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Scientists at ORNL have developed a vacuum-assisted extrusion method that reduces internal porosity by up to 75% in large-scale 3D-printed polymer parts. This new technique addresses the critical issue of porosity in large-scale prints but also paves the way for stronger composites.
By editing the polymers of discarded plastics, ORNL chemists have found a way to generate new macromolecules with more valuable properties than those of the starting material.
The Department of Energy’s Office of Electricity, in partnership with ORNL, has launched an experimental platform for energy sector-related data with enhanced emphasis on governance and usability.
The Advanced Plant Phenotyping Laboratory at ORNL utilizes robotics, multi-modal imaging, and AI to enhance understanding of plant genetics and interactions with microbes. It aims to connect genes to traits for advancements in bioenergy, agriculture, and climate resilience. Senior scientist Larry York highlights the lab's capabilities and the insights from a new digital underground imaging system to improve biomass feedstocks for bioenergy and carbon storage.
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.
Debjani Singh, a senior scientist at ORNL, leads the HydroSource project, which enhances hydropower research by making water data more accessible and useful. With a background in water resources, data science, and earth science, Singh applies innovative tools like AI to advance research. Her career, shaped by her early exposure to science in India, focuses on bridging research with practical applications.
At ORNL, a group of scientists used neutron scattering techniques to investigate a relatively new functional material called a Weyl semimetal. These Weyl fermions move very quickly in a material and can carry electrical charge at room temperature. Scientists think that Weyl semimetals, if used in future electronics, could allow electricity to flow more efficiently and enable more energy-efficient computers and other electronic devices.
The world’s fastest supercomputer helped researchers simulate synthesizing a material harder and tougher than a diamond — or any other substance on Earth. The study used Frontier to predict the likeliest strategy to synthesize such a material, thought to exist so far only within the interiors of giant exoplanets, or planets beyond our solar system.
Two ORNL teams recently completed Cohort 18 of Energy I-Corps, an immersive two-month training program where the scientists define their technology’s value propositions, conduct stakeholder discovery interviews and develop viable market pathways.
Researchers at the Department of Energy’s Oak Ridge National Laboratory and partner institutions have launched a project to develop an innovative suite of tools that will employ machine learning algorithms for more effective cybersecurity analysis of the U.S. power grid.