This study used historical data, remote sensing, and aquatic sensors to measure how far wildfire impacts propagated through the watershed after the 2022 Hermit’s Peak/Calf Canyon fire, New Mexico’s largest wildfire in history.
The Coastal Observations, Mechanisms, and Predictions Across Systems and Scales: Field, Measurements, and Experiments project established a network of observational field sites across Chesapeake Bay and western Lake Erie.
PNNL researchers have published their paper, “Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data,” in the Journal of Proteome Research.
The Center for Continuum Computing at PNNL aims to integrate cloud platforms, high-performance computing, and edge devices into a seamless ecosystem that accelerates scientific discovery.
John VerWey, an advisor in the Mission Alignment group at PNNL, has recently been selected to lead a panel discussion at the inaugural Special Competitive Studies Project (SCSP) AI+ Compute & Connectivity Summit.
Jingshan Du, a postdoctoral scientist at PNNL whose research focuses on crystallization pathways of water and other materials, was named a 2025 CAS Future Leader.
PNNL's “co-scientist” serves as a one-stop AI shop for accelerating scientific discovery. By leveraging AI agents, researchers can explore scientific databases, conduct analyses and request step-by-step plans for testing their hypotheses.
Machine learning and autonomous experimentation are poised to revolutionize how scientists grow very thin films on surfaces, important for technologies like microelectronics and quantum computing.
By combining computational modeling with experimental research, scientists identified a promising composition that reduces the need for a critical material in an alloy that can withstand extreme environments.
