Feature Articles

University of Washington professor Xiaodong Xu studies the properties of single atomic layer semiconductors, looking for new materials and new ways to control electrical conductivity.

The third iteration of the GeoAI leadership gathering focused on combining and scaling the many methods required to visualize and understand the Earth’s surface and how humans interact with it.

Nazia Zakir talks about her role as Environment, Safety and Health (ESH) senior director at Argonne National Laboratory.

Accurately predicting subseasonal weather conditions can help communities better prepare for emergency response in the event of strong storms or unprecedented flooding. This subseasonal to seasonal prediction capability is of particular interest to agencies such as the Air Force Weather, or AFW, program, which relies on accurate predictions to conduct missions safely and effectively around the world. In 2021, the AFW and ORNL launched two HPE Cray EX supercomputers, named Fawbush and Miller, to provide a platform for advanced weather modeling and prediction.

By adding rain, snow, and rain-on-snow precipitation data to a background model, a new scheme pinpoints local flood risks in order to improve the design of small-scale hydrological infrastructure.

Argonne was honored with the first Green Fleet Award as the laboratory continues to purchase zero-emissions vehicles.

The ARM Data Center collects and manages global observational and experimental data amassed by the Department of Energy (DOE) Office of Science’s Atmospheric Radiation Measurement user facility. The ARM Data Center gathers and curates some 50 terabytes of data per month from more than 460 instruments located in climate-critical locations worldwide. The data center processes and packages the information from these instruments into over 11,000 distinct data products. For the past 30 years, ARM has been making this data accessible to scientists around the world.

Idaho National Laboratory’s International Researcher and Visitor Program drives cross-cultural exchange and promotes collaboration with worldwide scientists and academia inspiring creativity within INL’s scientific community.

To do research, chemists need data to predict and explain the direction, outcome, and amount of energy released or used during a chemical reaction. This information – called thermochemical data – is essential for a good deal of fundamental chemical science and for understanding and improving industrial processes. Argonne National Laboratory developed the Active Thermochemical Tables (ATcT) over the last two decades to meet the growing need for such data in many sectors.