A team led by ORNL created a computational model of the proteins responsible for the transformation of mercury to toxic methylmercury, marking a step forward in understanding how the reaction occurs and how mercury cycles through the environment.
Oak Ridge National Laboratory scientists evaluating northern peatland responses to environmental change recorded extraordinary fine-root growth with increasing temperatures, indicating that this previously hidden belowground mechanism may play an important role in how carbon-rich peatlands respond to warming.
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.
Joe Hagerman, ORNL research lead for buildings integration and controls, understands the impact building technology innovations can have during times of crisis. Over a decade ago, he found himself in the middle of one of the most devastating natural disasters of the century, Hurricane Katrina.
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.
Oak Ridge National Laboratory researchers have built a novel microscope that provides a “chemical lens” for viewing biological systems including cell membranes and biofilms.
While some of her earth system modeling colleagues at ORNL face challenges such as processor allocation or debugging code, Verity Salmon prepares for mosquito swarms and the possibility of grizzly bears.