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The ORNL-developed AquaBOT measures a range of water quality indicators, providing data for studies focused on clean water and sustainable energy. Credit: Natalie Griffiths/ORNL, U.S. Dept. of Energy

Measuring water quality throughout river networks with precision, speed and at lower cost than traditional methods is now possible with AquaBOT, an aquatic drone developed by Oak Ridge National Laboratory.

Scientists with the Center for Bioenergy Innovation at ORNL highlighted a hybrid approach that uses microbes and catalysis to convert cellulosic biomass into fuels suitable for aviation and other difficult-to-electrify sectors. Credit: ORNL, U.S. Dept. of Energy

The rapid pace of global climate change has added urgency to developing technologies that reduce the carbon footprint of transportation technologies, especially in sectors that are difficult to electrify.

Melissa Cregger

The Center for Bioenergy Innovation at ORNL offers a unique opportunity for early career scientists to conduct groundbreaking research while learning what it takes to manage a large collaborative science center.

Bryan Piatkowski is a Liane Russell Distinguished Fellow at ORNL developing a framework to better understand the genetic underpinnings of desirable plant traits so they may be used to create climate-resilient crops for food, bioenergy and carbon sequestration. Credit: Carlos Jones/ORNL, U.S. Dept of Energy.

Bryan Piatkowski, a Liane Russell Distinguished Fellow in the Biosciences Division at ORNL, is exploring the genetic pathways for traits such as stress tolerance in several plant species important for carbon sequestration

Chunliu Zhuo is a postdoctoral researcher at the University of North Texas BioDiscovery Institute. Credit: University of North Texas

A team of researchers working within the Center for Bioenergy Innovation at ORNL has discovered a pathway to encourage a type of lignin formation in plants that could make the processing of crops grown for products such as sustainable jet fuels easier and less costly.

A new process developed by Oak Ridge National Laboratory leverages deep learning techniques to study cell movements in a simulated environment, guided by simple physics rules similar to video-game play. Credit: MSKCC and UTK

Scientists have developed a novel approach to computationally infer previously undetected behaviors within complex biological environments by analyzing live, time-lapsed images that show the positioning of embryonic cells in C. elegans, or roundworms. Their published methods could be used to reveal hidden biological activity. 

This protein drives key processes for sulfide use in many microorganisms that produce methane, including Thermosipho melanesiensis. Researchers used supercomputing and deep learning tools to predict its structure, which has eluded experimental methods such as crystallography.  Credit: Ada Sedova/ORNL, U.S. Dept. of Energy

A team of scientists led by the Department of Energy’s Oak Ridge National Laboratory and the Georgia Institute of Technology is using supercomputing and revolutionary deep learning tools to predict the structures and roles of thousands of proteins with unknown functions.

ORNL is making underused or inaccessible bioenergy data available to accelerate innovation for the bioeconomy. Credit: Andy Sproles/ORNL, U.S. Dept. of Energy

A research team from Oak Ridge National Laboratory has identified and improved the usability of data that can help accelerate innovation for the growing bioeconomy.