The Institute for Integrated Catalysis (IIC) at Pacific Northwest National Laboratory explores and develops the chemistry and technology of catalyzed processes that enable a carbon-neutral future.

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

PNNL is heavily engaged in the development and use of mass spectrometry technology across its science, energy, and security missions, from fundamental research through mature operational capabilities.

PNNL is a leader in multiple areas of shore power and port electrification research related to maritime ports, inland ports, and airports.

This report reviews the current state of the North American lithium battery materials market and will be updated periodically as the industry evolves.

Pacific Northwest National Laboratory supports innovations in data analytics, instrumentation, and experimental techniques for the Northwest (NW) Biopreparedness Research Virtual Environment (BRaVE) Initiative.

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.

PNNL computer scientists are presenting the latest research in HPC at SC20.

RadAnalysis is a software developed by the Department of Energy to assist in the packaging and transportation of radioactive materials. It facilitates compliance with regulations, providing consistency, accuracy, and relevant documentation.

PNNL combines AI and cloud computing with damage assessment tools to predict the path of wildfires and quickly evaluate the impact of natural disasters, giving first responders an upper hand.

National laboratories, industry and academia are collaborating to provide electric vehicle manufacturers with batteries that are more reliable, high-performing, safe, and less expensive.

PNNL has developed a tool suite of interactive analytics that can be rapidly integrated into analyst workflows to empirically analyze and gain qualitative understanding of AI model performance jointly across dimensions.

The Water cycle: Modeling of Circulation, Convection, and Earth system Mechanisms (WACCEM) Scientific Focus Area advances predictive understanding of water cycle variability and change.