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Argonne National Laboratory

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Argonne Impacts State by State

Argonne’s collaborations in Ohio and across the United States have led to groundbreaking discoveries and development of new technologies that help meet the nation’s needs for sustainable energy, economic prosperity, and security.

Water-focused innovation engine’ aims to drive economic development across Illinois, Ohio and Wisconsin

Estimated market opportunity for innovative water treatment-related products and services by state. (Image by Great Lakes ReNEW/Current.)

A new water-focused innovation engine” aims to drive economic development and job creation in the Great Lakes region by finding new ways to recover clean water, energy and valuable materials from wastewater, while removing harmful chemicals. These efforts will be carried out by Great Lakes ReNEW, a collaboration of research institutions, universities, utilities, investors and development organizations spanning six states — including Illinois, Ohio and Wisconsin.

ReNEW is led by Current, a Chicago-based, water-focused innovation hub. The U.S. Department of Energy’s (DOE) Argonne National Laboratory and the University of Chicago are partners in the effort. The initiative will be funded by $160 million in potential grant money from the U.S. National Science Foundation. An initial $15 million portion of the grant will cover development activities in Illinois, Ohio and Wisconsin over the next two years. The remaining funds will be awarded contingent upon progress and could be applied more broadly across ReNEW member states.

Scientists at Argonne and Ohio University analyze single atom with X-rays for the first time

New technique for analyzing single atoms for the first time combines X-ray beams from Argonne’s APS and scanning tunneling microscopy probe. (Image by Argonne National Laboratory.)

Scientists from Argonne and Ohio University report being able to tell the elemental type and chemical properties of just one atom by using X-ray beams.

X-ray beams observe a sort of fingerprint for the type of elements in a material. For example, the NASA Curiosity rover gathered small samples of sand on the Martian surface, then determined with X-ray analysis that their content is similar to volcanic soil in Hawaii. Using powerful X-ray machines called synchrotron light sources, scientists can analyze samples as small as a billionth of a billionth of a gram. Such samples contain about 10,000 atoms. Smaller sizes have proved exceedingly difficult to achieve, but in an astonishing leap, the team managed to scale their observations down to a single atom.

The groundbreaking method combines use of a high-energy X-ray beam from Argonne’s light source, the Advanced Photon Source (APS), a DOE Office of Science user facility, and the imaging possible at the atomic level with scanning tunneling microscopy. By this method, the team identified and determined the chemical state of single atoms of a metal, iron, and a rare earth element, terbium.

This new capability could impact future fundamental research in numerous scientific disciplines and development of new technologies, from quantum information science to environmental research.

Scientists at Argonne and Ohio University can turn single molecules clockwise or counterclockwise on demand

Scanning tunneling microscopy image of a rotating europium (Eu) complex on a gold sheet. The dark spot in disc indicates the single Eu atom. (Image by Argonne National Laboratory.)

You can easily rotate a baseball in your hand by twisting your fingers. But you need inventive scientists with access to world-class scientific facilities to rotate an object that is only two billionths of a meter wide. That is a million times smaller than a raindrop. With the help of the world-class scientific facilities of the Center for Nanoscale Materials (CNM) and APS, scientists at the Argonne and Ohio University were able to precisely rotate and study the characteristics of a single molecule. The key ingredient in the molecule is a single atom of europium, a rare earth element. It rests at the center of the molecule and gives it many potential applications. The ability to control the motion of such a rare earth complex could impact a wide spectrum of technologies. That includes next generation microelectronics, quantum technologies, catalysis to speed up reactions, conversion of light into electricity and more. The team’s europium complex would reduce the amount of rare earth needed for a particular device and would be much less expensive to manufacture in mass quantities. The CNM is a DOE Office of Science user facility.

Ohio State takes honors in advanced vehicle competition managed by Argonne

The EcoCAR 3 Chevrolet Camaro. (Image by Argonne National Laboratory)

The Ohio State University (Columbus) was named the EcoCAR Mobility Challenge Year One champion in the four-year collegiate engineering competition managed by Argonne. EcoCAR, the latest DOE Advanced Vehicle Technology Competition, challenged 12 North American universities to apply advanced propulsion systems, electrification, Society of Automotive Engineers Level 2 automation and vehicle connectivity to improve the energy efficiency of a 2019 Chevrolet Blazer, while balancing emissions, safety and consumer acceptability.

Teams have four years (2018-2022) to transform their vehicles from design concept into reality, while building an energy-efficient, connected and semi-automated vehicle based on their engineered solutions. In addition to DOE, other EcoCAR sponsors included General Motors, MathWorks, NXP, National Science Foundation, Intel, American Axle & Manufacturing, Bosch, PACCAR, dSPACE, Siemens, Denso, Horiba, AVL, Delphi Technologies, California Air Resources Board, Tesa Tape, Vector, Electric Power Research Institute and Proterra.

BASF factory in Elyria to leverage Argonne battery technology

Argonne National Laboratory battery researchers (from left) Khalil Amine, Chris Johnson, Sun-Ho Kang and Mike Thackeray flank a continuously stirred tank reactor used to produce scaled-up quantities of cathode materials for lithium-ion batteries. (Image by Argonne National Laboratory)

Researchers at Argonne invented a game-changing structure for battery technology that led to multiple commercialization agreements and the building of two manufacturing plants in the Midwest, including one in Elyria, Ohio, by BASF Corp.

Argonne’s Nickel Manganese Cobalt (NMC) blended cathode structure was developed roughly 15 years ago. The development of NMC represented a major leap in lithium-ion battery technology from earlier cathode chemistries. It offers the longest lasting energy available in the smallest, lightest package. In 2009, BASF, the second largest producer of chemicals and related products in North America, licensed the NMC cathode technology and invested in further research and development as well as facilities to produce NMC-based products, which are used in electric and hybrid vehicles, personal electronics and power tools. In 2012, BASF invested $50 million to construct a 70,000-square-foot manufacturing plant in Elyria. Argonne and BASF also received a Deals of Distinction Award from the Licensing Executives Society Inc.

Ohio State, Argonne researchers earn award for paper on large-scale data visualizations

InSituNet uses deep learning to synthesize high-fidelity visualizations of science simulations, for example cosmological simulations that allow studies of the formation and evolution of galaxies. (Image by Vadim Sadovski/Shutterstock)

A team of researchers from Argonne and Ohio State won the Best Paper Award at the IEEE Scientific Visualization conference in Vancouver, Canada, in October 2019. The conference featured original research papers on scientific visualization, including theory, methods and applications ranging from mathematics and physical science to biosciences, economics and multimedia.

The paper, InSituNet: Deep Image Synthesis for Parameter Space Exploration of Ensemble Simulations,” presents a deep learning model for exploring parameter space for large-scale ensemble simulations in situ. The solution proposed by the Argonne-Ohio State team is a deep learning-based model, called InSituNet. Their approach works like this: Data is collected from an ensemble of simulations and visualized in situ using various visual mapping and view parameters. The model is then trained to learn the mapping from ensemble simulation parameters to visualizations of corresponding simulation outputs.