Tennessee State University received Department of Energy funding to establish an academy focused on preparing students and professionals to work in an emerging field: clean energy systems. PNNL is helping with that effort and others.

Researchers from PNNL have been assessing installation and use of electric heat pumps in an Alaskan community that relies on fuel oil for heat. The resulting information could advance electrification in cold rural areas across the nation.

PNNL researchers are working to provide the technical assistance and expertise needed for communities to shape their clean energy future.

In a new approach, quantum flow algorithms are used to simulate many-body systems on quantum computers and effectively describe chemical processes.

PNNL chief scientist and joint appointee Auroop Ganguly was recently appointed a Distinguished Member of the Association for Computing Machinery, a high honor from the world's largest computer science society.

Samantha Erwin, a PNNL data scientist, was recently appointed to the Society for Industrial and Applied Mathematics Membership Committee.

PNNL helps deliver efficiency-related rules and requirements that steadily improve performance of America’s buildings, saving energy and costs and reducing carbon emissions.

Brett Jefferson, data scientist, was recently recognized for his determination and success in his research space with an Early Career Award from Indiana University Bloomington in the Psychological and Brain Sciences Department.

The convergence of artificial intelligence, cloud, and high-performance computing to accelerate scientific discovery is the focus of a multi-year collaboration between Microsoft and PNNL.

PNNL researchers comment on the “Adversarial Machine Learning” white paper from the National Institute of Standards and Technology.

Mandy Mahoney, director of the DOE Building Technologies Office, visited PNNL in late November. One key agenda item involved meeting with staff for a discussion of effective equity and justice integration in buildings-related research.

PNNL has created the Center for AI @PNNL to coordinate the pioneering research of hundreds of scientists working on a range of projects in artificial intelligence.

PNNL is one of the founding partners of the Trillion Parameter Consortium, which was formed to create reliable generative AI models.

Input from humans helps when deciding whether to trust the recommendations or decisions of a machine-learning system.

PNNL’s DataLife tool analyzes and identifies bottlenecks in scientific workflows.

The use of disciplines in pure mathematics can increase the reliability and explainability of machine learning models that “transcend human intuition,” according to PNNL scientists.

A larger HVAC workforce with training on modern heat pump technology will be pivotal to achieving the mass-scale electrification of household HVAC systems needed to meet building decarbonization goals.

Leaders from the DOE Office of Energy Efficiency and Renewable Energy visited PNNL October 19–20 for a firsthand look at capabilities and research progress.

PNNL’s Andrea Mengual co-chaired a working group that produced Building Performance Standards: A Technical Resource Guide. PNNL’s Kim Cheslak, Bing Liu, and Jian Zhang contributed to the effort.

PNNL is at the midpoint of a study focused on the installation of electric heat pump water heaters in New Orleans homes. The efficient water heaters offer a unique capability that could help speed the transition from fossil fuels.