PNNL researchers have used field campaign data to better understand clouds, aerosols, and the interactions between humans and the atmosphere.

As new paradigms in advanced computing take shape, computational chemistry researchers are finding new ways to solve challenging chemistry problems.

A new AI model developed at PNNL can identify patterns in electron microscope images of materials without requiring human intervention, allowing for more accurate and consistent materials science.

Published in Nature Communications, Increased Asian Aerosols Drive a Slowdown of Atlantic Meridional Overturning Circulation, identifies the role aerosols over Asia is having on the AMOC, a complex system of currents in the Atlantic Ocean.

The Rapid Assessment of Platform Technologies to Expedite Response project aims to prepare against future pandemics.

To overcome high-performance computing bottlenecks, a research team at PNNL proposed using graph theory, a mathematical field that explores relationships and connections between a number, or cluster, of points in a space.

PNNL researchers use machine learning and data analytics to assist with detection of nuclear proliferation and nuclear material trafficking.

Scientists are pioneering approaches in the branch of artificial intelligence known as machine learning to design and train computer software programs that guide the development of new manufacturing processes.

In honor of National Intern Day, PNNL and intern Jonathan Mills were named among the Top 100 in the nation by early-career recruiting firm WayUp.

As wildfires grow increasingly severe, PNNL researchers are working to slow their spread and mitigate their harmful effects.

TransMED analyzes patient data from similar diseases across multiple sources to understand COVID-19 patient outcome risk factors.

PNNL experts perform fundamental climate science work at multiple scales to understand impacts on energy, water, food, and infrastructure systems.

PNNL researchers have uncovered a plant-derived process that leads to the formation of aerosol particles over the Amazon rainforest and potentially other forested parts of the world. 

Artificial intelligence-based decision tool enables grid operators to respond more quickly and effectively to grid emergencies.

PNNL data scientists are refining their artificial intelligence tools with COVID-19 data to advance therapeutics and treatments for a future pandemic.

A Q&A with Lauren Charles, veterinarian and PNNL data scientist, on zoonotic diseases and the role biosurveillance plays in mitigating the growing threat to global health.

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.

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.

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