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.

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

Cyber networks are constantly under attack by bugs, bots, and nefarious actors. While system owners acutely understand the need to secure their networks, they’re not always sure of the best actions to take.

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 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.

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.

Our nation’s critical infrastructure supports the security and wellbeing of our society. Maintaining the resilience of important markets and services is vital to upholding our way of life.  

PNNL is working on behalf of the U.S. Department of Energy to create a prototype system that enables homes to help provide services to the power grid while delivering economic benefits to residents.

A software suite for working with neutron activation rates measured in a nuclear fission reactor, an accelerator-based neutron source, or any neutron field to determine the neutron flux spectrum using a generalized least-squares approach.

Visual Sample Plan (VSP) is a software tool that supports the development of a defensible sampling plan based on statistical sampling theory and the statistical analysis of sample results to support confident decision making.

PNNL develops training, exercises, and assessments to prepare and equip border security officers to detect, identify, and interdict the illicit movements of materials, commodities, and components associated with WMD.