Data-driven autonomous technology to rapidly design and deliver antiviral interventions targeting SARS-CoV-2 to reduce drug discovery timeline and advance bio preparedness capabilities.
Data scientist Jung Lee accepted the position of review editor for Frontiers in Computational Neuroscience after serving as a guest editor for a special issue.
A team from the Environmental Molecular Sciences Laboratory published research, demonstrating that the soil microbes were directly involved in the stabilization of soil organic carbon and mineral weathering.
The work by the team at PNNL takes a critical step in leveraging ML to accelerate advanced manufacturing R&D, specifically for manufacturing techniques without access to efficient, first-principles simulations.
PNNL scientists carve a path to profit from carbon capture by creating a system that efficiently captures CO2 and converts it into one of the world’s most widely used chemicals: methanol.
PNNL mathematician Aaron Luttman contributed to the organizing committee for workshop exploring robust machine learning and artificial intelligence systems for the U.S. Army.
The Joint Appointment program at PNNL is one of the most diverse among other U.S. national laboratories, involving nearly 60 universities and research institutions in the United States and abroad.
A review article led by researcher Jade Holliman explores the different classes of metamaterials, from the underlying fundamental science to potential applications.
Steven Spurgeon’s research is featured in the cover of the MRS Bulletin along with his team’s invited perspective on the future of machine learning for electron and scanning probe microscopy.
To thwart pathogens, researchers in the epidemiology field of infectious disease (ID) prediction are continuously trying to forecast when, where, and how an ID event will occur.
A PNNL team developed and used a model framework to understand the performance and structural reliability of a state-of-the-art solid oxide electrolysis cell design.
As leaders in AI and machine learning, PNNL experts are sharing their latest findings at the 36th annual Neural Information Processing Systems (NeurIPS) Conference, Nov. 28–Dec. 9, 2022.
PNNL gathered researchers from eight national laboratories plus the U.S. Department of Energy (DOE) to share ideas and build synergy at the Energy Equity and Environmental Justice Summit.
