Argonne to host eight graduate student awardees in Department of Energy-sponsored research program estevens@anl.gov Mon, 01/22/2024 - 15:21 Argonne hosts and mentors doctoral students through graduate student research program Graduate students gain access to world-class research, resources and mentorship at Argonne. 25771914421_738591-1600x900.jpg At Argonne, students in the SCGSR program will have the chance to conduct hands-on research, with professional STEM researchers such as materials scientist Justin Connell ready to assist as mentors. (Image by Argonne National Laboratory.) Nathan Schm ..read more

Jonathan Yarranton jyarranton@anl.gov Mon, 12/04/2023 - 05:02 Related Organizations Chemical Sciences and Engineering Science & Technology Topics Crystallography Inorganic Chemistry Organic Chemistry Physical Chemistry Computational Chemistry Energy Conversion X-Ray Science and Technology Discipline Energy R&D Display Work Address No Display Fax Number No Display Work Email Address Yes ..read more

Jonathan Taylor Yarranton jyarranton@anl.gov Mon, 12/04/2023 - 05:02 Related Organizations Chemical Sciences and Engineering Science & Technology Topics Crystallography Inorganic Chemistry Organic Chemistry Physical Chemistry Computational Chemistry Energy Conversion X-Ray Science and Technology Discipline Energy R&D Display Work Address No Display Fax Number No Display Work Email Address Yes ..read more

Using supercomputers to help companies advance clean energy technologies cloudadminsju@… Mon, 11/20/2023 - 16:08 Argonne’s high performance computing systems and expertise will help industry address challenges in manufacturing and materials development Through DOE’s High Performance Computing for Energy Innovation initiative, Argonne will partner with Ford Motor Company, Capstone Green Energy, Lakril Technologies and Power Manufacturing to help accelerate the development of clean energy technologies. 33181D_086_ALCF Polaris_1600x900 Argonne's Polaris supercomputer brings advanced capabilities ..read more

Argonne’s Aurora supercomputer set to supercharge materials discovery cloudadminet@a… Fri, 10/13/2023 - 09:23 Researchers will use the exascale system and AI to speed up the search for new materials for batteries, catalysts and other applications Through the Aurora Early Science Program, researchers are preparing to leverage Argonne’s exascale supercomputer to model the behavior of materials at an unprecedented level of detail. qmc_23_gray_hires_01_1600x900 Researchers are using the QMCPACK code to accurately predict complex materials properties, such as the electron spin density of cobalt-dop ..read more

Speeding up the discovery of new catalysts for clean energy with Aurora estevens@anl.gov Thu, 07/06/2023 - 13:47 Researchers will use Argonne’s exascale supercomputer to advance computational chemistry Researchers are developing exascale software tools to enable the design of new chemicals and chemical processes for clean energy production. C179H400Cu3600O206 C179H400Cu3600O206: Figure of representative molecules calculated on the surface of isotope Copper-111 (Image by Argonne National Laboratory/David Bross.) Jeremy Sykes July 12, 2023 The U.S. Department of Energy’s (DOE) Argonne National ..read more

Science beyond Siri: A team of educators and computer scientists take on AI cloudadminjba@… Tue, 11/01/2022 - 11:53 Soon enough, AI competency will be an essential workforce skill. A group of computer scientists and learning science experts are considering what a foundational introduction to AI might look like for middle school and high school students. Argonne+NIU-AIcamp.jpg Argonne National Laboratory and Northern Illinois University collaborated to host a camp that introduced middle school and high school students to artificial intelligence. (Image by Argonne National Laboratory.) Laura Wol ..read more

Scientists use machine learning to accelerate materials discovery cloudadminlm@a… Mon, 10/03/2022 - 16:03 A new computational approach will improve understanding of different states of carbon and guide the search for materials yet to be discovered. metastable-16x9.jpg The final product of the machine learning algorithm: metastable phase diagrams for carbon. The colored regions indicate conditions at which carbon exists in certain metastable states that may yield useful material properties. (Image by Argonne National Laboratory.) Savannah Mitchem October 5, 2022 Materials — we use them, w ..read more

Helping companies improve energy efficiency through high performance computing cloudadminjba@… Mon, 10/03/2022 - 12:32 Argonne is working closely with industry leaders on two new projects that will advance the development of carbon capture technology and improve the energy efficiency of chemical manufacturing processes. PowerplantandGenerator__shutterstock_740085760-16x9.jpg Argonne has received funding from the DOE for two new high performance computing projects that advance cutting edge manufacturing and clean energy technologies. One of the projects focuses on modeling carbon capture techno ..read more

Xiaoyu Wang xiaoyu.wang@anl.gov Tue, 05/31/2022 - 05:03 Research Interests Rare Earth Elements Separations; Liquid-Liquid Equilibria; Interfacial Behaviors; Zeolites in Separations and Catalysis; Ionic Liquids; Energy Storage; Chiral Enantiomer Separations; Molecular Dynamics Simulations. Education PhD in Chemical Engineering, Illinois Institute of Technology, Chicago, IL (2020) BSci in Chemistry, Sichuan University, Chengdu (2012) Awards and Honors NSF Graduate Research Fellowship, Illinois Institute of Technology, 2015 Gamson Fellowship, Illinois Institute of Technology, 2014 Energy Tech ..read more