LIVERMORE, Calif. — Jacqueline Chen, whose work on fundamental turbulence-chemistry interactions in combustion helped advance the design of automotive, gas turbine and jet engines, was selected by the Department of Energy’s Office of Science as a distinguished scientist fellow — one of only eight researchers in the nation to hold the distinction.
Chen, a senior scientist in the Chemistry, Combustion and Materials Division of Sandia National Laboratories, is a pioneer in the field of advanced computational methods to understand combustion and chemical reactions relevant to engines.
The Office of Science’s recognition honors Chen’s career pushing the limits of supercomputers and applied math research to make engines more efficient while minimizing harmful emissions.
“It’s critical that we advance every tool that we can, including the world’s fastest high-performance computer, Summit at Oak Ridge National Laboratory. This supercomputer is capable of performing high-fidelity simulations that generate huge comprehensive sets of data to help the nation be energy efficient and evolve combustion engines to their maximum potential,” Chen said.
Chen’s achievements include a cool-flame ignition mechanism discovery that is important in modern diesel engines with exhaust gas recirculation. One recent discovery also is paving the way for the next generation of gas turbines for electricity generation, focusing on using hydrogen as a fuel to reduce carbon emissions from fossil fuels and to provide flexibility to complement the rising number of renewable energy sources, like solar power, that cannot be switched on or off to fit the needs of consumers.
She has also spent her career trying to inspire young scientists. She has mentored dozens of researchers who now have successful careers in labs, universities and industries across the nation. She has also brought scientists from different disciplines together to solve the problems of the future, through leadership of DOE’s Exascale Combustion Co-Design Center and the Exascale Computing Project on combustion simulation known as Pele, among others. Through these projects, national lab and university researchers are working together to improve the next generation of combustion application software optimized to exascale architectures for high-performance computing.
“Jackie’s selection as an Office of Science distinguished scientist fellow is testament to her brilliant intellect, devotion and passion for her work, her strong desire for collaboration and the energy and time she has dedicated to coaching and mentoring postdocs and students who are now trusted colleagues and scientific leaders,” said Sarah Allendorf, director of the Chemistry, Combustion and Materials Science Center at Sandia.
As an Office of Science distinguished fellow, Chen will use her expertise and her worldwide connections to advance machine learning and simulate engine combustion in even greater detail, to make engines cleaner and more efficient. She hopes to connect universities and the DOE labs through a new exascale computational framework that enables machine learning algorithms to be tested as part of combustion research. She will also generate high-fidelity combustion data used to train and validate physics-informed, machine-learned models.
She joined the national laboratory in 1982 and holds three mechanical engineering degrees: a Bachelor of Science from Ohio State University; a master’s degree from the University of California, Berkeley; and a doctorate from Stanford University.
Sandia National Laboratories is a multimission laboratory operated by National Technology and Engineering Solutions of Sandia LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration. Sandia Labs has major research and development responsibilities in nuclear deterrence, global security, defense, energy technologies and economic competitiveness, with main facilities in Albuquerque, New Mexico, and Livermore, California.
Sandia news media contact: Michael Langley, email@example.com, 925-315-0437