Six projects by researchers at the U.S. Department of Energy’s (DOE) Argonne National Laboratory were recognized with 2024 R&D 100 Awards. The awards, frequently referred to as the “Oscars of Innovation,” recognize exciting new products or processes that have been developed in the past two years. An additional three projects were named finalists.
“I would like to send my heartfelt congratulations to the Argonne researchers and their partners who were named winners or finalists in this year’s program,” said Argonne Director Paul Kearns. “Their impactful research is an inspiration for our laboratory and the entire science community.”
Argonne has a decades-long history of winning R&D 100 awards, including 151 winners since the competition began in 1963. Past winners also include Fortune 500 companies, other DOE national laboratories, academic institutions and smaller companies.
Argonne’s winners are:
AXES: The Complete Advanced X-Ray Emission Spectrometry Solution
AXES is a complete advanced X-ray emission spectrometry (XES) solution featuring the only high-performance XES spectrometer with the unprecedented ability to probe seven different elements simultaneously. This instrument enables scientists to make correlative electronic discoveries with minimal human intervention due to its integrated AI-enabled image processing software that performs data analyses in real time. (Argonne development team: Chengjun Sun, Mikhail A. Solovyev and Shelly Diane Kelly)
Direct Recycling Process for Lithium-Ion Battery Cells
Argonne’s direct recycling process recovers positive electrodes from lithium-ion batteries so that the positive electrodes can be directly re-used in battery manufacturing. This significantly increases recycling profitability. Traditional recycling processes are less profitable because they break down batteries into lower-value elements. Direct recycling also has a much lower environmental footprint. (Argonne development team: Albert L. Lipson, Jessica D. Macholz, Jeffrey S. Spangenberger, Qiang Dai, Peyton Melin, Sabine M. Gallagher, Michael LeResche, Bryant Polzin and Donghyeon Kang)
Hydro4Crystal
The Hydro4Crystal platform produces single-crystal battery cathode materials that are faster, less complex and more efficient than conventional methods. Hydro4Crystal integrates single crystal formation, lithiation, doping and surface coating into a swift, continuous, one-pot procedure. The battery cathode materials increase energy density, enhance charging speed, and extend battery life. (In partnership with ACT-ion Battery Technologies. Argonne principal investigator: Youngho Shin)
Rapid Thermal Processing of Solid-State Lithium Battery Ceramic Electrolyte Materials
Rapid photonic processing technology forms ceramic electrolyte materials for solid-state lithium batteries within seconds at room temperature, bypassing the long sintering time and high energy consumption of conventional technologies and enabling high-throughput roll-to-roll manufacturing of solid electrolytes at a lower cost and smaller carbon footprint. (In partnership with PulseForge, Inc.; Argonne development team: Yuepeng Zhang, Jungkuk Lee, Samuel David Miller, John Hryn and Gregory Krumdick)
Ultra-Fast Selective Delamination (UFSD) of Lithium-Ion Battery Electrodes
Researchers at Argonne developed a new technique called ultra-fast delamination, which is an energy-saving and environmentally sustainable process to recycle and recover critical materials from lithium-ion battery electrodes. The technique works by separating electrode materials from manufacturing scrap and end-of-life lithium-ion batteries. (Argonne development team: Bryant J. Polzin, Ozgenur Kahvecioglu and Beihai Ma)
Lagrangian-Eulerian Spark Ignition (LESI) Model
The Lagrangian-Eulerian Spark Ignition (LESI) model is the most accurate ignition model available for computational fluid dynamics software packages used to simulate internal combustion engines. LESI can be used to describe and improve spark-ignition processes in internal combustion engine-powered vehicles, with the goal of improving their efficiency and reducing their greenhouse gas emissions. (Argonne development team: Riccardo Scarcelli and Samuel Kazmouz)
Argonne’s finalists are:
National Economic Resilience Data Explorer (NERDE)
NERDE is a transformative data explorer and decision-support tool that enables planners, economic development organizations, administrators and nongovernmental organizations — regardless of expertise or resources — to improve the economic development and resilience efforts in their communities by providing near-real-time access to data from more than 200 databases nationwide in highly usable form. NERDE democratizes and transforms the marketplace for economic development data by offering it free of charge to any users who may benefit from it, so that communities across the nation can strengthen their economic development and resilience planning — regardless of their economic resources and circumstances. (Argonne development team: Iain Hyde, Carmella Burdi, Alison Turner, Parfait Gasana, Adam Shaw, M. Ross Alexander and Matt Cowan)
DeepHyper (submitted by Oak Ridge National Laboratory, in partnership with Lawrence Berkeley National Laboratory)
DeepHyper is an open-source software package that reduces complexity in the development workflow of AI models. It simplifies the complex processes involved in building machine learning (ML) and deep learning (DL) models by automating data preparation, model selection and parameter tuning. This automation is particularly valuable for handling complex predictive and generative modeling problems involving large datasets, where manual adjustments are challenging and time-consuming. DeepHyper focuses on creating models that are not only accurate but also energy-efficient, cost-effective and trustworthy. (Argonne development team: Romain Egele, Remit Maulik, Sandeep Madireddy, Yixuan Sun, Tanwi Mallick, Krishnan Ragavan, Adarsha Balaji, Hongwei Jin and Misha Salim)
Pele (submitted by National Renewable Energy Laboratory, in partnership with Sandia National Laboratories, Lawrence Berkeley National Laboratory, Oak Ridge National Laboratory and Lawrence Livermore National Laboratory)
Pele is the Exascale Computing Project’s (ECP’s) application suite for high-fidelity detailed simulations of turbulent combustion in open and confined domains. It includes detailed physics and geometrical flexibility to evaluate design and operational characteristics of clean, efficient combustors for automotive, industrial, and aviation applications. It targets simulation capabilities required to inform next-generation combustion technologies. (Argonne principal investigator: Stephen Klippenstein)