Quantum precision reached in modeling molten salt behavior
From decoding plant genomes to modeling microbial behavior, computational biologist Priya Ranjan builds computational tools that turn extensive biological datasets into real-world insights. These tools transform the way scientists ask and answer complex biological questions that advance biotechnology breakthroughs and support cultivation of better crops for energy and food security.
A new Global Biomass Resource Assessment developed by ORNL scientists gathered data from 55 countries resulting in a first-of-its kind compilation of current and future sustainable biomass supply estimates around the world.
Researchers at Oak Ridge National Laboratory have developed free data sets to estimate how much energy any building in the contiguous U.S. will use in 2100. These data sets provide planners a way to anticipate future energy needs as the climate changes.
John Lagergren, a staff scientist in Oak Ridge National Laboratory’s Plant Systems Biology group, is using his expertise in applied math and machine learning to develop neural networks to quickly analyze the vast amounts of data on plant traits amassed at ORNL’s Advanced Plant Phenotyping Laboratory.
A team of computational scientists at ORNL has generated and released datasets of unprecedented scale that provide the ultraviolet visible spectral properties of over 10 million organic molecules.
Walters is working with a team of geographers, linguists, economists, data scientists and software engineers to apply cultural knowledge and patterns to open-source data in an effort to document and report patterns of human movement through previously unstudied spaces.
Long before COVID-19’s rapid transmission led to a worldwide pandemic, Oak Ridge National Laboratory’s Jason DeGraw was performing computer modeling to better understand the impact of virus-laden droplets on indoor air quality