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ORNL scientists have determined how to avoid costly and potentially irreparable damage to large metallic parts fabricated through additive manufacturing, also known as 3D printing, that is caused by residual stress in the material.
![ORNL engineer Canan Karakaya uses computational modeling to design and improve chemical reactors and how they are operated to convert methane, carbon dioxide, ammonia or ethanol into higher-value chemicals or energy-dense fuels. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-03/2024-P03340.jpg?h=e6a52188&itok=crvddM9b)
Canan Karakaya, a R&D Staff member in the Chemical Process Scale-Up group at ORNL, was inspired to become a chemical engineer after she experienced a magical transformation that turned ammonia gas into ammonium nitrate, turning a liquid into white flakes gently floating through the air.
The United States could triple its current bioeconomy by producing more than 1 billion tons per year of plant-based biomass for renewable fuels, while meeting projected demands for food, feed, fiber, conventional forest products and exports, according to the DOE’s latest Billion-Ton Report led by ORNL.
![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](/sites/default/files/styles/list_page_thumbnail/public/2024-02/2023-P19202.jpg?h=c6980913&itok=Q-GNSOOO)
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](/sites/default/files/styles/list_page_thumbnail/public/2024-02/global_croplands_usgs_globe-4g_1.png?h=4016a495&itok=rb8eHyvK)
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.
![Prasad Kandula builds a medium-voltage solid state circuit breaker as part of ORNL’s project to develop medium-voltage power electronics in GRID-C. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/2023-p19949.jpg?h=036a71b7&itok=hk4ue1hl)
Scientists at ORNL are looking for a happy medium to enable the grid of the future, filling a gap between high and low voltages for power electronics technology that underpins the modern U.S. electric grid.
![Researchers at Corning have found that understanding the stability of the rings of atoms in glass materials can help predict the performance of glass products.](/sites/default/files/styles/list_page_thumbnail/public/2024-01/picture2.png?h=342db57d&itok=yUdVp1Za)
Corning uses neutron scattering to study the stability of different types of glass. Recently, researchers for the company have found that understanding the stability of the rings of atoms in glass materials can help predict the performance of glass products.
![Wire arc additive manufacturing allowed this robot arm at ORNL to transform metal wire into a complete steam turbine blade like those used in power plants. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2023-12/2023-P05157.jpg?h=036a71b7&itok=LKO4fsAu)
Researchers at ORNL became the first to 3D-print large rotating steam turbine blades for generating energy in power plants.
![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](/sites/default/files/styles/list_page_thumbnail/public/2023-12/2023-P18433%20%281%29_0.jpg?h=8f9cfe54&itok=DQKdmnrN)
![The AI agent, incorporating a language model-based molecular generator and a graph neural network-based molecular property predictor, processes a set of user-provided molecules (green) and produces/suggests new molecules (red) with desired chemical/physical properties (i.e. excitation energy). Image credit: Pilsun You, Jason Smith/ORNL, U.S. DOE](/sites/default/files/styles/list_page_thumbnail/public/2023-12/image001_0.png?h=16ec4b77&itok=KtCjteSq)
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.