Oak Ridge National Laboratory scientists worked with the Colorado School of Mines and Baylor University to develop and test control methods for autonomous water treatment plants that use less energy and generate less waste.
Researchers at Oak Ridge National Laboratory have identified a statistical relationship between the growth of cities and the spread of paved surfaces like roads and sidewalks. These impervious surfaces impede the flow of water into the ground, affecting the water cycle and, by extension, the climate.
Algorithms developed at Oak Ridge National Laboratory can greatly enhance X-ray computed tomography images of 3D-printed metal parts, resulting in more accurate, faster scans.
Scientists at Oak Ridge National Laboratory and the University of Tennessee designed and demonstrated a method to make carbon-based materials that can be used as electrodes compatible with a specific semiconductor circuitry.
Oak Ridge National Laboratory researchers have developed a machine learning model that could help predict the impact pandemics such as COVID-19 have on fuel demand in the United States.
Researchers at Oak Ridge National Laboratory developed a method that uses machine learning to predict seasonal fire risk in Africa, where half of the world’s wildfire-related carbon emissions originate.
Ada Sedova’s journey to Oak Ridge National Laboratory has taken her on the path from pre-med studies in college to an accelerated graduate career in mathematics and biophysics and now to the intersection of computational science and biology
While Tsouris’ water research is diverse in scope, its fundamentals are based on basic science principles that remain largely unchanged, particularly in a mature field like chemical engineering.
A new method developed at Oak Ridge National Laboratory improves the energy efficiency of a desalination process known as solar-thermal evaporation.
A study led by Oak Ridge National Laboratory explored the interface between the Department of Veterans Affairs’ healthcare data system and the data itself to detect the likelihood of errors and designed an auto-surveillance tool