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Media Contacts
![Veda Galigekere is leading Oak Ridge National Laboratory’s work on fast, efficient, wireless charging of electric vehicles.](/sites/default/files/styles/list_page_thumbnail/public/2019-05/2019-P00214_0.jpg?h=9f7a701f&itok=crDMVmT6)
Galigekere is principal investigator for the breakthrough work in fast, wireless charging of electric vehicles being performed at the National Transportation Research Center at Oak Ridge National Laboratory.
![The researchers used the new model to accurately identify clusters of gene mutations (spheres), which helped them study the emergence of various genetic diseases. Image credit: Ivaylo Ivanov, Georgia State University.](/sites/default/files/styles/list_page_thumbnail/public/2019-05/med-res-image6_3mb-1.png?h=bf86d530&itok=wTUjuyV_)
Environmental conditions, lifestyle choices, chemical exposure, and foodborne and airborne pathogens are among the external factors that can cause disease. In contrast, internal genetic factors can be responsible for the onset and progression of diseases ranging from degenerative neurological disorders to some cancers.
![ORNL staff members (from left) Ashley Shields, Michael Galloway, Ketan Maheshwari and Andrew Miskowiec are collaborating on a project focused on predicting and analyzing crystal structures of new uranium oxide phases. Credit: Jason Richards/ORNL](/sites/default/files/styles/list_page_thumbnail/public/2019-03/teamphotoforhighlight_0.jpg?h=a00326b7&itok=O4yDtVj6)
Scientists at the Department of Energy’s Oak Ridge National Laboratory are working to understand both the complex nature of uranium and the various oxide forms it can take during processing steps that might occur throughout the nuclear fuel cycle.
![Molecular dynamics simulations of the Fs-peptide revealed the presence of at least eight distinct intermediate stages during the process of protein folding. The image depicts a fully folded helix (1), various transitional forms (2–8), and one misfolded state (9). By studying these protein folding pathways, scientists hope to identify underlying factors that affect human health.](/sites/default/files/styles/list_page_thumbnail/public/2019-03/Slide1_0.png?h=c855054e&itok=aNbgxXsc)
Using artificial neural networks designed to emulate the inner workings of the human brain, deep-learning algorithms deftly peruse and analyze large quantities of data. Applying this technique to science problems can help unearth historically elusive solutions.