The Washington State Academy of Sciences added six people from PNNL to its 2022 class of inductees.

Journal article on novel approach to characterizing particles selected by Spectrochimica Acta Part B as the best paper published during 2021.

PNNL researchers developed a hybrid quantum-classical approach for coupled-cluster Green’s function theory that maintains accuracy while cutting computational costs.

PNNL researchers created a model that helps materials scientists not only predict what is, but what could be.

PNNL researchers design an artificial intelligence-guided electron microscope in a Laboratory Directed Research and Development study.

Xantheas awarded a visiting fellowship from the International Center for Advanced Studies of Energy Conversion in Germany.

Arun Veeramany furthers the field of risk, reliability, and resilience in civil and mechanical engineering in his new role as an American Society of Civil Engineers-American Society of Mechanical Engineers journal editorial board member.

In an invited review article, PNNL researchers examined the literature surrounding modeling and measuring the ice-nucleating particles that help form clouds.

PNNL mathematicians and data scientists had a strong presence at the 2022 Joint Mathematics Meetings as event organizers and speakers.

A novel database of tracked deep convective storms reveals how environmental factors affect storm formation and growth in South America.

Investigating cloud condensation nuclei activities in various airmasses enabled linking activity variations with organic oxidation levels and volatility

New study investigates how to use a non-toxic condensation particle counter for airborne atmospheric research

New college-to-career program provides students a direct pathway to cybersecurity careers at U.S. Space Force's Space Systems Command.

A new capability facilitates source apportionment of organic aerosols in real time.

The COVID-19 pandemic massively disrupted human activities, which caused additional turmoil through regional record rainfall and floods.

Measuring the ice nucleation activity of particles in the ambient atmosphere can help develop better representations for use in climate models.

PNNL contributes to 30 years of data on clouds, radiation, and other climate-making factors as part of field campaigns and analysis conducted by DOE's Atmospheric Radiation Measurement user facility.

Parallel graph neural networks identify protein-ligand 3-D structural interactions to aid in protein function prediction and drug discovery.

Researchers use machine learning to speed up the analysis of aerosol datasets from mass spectrometry.

Amelia Hough-Ross, an IT engineer in Research Computing at PNNL, will be presenting at the Wonder Women Tech Ignite Virtual Summit on May 4-5, 2022.