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.

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

PNNL scientists investigate the promising properties of a common, Earth-abundant salt.

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.

Lighting control data are critical for optimizing the design and operation of future lighting systems for the benefit of occupants and energy efficiency.

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

DOE Integrated Lighting Campaign organizers introduce new recognition categories in horticulture, innovative financing, and energy equity.

Johannes Lercher, Battelle Fellow and director of the PNNL Institute for Integrated Catalysis, envisions energy storage solutions at the new Energy Sciences Center.

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

PNNL researchers are studying catalysts that are key to dealing with waste and producing sustainable energy.

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’s new Hydrogen Energy Storage Evaluation Tool allows users to examine multiple energy delivery pathways and grid applications to maximize benefits.