Vital to our nation’s future are innovative intelligent systems for water treatment and distribution, water-enabled energy production and the sustainable management of all our water resources.
Argonne National Laboratory offers a wide range of research capabilities and technologies that address these pressing challenges for water science and technology. These include materials discovery, synthesis, characterization and scale-up; new process technologies for systems that treat and handle water; and machine learning, artificial intelligence, data science, modeling and simulation.
With its partners in Chicagoland and beyond, Argonne is ideally suited to take materials and process technologies from discovery to application by tapping into our world-class materials and chemistry expertise, analytical capabilities at the Advanced Photon Source (APS), high-performance computing at the Argonne Leadership Computing Facility (ALCF), nanoscience and nanotechnology capabilities at the Center for Nanoscale Materials (CNM), and scale-up capabilities at Argonne’s Materials Engineering Research Facility. APS, ALCF and CNM are U.S. Department of Energy Office of Science user facilities at Argonne.
The Argonne Water + AI Strategy
Argonne’s ten-year strategy entails the advancement of water science and engineering empowered by artificial intelligence (Water + AI). The aim is a major transformation of three water-related systems essential to securing America’s water resources and delivering economic growth.
- Intelligent fit-for-purpose water systems. Such systems would provide water of the required quality and quantity to meet demand as it is needed. This would involve connecting water treatment plants to sensors along the distribution line, smart water meters and filters, and a smart phone user interface tied to wireless data collection and analysis.
- Intelligent water-enabled energy systems. Such systems would make more intelligent use of the cooling and waste water in power plants, the water involved in hydropower projects and the high-pressure water mixtures in fracking. Water power resource managers, for example, need advanced modeling tools to simulate the potential impacts and value of hydropower projects that would expand the use of renewable energy and its integration into flexible, reliable power grids. In addition, better methods are needed for recovering for beneficial uses the waste water in energy systems.
- Intelligent management systems for our water resources. Such systems would more intelligently manage ground water, surface water, and water in polar regions and the atmosphere. By identifying typical sources and distribution of microbial communities in waterways, for example, researchers can develop hydrological models that incorporate the microbial data, laying out how water flows from different sources and how rain events affect bacterial diversity and count.
This bold vision will be realized by drawing upon Argonne’s strengths in water science and engineering (materials research and scaling to the manufacturing level), unique capabilities in machine learning and artificial intelligence, and world-class scientific facilities such as the APS, ALCF, CNM and the Materials Engineering Research Facility (MERF).
National Water Challenges
Without water there is no life. Water—one of our most precious resources—is continually cycling through extraction from the environment, use and recycling to the environment when possible. Today the water cycle is under threat due to many factors including climate change, deforestation, increased pollution, greenhouse gases, increased demand and wasteful use. Researchers from around the world are searching for innovative solutions to make this cycle more effective and efficient and help secure a plentiful and clean water supply.
Water in the form of hydroelectric power is also a key component in the nation’s portfolio of energy sources. A pressing need exists for more intelligent approaches to minimizing the social and environmental impacts of creating a water reservoir by damming and changing water flow. Also needed are more intelligent approaches to handling the cooling water and waste water in energy systems.