Of the various methods to store renewable energy, one stands out for holding onto energy for months at a time: storing energy in the chemical bonds of molecules such as hydrogen.
Bojana Ginovska leads a physical biosciences research team headed for PNNL's new Energy Sciences Center. She uses the transformative power of molecular catalysis and enzymes to explore scientific principles.
PNNL's new Hydrogen Energy Storage Evaluation Tool allows users to examine multiple energy delivery pathways and grid applications to maximize benefits.
Federal and industry-matched funding will move 11 PNNL technologies closer to commercialization where they will help bolster U.S. competitiveness.
PNNL researchers are expanding PNNL's operational Rapid Analytics for Disaster Response (RADR) image analytics and modeling suite to predict the path of fires, floods and other natural disasters, giving first responders an upper hand. The suite utilizes a combination of image-capturing technology (satellite, airborne, and drone images), artificial intelligence, and cloud computing, to not only assess damage but predict it as well.
PNNL scientists developed a tiny battery and tag to track younger, smaller species, to evaluate behavior and estimate survival during downstream migration.
PNNL researchers used natural language processing and deep learning techniques to reveal how and why different types of misinformation and disinformation spread across social platforms. Applied to COVID-19, the team found that misinformation intended to influence politics and incite fear spreads fastest.
Researchers will be able to design their own computer accelerators for faster analysis of large datasets
Machine learning techniques are accelerating the development of stronger alloys for power plants, which will yield efficiency, cost, and decarbonization benefits.