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Robert “Bob” Hettich, an ORNL Corporate Fellow, is a pioneer in using mass spectrometry to uncover how microbes interact within complex environments and influence larger systems like plants and humans. A founder of the field of metaproteomics, he leads research that supports bioenergy, environmental resilience and health through advanced protein analysis.
Neus Domingo Marimon, leader of the Functional Atomic Force Microscopy group at the Center for Nanophase Materials Sciences of ORNL, has been elevated to senior member of the Institute of Electrical and Electronics Engineers.
P&G is using simulations on the ORNL Summit supercomputer to study how surfactants in cleaners cause eye irritation. By modeling the corneal epithelium, P&G aims to develop safer, concentrated cleaning products that meet performance and safety standards while supporting sustainability goals.
Speakers, scientific workshops, speed networking, a student poster showcase and more energized the Annual User Meeting of the Department of Energy’s Center for Nanophase Materials Sciences, or CNMS, Aug. 7-10, near Market Square in downtown Knoxville, Tennessee.
Madhavi Martin brings a physicist’s tools and perspective to biological and environmental research at the Department of Energy’s 91°µÍř, supporting advances in bioenergy, soil carbon storage and environmental monitoring, and even helping solve a murder mystery.
Technologies developed by researchers at ORNL have received six 2023 R&D 100 Awards.
Scientist-inventors from ORNL will present seven new technologies during the Technology Innovation Showcase on Friday, July 14, from 8 a.m.–4 p.m. at the Joint Institute for Computational Sciences on ORNL’s campus.
Nature-based solutions are an effective tool to combat climate change triggered by rising carbon emissions, whether it’s by clearing the skies with bio-based aviation fuels or boosting natural carbon sinks.
Andrew Lupini, a scientist and inventor at ORNL, has been elected Fellow of the Microscopy Society of America.
Researchers at ORNL have developed a machine-learning inspired software package that provides end-to-end image analysis of electron and scanning probe microscopy images.