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Media Contacts
![DOE national laboratory scientists led by Oak Ridge National Laboratory have developed the first tree dataset of its kind, bridging molecular information about the poplar tree microbiome to ecosystem-level processes. Credit: Andy Sproles, ORNL/U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-04/plantTreeMicrobe04%20%281%29.jpg?h=55e40f5b&itok=OkZsQvEv)
A first-ever dataset bridging molecular information about the poplar tree microbiome to ecosystem-level processes has been released by a team of DOE scientists led by ORNL. The project aims to inform research regarding how natural systems function, their vulnerability to a changing climate and ultimately how plants might be engineered for better performance as sources of bioenergy and natural carbon storage.
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.
![ORNL’s Kate Evans has been awarded the 2024 Society for Industrial and Applied Mathematicians Activity Group on Mathematics of Planet Earth Prize.](/sites/default/files/styles/list_page_thumbnail/public/2024-03/Evans_SIAM.jpg?h=c6980913&itok=2lgbSBjY)
Kate Evans, director for the Computational Sciences and Engineering Division at ORNL, has been awarded the 2024 Society for Industrial and Applied Mathematicians Activity Group on Mathematics of Planet Earth Prize.
![Anuj Kapadia](/sites/default/files/styles/list_page_thumbnail/public/2024-03/kapadia.jpg?h=8f9cfe54&itok=M4gtR_dd)
Anuj J. Kapadia, who heads the Advanced Computing Methods for Health Sciences Section at ORNL, has been elected as president of the Southeastern Chapter of the American Association of Physicists in Medicine.
![New system combines human, artificial intelligence to improve experimentation](/sites/default/files/styles/list_page_thumbnail/public/2024-02/Screenshot%202024-02-14%20at%2011.37.46%20AM%20%281%29.png?h=e621a1e2&itok=N3lsBqrh)
To capitalize on AI and researcher strengths, scientists developed a human-AI collaboration recommender system for improved experimentation performance.
![Moriano awarded early career fellowship for underrepresented groups](/sites/default/files/styles/list_page_thumbnail/public/2024-02/Pablo-Moriano-Pic.jpg?h=4d38fa4a&itok=QTrNiMK-)
Pablo Moriano, a research scientist in the Computer Science and Mathematics Division at ORNL, was selected as a member of the 2024 Class of MGB-SIAM Early Career Fellows.
![: 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.
![Using a better modeling framework, with data collected from Mississippi Delta marshes, scientists are able to improve the predictions of methane and other greenhouse gas emissions. Credit: Matthew Berens/ORNL, U.S Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/picture1_0.jpg?itok=uQVJerN0)
Scientists at the Department of Energy’s Oak Ridge National Laboratory are using a new modeling framework in conjunction with data collected from marshes in the Mississippi Delta to improve predictions of climate-warming methane and nitrous oxide.
![ORNL Associate Laboratory Director for Computing and Computational Sciences. Credit: Carlos Jones/ORNL, U.S. Dept. of Energy](/sites/default/files/styles/list_page_thumbnail/public/2024-01/tourassi.jpg?h=55be468c&itok=AvEfpuPK)
Gina Tourassi, associate laboratory director for computing and computational sciences at the US Department of Energy’s (DOE’s) Oak Ridge National Laboratory, has been named a fellow of the Institute of Electrical and Electronics Engineers, the world’s largest organization for technical professionals.
A team from DOE’s Oak Ridge, Los Alamos and Sandia National Laboratories has developed a new solver algorithm that reduces the total run time of the Model for Prediction Across Scales-Ocean, or MPAS-Ocean, E3SM’s ocean circulation model, by 45%.