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

A study raises questions about how far droplets, like those that carry the virus that causes COVID-19, can travel before becoming harmless.

Steven Spurgeon, a materials scientist and microscopy researcher at PNNL, has accepted an affiliate associate professorship at the University of Washington Department of Physics.

PNNL researchers develop software that uses geographical data to build a free, open-source grid reference system to provide a precise system to locate structures.

Researchers have been investigating if machine learning techniques could be used to help create novel beers.

A multi-institutional team has developed a deep learning framework to identify novel molecules as drug candidates.

Human-machine teaming may sound like something from the distant future. In “Human-Machine Teaming: A Vision of Future Law Enforcement” in Domestic Preparedness, Corey Fallon, Kris Cook, and Grant Tietje of PNNL examine this topic.

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

New building energy codes could reduce utility bills by $138 billion and prevent 900 million metric tons of CO2 emissions coming from buildings. Now, they will be easier to adopt.

PNNL is highlighting scientific and technical experts in the national security domain who were recently promoted to scientist and engineer Level 5, one of PNNL’s most senior research roles.

PNNL has received 119 R&D 100 Awards since 1969, when the laboratory began submitting entries in the contest that recognizes top 100 inventions each year.

PNNL will play a key role in advancing Connected Communities made up of efficient homes and buildings that communicate with the grid to produce energy and environmental benefits.

A new model offers more accurate predictions of how intensely hurricanes may strike.

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

PNNL data scientist was invited to give the first big-picture talk about autonomous control systems at the Autonomous Discovery in Science and Engineering Workshop.

A team of PNNL researchers are looking at how to evaluate robustness and accountability, fairness, and transparency of artificial intelligence models used to detect and quantify deceptive content online.

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.

More than 30 PNNL interns contributed to the Airport Risk Assessment Model, a web-based tool that helps airport security stakeholders prioritize resource allocations.

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.

Researchers developed two solutions for air-conditioning—a novel, energy-efficient dehumidification system and a technology to detect refrigerant leaks. Both help increase energy-efficiency and reduce costs.