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Man in blue shirt and grey pants holds laptop and poses next to a green plant in a lab.

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.

Red background fading into black from top to bottom. Over top the background are 20 individual rectangles lined up in three rows horizontally with a red and blue line moving through it.

ORNL scientists develop a sample holder that tumbles powdered photochemical materials within a neutron beamline exposing more of the material to light for increased photo-activation and better photochemistry data capture.

A tan and black cylinder that is made up of three long tubes vertically with a black line horizontally going across the bottom and the top. There is a piece laying on the floor that says ORNL.

ORNL researchers used electron-beam additive manufacturing to 3D-print the first complex, defect-free tungsten parts with complex geometries. 

Alyssa Carrell is an ORNL ecologist studying how plant-microbe relationships can build resilience in natural ecosystems vulnerable to climate change. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Alyssa Carrell started her science career studying the tallest inhabitants in the forest, but today is focused on some of its smallest — the microbial organisms that play an outsized role in plant health. 

New system combines human, artificial intelligence to improve experimentation

To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance. 

Chelsea Chen, polymer physicist at ORNL, stands in front of an eight-channel potentiostat and temperature chamber used for battery and electrochemical testing. Credit: Genevieve Martin/ORNL, U.S. Dept. of Energy

Chelsea Chen, a polymer physicist at ORNL, is studying ion transport in solid electrolytes that could help electric vehicle battery charges last longer.

: ORNL climate modeling expertise contributed to an AI-backed model that assesses global emissions of ammonia from croplands now and in a warmer future, while identifying mitigation strategies. This map highlights croplands around the world. Credit: U.S. Geological Survey

ORNL climate modeling expertise contributed to a project that assessed global emissions of ammonia from croplands now and in a warmer future, while also identifying solutions tuned to local growing conditions.

Alex May, pictured above, is the first and only full-time data curator at the Department of Energy’s Oak Ridge Leadership Computing Facility. Credit: Carlos Jones and Wikimedia Commons, background/ORNL, U.S. Dept. of Energy
Alex May is the first and only full-time data curator at the Department of Energy’s Oak Ridge Leadership Computing Facility, evaluating datasets developed by computational scientists before they are made public through the OLCF’s Constellation portal for open data exchange.
Mirko Musa was always fascinated by the power of rivers, specifically how these mighty waterways sculpt landscapes. Now, as a water power researcher, he’s finding ways to harness that power and protect rivers at the same time. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy

Mirko Musa spent his childhood zigzagging his bike along the Po River. The Po, Italy’s longest river, cuts through a lush valley of grain and vegetable fields, which look like a green and gold ocean spreading out from the river’s banks. 

ORNL and Enginuity researchers proved that a micro combined heat and power prototype, or mCHP, with an opposed piston engine can achieve more than 93% overall energy efficiency. The environmentally friendly mCHP can replace a back-up generator or traditional hot water heater. Credit: ORNL, U.S. Department of Energy

ORNL researchers, in collaboration with Enginuity Power Systems, demonstrated that a micro combined heat and power prototype, or mCHP, with a piston engine can achieve an overall energy efficiency greater than 93%.