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.

Cyber, physical, and blended cyber-physical threats are real, ubiquitous, and expensive to deal with. Private companies, government institutions, and critical infrastructures struggle to implement viable solutions as technology evolves.

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.

Scientific and technological advancements to safely and permanently store CO2

The Interfacial Dynamics in Radioactive Environments and Materials (IDREAM) Energy Frontier Research Center (EFRC) conducts fundamental science to support innovations in retrieving and processing high-level radioactive waste.

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 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 designs, delivers, and manages training programs that enable partners worldwide to understand their individual or organizational roles and responsibilities, fulfill a job function, or strengthen a particular skill set.

The Pacific Northwest Advanced Compound Identification Center (PNACIC) brings together innovations in integrated chemistry and advanced instrumentation to create a platform for comprehensive, unambiguous identification of metabolites.

Advancing our understanding of how soil microbial communities respond to--and affect--changing environmental conditions

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.

The Suite Of Comprehensive Rapid Analysis Tools for Environmental Sites online tools provide rapid data analytics and visualization of environmental data supporting remedy decisions, optimization, and exit strategies.