PNNL researchers continue to deliver high-quality, high-impact research on radioactive waste and nuclear materials management, earning “Papers of Note” and “Superior Paper” awards.
Four engineers at PNNL received awards for nuclear science presentations related to Hanford Site cleanup at the annual meeting of the world's leading organization for chemical engineering professionals.
International compliance analyst Madalina Man highlighted the history of international safeguards on a podcast by the United Arab Emirates Federal Authority for Nuclear Regulation.
PNNL postdoc Pengfei Shi won first place in the Early Career Researcher Poster Competition at the recently concluded NOAA Subseasonal and Seasonal Applications Workshop.
Data-gathering instruments will be positioned on commercial, ocean-going ships in a Department of Energy-funded project that is expected to improve understanding of marine atmosphere and aerosol–cloud interactions.
PNNL researchers earned five Papers of Note, 17 Superior Papers, and one poster award for their environmental remediation, radioactive waste, and nuclear energy-related presentations.
At the National Homeland Security Conference, researchers shared how partnerships and emerging technologies like artificial intelligence can play a key role in emergency management preparedness and response.
Kriston Brooks received the 2023 Department of Energy Office of Classification Outstanding DC Award, which is given to those in the classification community who have made significant contributions.
The Health Physics Society has selected Jonathan Napier, a PNNL environmental health physicist, to serve as a delegate to the International Radiation Protection Association’s General Assembly.
PNNL’s Chris Chini has been named a guest editor of Environmental Research: Infrastructure and Sustainability’s special issue examining energy infrastructure vulnerabilities from physical and natural threats.
A 19-person, multi-institutional national laboratory team received the inaugural Gordon Bell Prize for Climate Modeling from the Association for Computing Machinery for their work on more accurately modeling deep convective clouds.