New datasets delineating global urban land support scientific research, application, and policy, but they can produce different results when applied to the same problem making it difficult for researchers to decide which to use.
The demand for energy is growing—and so is the technology supporting it. However, future development of power generation technologies could be affected by a key factor: material supply.
PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.
The Department of Energy Office of Nuclear Energy acting assistant secretary makes his first visit to a national laboratory in his new role, touring PNNL's Radiochemical Processing Laboratory.
Resolving how nanoparticles come together is important for industry and environmental remediation. New work predicts nanoparticle aggregation behavior across a wide range of scales for the first time.
Variations in the level of market globalization can greatly affect the amount of water required to meet future global demand for agricultural commodities.
Climate change and socioeconomic pressures are transforming passenger and freight transportation in the Arctic, producing effects that have yet to be fully understood.
Testing the assumption that different future socio-economic development patterns, which result in different land-use changes, can be paired with different future climate outcomes for risk assessments in a multi-model framework.
A poem inspired by radioactive tank waste—“Can a Scientist Dream it Alone?”—was awarded first place in the Department of Energy’s Poetry of Science Art Contest.
Incorporating spatially explicit land characteristics in a global model illustrates the complex effects of applying uniform regional protection assumptions in a global analysis.
