PNNL evaluates bacterial, fungi, and algae strains as part of a four-step process to streamline and standardize biomanufacturing processing.

PNNL is leading the nation with research addressing urgent needs for reimagining U.S. critical infrastructure against the realities of software-speed attacks and hazards.

PNNL is working with national laboratories and academia to provide electric vehicle manufacturers with batteries that are more reliable, high-performing, safe, and less expensive.

FEMP's operations and maintenance (O&M) resources offer federal agencies technology- and management-focused guidance to improve energy and water efficiency and ensure safer and more reliable operations.

PNNL provides tools and expertise to bring faster, cost-effective catalysts to industry that can be produced at a large scale.

PNNL’s pioneering CETC project with regional universities demonstrates transactive controls among multiple commercial buildings and devices for energy efficiency and grid reliability.

PNNL and their collaborators are investigating combinations of fuels to boost vehicle efficiency, performance, and affordability.

PNNL is leading an effort to reveal the potential of algae for biofuels to replace conventional fuels for transportation.

PNNL is a leader in the integration of aberration-corrected electron microscopy, in-situ techniques, and atom probe tomography to address challenges in nuclear materials, environmental remediation, energy storage, and national security.

By improving the Weather Research and Forecasting (WRF)-Solar model, this project aims to reduce forecast errors, improve sub-grid scale variability estimates, and more accurately estimate forecast uncertainty.

The U.S. Department of Energy-sponsored Internet of Things Upgradeable Lighting Challenge is designed to encourage the widespread adoption of IoT-Upgraded Lighting.

PNNL is one of five national laboratory JCESR -- a bold effort to transform the way we store energy to power vehicles and the electric grid.

PNNL administers two research buoys for the U.S. Department of Energy that allows collection of wind meteorological and oceanographic data off the nation's coasts.

PNNL is leading a consortium that provides funding opportunities to the automotive industry for accelerating new lightweight technologies in on-highway vehicles.

Physics-informed machine learning (PIML) is a modeling approach that harnesses the power of machine learning and big data to improve the understanding of coupled, dynamic systems.

PNNL data scientists and engineers will be presenting at NeurIPS, the Thirty Fourth Conference on Neural Information Processing Systems, and the co-located Women in Machine Learning workshop, WiML.