feedstocks. The much smaller 3D-printed electrochemical reactors operate at ambient temperature and low pressure, making them more energy efficient and offering much lower capital and operating costs than larger thermochemical systems now widely used by industry.
For many applications, the molecule to be converted is CO2, which is abundant and the lowest energy state of carbon. Through a cooperative research and development agreement, Laboratory researchers are working with partners at TotalEnergies, Stanford University, and SLAC National Accelerator Laboratory to design next-generation electrochemical reactors for industrial CO2 conversion using computationally driven algorithms. Production of ethylene, the most common carbon-based commodity chemical in the world, requires extreme conditions, whereas a reactor operates at room temperatures. Iteration of computational modeling and AM of trial reactors promises to rapidly converge on a design that is efficient in both energy usage and conversion of CO2 into ethylene.
LLNL researchers are also examining biomass as an alternative conversion fuel for electrochemical processes rather than water or CO2. Current electrolyzers, which convert electrical energy into molecules with high potential-energy densities, struggle with energy efficiency due to oxygen gas production at the anode. The Livermore team found that replacing this oxygen evolution reaction with biomass oxidation could cut energy use by more than 50 percent. This process cleans up chemical production by converting 5-Hydroxymethylfurfural (HMF), derived from biomass, into 2,5-Furandicarboxylic acid (FDCA), a valuable building block for sustainable plastics like PEF (a bio-based polymer). In addition, Laboratory researchers are studying the feasibility of reactors converting nitrogen (N2) to ammonia. Roughly half the world’s population relies on crops grown with the aid of synthetic fertilizers composed primarily of nitrates and ammonia.
Enhancing the Energy Grid
LLNL is the lead laboratory for DOE’s North American Energy Resilience Model (NAERM) project, an ambitious initiative to develop ground-breaking capability to ensure reliable and resilient energy delivery across multiple sectors, spanning multiple organizations and authorities, while considering a range of large-scale, emerging threats. NAERM advances existing capabilities to model, simulate, and assess the behavior of electric power systems, as well as its associated dependencies on natural gas, telecommunications, and other critical infrastructures. The model predicts the impact of threats, evaluate and identify effective mitigation strategies, and support black start planning, benefiting the U.S. by advancing energy and economic security.
LLNL applies its expertise in high-performance computing (HPC) simulations, uncertainty quantification, risk analysis and decision support, and data analytics and machine learning to advance power grid modeling and enable resilient grid design and operations. Laboratory researchers have supported DOE’s grid modeling efforts by developing and importantly, improving the performance of HPC modeling capabilities that integrate transmission and distribution components of the grid. The State of California provides interesting test cases for Livermore’s analyses. California has a wide variety of energy sources including a growing number of distributed energy resources (DERs); droughts and floodings; and potential disruptions from fire, earthquakes, or consequences of human actions. DERs, which in the future could include small nuclear reactors as well as renewable sources, make possible creation of a more decentralized grid, which would be more resilient to a wide variety of natural threats and cyberattacks. Laboratory researchers are studying the potential of using AI to achieve a dynamically adaptive distributed power grid that can detect and respond to threats to minimize disruption and impact. In addition to the simulations, Livermore’s Skyfall laboratory connects real-world equipment with HPC simulation capabilities to study how transmission and distribution systems might respond to a broad range of power irregularities.
Concentrating on Rare-Earth Elements
Under the Defense Advanced Research Project Agency's Environmental Microbes as a BioEngineering Resource program, a Laboratory team received an additional $4.6 million in funding for phase two of their research efforts to develop a separation technique that will increase the concentration of rare-earth elements (REE) so they are more readily available to the defense sector. This effort builds on a long history of a bio-REE extraction process developed by the Laboratory through the DOE Critical Material’s Institute. To date, the chemical processes to extract and purify REEs are complex and harmful to the environment. REEs are a set of 17 elements in the periodic table that includes the 15 lanthanides, plus scandium and yttrium. They are essential for American competitiveness in a high-tech economy because they are used in many devices important to U.S. industry and national security, including computer components, wind turbines, hybrid/electric vehicles, liquid crystal displays, and tunable microwave resonators. In the defense sector, they are used for lasers, precision-guided weapons, motor magnets, and other devices.
The team will use bioengineered proteins to enhance the biomining workflow and to produce high-value reagents needed for REE processing. Use of natural products, such as the protein lanmodulin, allows for one-step quantitative and selective extraction or recycling REE from new sources, including electronic waste and coal byproducts—something other chemical extraction methods cannot do. LLNL researchers are poised to discover game-changing different flavors of REE-binding proteins with much greater separation power. The team will use the Laboratory’s HPC capabilities to iteratively design and improve proteins with enhanced REE specificity and affinity using machine learning. Ultimately, the goal is to commercialize the technology for use in the mining and REE recycling sectors.
