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A Co-Optima research team led by Oak Ridge National Laboratory’s Jim Szybist in collaboration with Argonne, Sandia and the National Renewable Energy Laboratory, created a merit function tool that evaluates six fuel properties and their impact on engine performance, giving the scientific community a guide to quickly evaluate biofuels. Credit: ORNL/U.S. Dept. of Energy

As ORNL’s fuel properties technical lead for the U.S. Department of Energy’s Co-Optimization of Fuel and Engines, or Co-Optima, initiative, Jim Szybist has been on a quest for the past few years to identify the most significant indicators for predicting how a fuel will perform in engines designed for light-duty vehicles such as passenger cars and pickup trucks.

Suman Debnath is using simulation algorithms to accelerate understanding of the modern power grid and enhance its reliability and resilience. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Planning for a digitized, sustainable smart power grid is a challenge to which Suman Debnath is using not only his own applied mathematics expertise, but also the wider communal knowledge made possible by his revival of a local chapter of the IEEE professional society.

Paul Abraham uses mass spectrometry to study proteins.

Systems biologist Paul Abraham uses his fascination with proteins, the molecular machines of nature, to explore new ways to engineer more productive ecosystems and hardier bioenergy crops.

Unique imaging capabilities yield new knowledge, growth for bioeconomy

Scientists at the Department of Energy’s Oak Ridge National Laboratory have a powerful new tool in the quest to produce better plants for biofuels, bioproducts and agriculture.

SPRUCE experiment

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.

ORNL’s Lab-on-a-crystal uses machine learning to correlate materials’ mechanical, optical and electrical responses to dynamic environments. Credit: Ilia Ivanov/ORNL, U.S. Dept. of Energy

An all-in-one experimental platform developed at Oak Ridge National Laboratory’s Center for Nanophase Materials Sciences accelerates research on promising materials for future technologies.

The hybrid inverter developed by ORNL is an intelligent power electronic inverter platform that can connect locally sited energy resources such as solar panels, energy storage and electric vehicles and interact efficiently with the utility power grid. Credit: Carlos Jones, ORNL/U.S. Dept of Energy.

ORNL researchers have developed an intelligent power electronic inverter platform that can connect locally sited energy resources such as solar panels, energy storage and electric vehicles and smoothly interact with the utility power grid.

The CrossVis application includes a parallel coordinates plot (left), a tiled image view (right) and other interactive data views. Credit: Chad Steed/Oak Ridge National Laboratory, U.S. Dept. of Energy

From materials science and earth system modeling to quantum information science and cybersecurity, experts in many fields run simulations and conduct experiments to collect the abundance of data necessary for scientific progress.

Map with focus on sub-saharan Africa

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.

Eriophorum vaginatum flourishes in the tundra biome

An international team of scientists found that rules governing plant growth hold true even at the edges of the world in the Arctic tundra.