The ARPA-E Energy Innovation Summit brings together researchers, industry leaders, entrepreneurs, and investors to showcase the latest technologies shaping tomorrow’s energy landscape. This year, eight projects led by PNNL were featured.
A team from PNNL contributed several articles to the Domestic Preparedness Journal showcasing recent efforts to explore the emergency management and artificial intelligence research and development landscape.
Seawater threatens to intrude into coastal freshwater aquifers that millions of people depend on for drinking water and irrigation. This study investigates sea-level rise impacts on the global coastal groundwater table.
New datasets delineating global urban land support scientific research, application, and policy, but they can produce different results when applied to the same problem making it difficult for researchers to decide which to use.
A team of researchers recently coordinated a series of international workshops aimed at enhancing chemical research security and fostering collaboration among scientists and academic researchers from both countries.
PNNL will analyze current and projected transportation fuel dynamics, supply chain risks, and risk comparators with relevant sectors, such as transportation electrification.
A recent paper published in Science sheds light on how aerosols—tiny particles in the air—released by industrial activities can trigger downstream snowfall events.
After 20 years of contributions to the field of hydrogen safety, the Hydrogen Safety Panel launched its new mentoring program at PNNL earlier this year. Now, the program has selected its first two mentees.
Through a detailed examination of historical data supported by mechanistic analysis and model experiments, researchers unveil that a large-scale climate system intensifies heat extremes and wildfire risks in the PNW.
This study shows that dry dynamics alone is not enough to understand jet stream persistence. Instead, clouds and precipitation are more important contributors than internal “dry” mechanisms to this memory of the Southern Hemisphere jet.
Over the past three years, PNNL’s Know Your Collaborator (KYC) workshop series has engaged hundreds of academic partners and institutional researchers internationally on the topic of research security.
PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.
This study provides a comprehensive analysis of isolated deep convection & mesoscale convective systems using self-organizing maps to categorize large-scale meteorological patterns and a tracking algorithm to monitor their life cycle.
This study explored the future effects of climate change and low-carbon energy transition (i.e., emission reduction) on Arctic offshore oil and gas production.
