Researchers affiliated with the University of Minnesota, the University of California (UC), Berkeley, and the U.S. Department of Energy’s (DOE) Lawrence Berkeley National Laboratory have developed a breakthrough computer model that can identify the best molecules for capturing carbon from power plant stacks. The model greatly accelerates the search for new low-cost and efficient ways to burn coal and natural gas while also drastically reducing greenhouse gas emissions. But this significant breakthrough would not have been possible without key public investments in energy innovation.
Carbon capture technology development largely focuses on amine scrubbing, a process that uses chemical solvents to absorb carbon dioxide from coal and gas power plant stacks. However, fueling the traditional amine-based processes requires it to use as much as a third of the energy produced by the power plant itself. As a result, the process induces so-called “parasitic energy” costs – power producers must burn more coal or gas to run a power plant with amine carbon capture technology than a plant without. The added energy costs greatly reduce the potential for deployment, so dramatically lowering those costs through new technologies could go a long way in making carbon capture a viable clean energy technology worldwide.
That’s where the computer model comes in. The computer model project, co-led by Professors Laura Gagliardi and Berend Smit of the University of Minnesota and UC Berkeley, respectively, targets the potential use of metal-organic frameworks (MOFs), sponge-like, crystalline molecular systems that can capture and contain carbon dioxide and other greenhouse gases at significantly lower parasitic energy costs. And it cuts to a fraction the time required to isolate the MOFs that hold the best promise. Smit explains the significance of the new model in academic-speak:
“We’ve developed a novel computational methodology that yields accurate force fields – parameters describing the potential energy of a molecular system – to correctly predict the adsorption of carbon dioxide and molecular nitrogen by MOFs with open metal sites…MOFs have an extremely large internal surface area and, compared to other common adsorbents, promise very specific customization of their chemistry and could dramatically lower parasitic energy costs in coal-burning power plants. However, there are potentially millions of variations of MOFs and since from a practical standpoint we can only synthesize a very small fraction of these materials, the search for the right ones could take years. Our model saves this time by enabling us to synthesize only those that are most ideal.”
To be sure, this breakthrough accelerated the development of more cost-effective carbon capture technology, which the International Energy Agency finds must contribute at least one-fifth of the world’s total greenhouse gas emission reductions by 2050. But how did this breakthrough come about? Through government investment in innovation. Both scholars’ university research is supported by three key Department of Energy innovation programs: the Office of Science, the Lawrence Berkeley National Laboratory, and the Advanced Research Projects Agency-Energy (ARPA-E).
The computer model was born from the Center for Gas Separations Relevant to Clean Energy Technologies, which Berend Smit directs. It’s one of 46 DOE Energy Frontier Research Center’s (EFRCs), established in 2009 through the Office of Science, to conduct collaborative basic research into scientific breakthroughs that could result in untold leaps in clean energy development. Smit’s collaboration of universities and National Labs were chosen to study more cost and performance efficient ways to capture carbon dioxide from smoke stacks. Among other public research infrastructure, the Center used two Lawrence Berkeley National Laboratory user facilities to develop the fundamental framework for the model: the National Energy Research Scientific Computing Center, which is one of the largest super-computing facilities dedicated to science and the Molecular Foundry, which is dedicated to nanoscience.
Once the basic science research was successfully completed, ARPA-E provided an additional $4 million grant to the research team to complete development of the model for general use by carbon capture researchers everywhere so new absorption technologies can be developed in record time. The Berkeley Lab notes that with the successful completion of the model through the ARPA-E grant, “work is already underway to apply [it] to new amine-based systems for removing carbon dioxide from flue exhaust.”
And this story of government-supported breakthroughs is not only a great story for today, but is also a testament to how public support can have long-lasting impacts. Because of her work, Laura Gagliardi was recently tasked with directing the $8.1 million DOE-funded Nanoporous Materials Genome Center at the University of Minnesota to create similar computing model results for advanced nano-materials potentially important to clean energy, as she did with molecules important to carbon capture. And according to Gagliardi in e-mail correspondence with ITIF and echoing the Berkeley Lab’s statement, the breakthrough computer model can be expanded to cover more chemical and material-based science problems: “We are studying other systems and we would like to make the computer model very general so that it can be used by everybody.”
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