Driving Machine Learning to Exascale
Through her role in the Department of Energy’s Advanced Scientific Computing Research-supported ExaLearn project, Jenna Pope is developing deep learning approaches for finding optimal water cluster structures for a variety of applications.
Carving Out Quantum Space
The race toward the first practical quantum computer is in full stride. Scientists at PNNL are bridging the gap between today’s fastest computers and tomorrow’s even faster quantum computers.
Advantage: Water
When water comes in for a landing on the common catalyst titanium oxide, it splits into hydroxyls just under half the time. Water's oxygen and hydrogen atoms shift back and forth between existing as water or hydroxyls, and water has the sli
Google It: Quantum Chemistry Problem Solved
PNNL quantum computing pioneer Nathan Wiebe contributed to a Google-led quantum computing landmark study published in the journal Science.
Opening the Black Box of Neural Networks
Pacific Northwest National Laboratory researchers used machine learning to explore the largest water clusters database, identifying—with the most accurate neural network—important information about this life-essential molecule.
Cloud Computing Captures Chemistry Code
The speed and agility of cloud computing opens doors to completing advanced computational chemistry workflows in days instead of months.
Exploring Energy Efficiency through Analog Computing
Researchers discussed this topic at the 2024 Analog Computing for Science Workshop co-led by Antonino Tumeo.
Collaboration Speeds Complex Chemical Modeling
Calculating quantum chemistry quickly allows scientists to refine their understanding of complex chemical systems.
PNNL Scientists Tap Nation’s Fastest Computers to Explore Critical Science Questions
Researchers will explore climate, pathogens and energy-efficient microelectronics using 3 million node hours on the nation’s supercomputers.