A breakthrough in electron microscopy based on deep learning can automatically visualize and identify areas of interest, helping to speed advances in materials science.

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.

Battery energy storage systems are being proposed in municipalities across the U.S. PNNL researchers can help community planners guide safe siting and operations.

PNNL’s software tool brings together artificial intelligence and satellite imagery to help responders assess damage and take action.

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

PNNL researchers are helping to better define the need for grid energy storage in future clean energy scenarios, as well as working to improve technologies for storing renewable energy so it's available when and where it's needed.

Findings in a new PNNL report show long-duration energy storage will be a necessity in decarbonizing the grid and recommends the planning and procurement process to identify those needs start immediately.

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.

Artificial intelligence may help humans and computers work together to monitor materials that could be used to make weapons.

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.

Focused research studies of advanced algorithms and materials are setting the stage for the next generation of quantum computers.

COVID-19 changed when and where we use electricity. Researchers showed that commonly available total demand data masked the actual changes.

With an eye on renewable, accessible, and resilient power, PNNL researchers show hyper-local microgrids are a viable option, if designed with the right mix of sources.

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