More than 30 PNNL interns contributed to the Airport Risk Assessment Model, a web-based tool that helps airport security stakeholders prioritize resource allocations.

The web-based tool, called PLATIPUS, is publicly available and interacts with publications available in the CovidScholar database.

PNNL’s data-infused approach to electron microscopes’ use in scientific experimentation will help researchers and industry interpret large data streams and drive down costs.

The U.S. Department of Energy has selected the Scalable Predictive Methods for Excitations and Correlated Phenomena project to receive funding to develop software for chemical research.

PNNL researcher Erol Cromwell uses neural networks to elucidate subsurface permeability.

Research into practical systems for chemical energy storage will be a focus at the Energy Sciences Center.

The Washington State Academy of Sciences consists of more than 300 elected members who are nationally recognized for their scientific and technical expertise.

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 computational scientist Diana Bacon’s role as carbon storage associate editor uses her expertise in subsurface modeling and quantitative risk assessment.

Seeking a deeper understanding of when, where, and why large wildfires occur using explainable artificial intelligence.

Rising greenhouse gases and declining aerosols have triggered an approximate four-day delay in rainfall over tropical land and the Sahel.

PNNL combines AI and cloud computing with damage assessment tool to predict path of wildfires and quickly evaluate the impact of natural disasters, giving first responders an upper hand.

At PNNL, women in engineering tackle some of the world’s most complex problems in environmental science, sustainable energy, and national security.

Svitlana Volkova uses natural language processing and AI to reveal how misinformation and disinformation spread through social media.

Researchers to design their own computer accelerators for faster analysis of large datasets.

PNNL provided ultra-low measurements of argon-39 to date groundwater as part of a collaborative study of the aquifer in California’s San Joaquin Valley. PNNL is one of only a few laboratories worldwide with this capability.

Machine learning techniques are accelerating the development of stronger alloys for power plants, which will yield efficiency, cost, and decarbonization benefits.

OpenCGRA expedites the design-prototype cycle of computer architecture development.

PNNL is lending analytics expertise to a new first-of-its-kind electric-vehicle carsharing program being launched in Hood River, Oregon.

New research aids the design of more efficient water purification technologies.