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.

Michael Tillou, a senior buildings research engineer at PNNL, has been honored with an ASHRAE Distinguished Service Award.

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.

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

PNNL researchers deploying and testing novel building technologies and energy-management approaches.

Researchers 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.

The first customized resource of its kind, H-BEST analyzes the indoor environmental quality profile for buildings and helps its users identify the costs and benefits of improvements.

Modeling study suggests vigorous ventilation can cause spike in viral concentrations

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