EZBattery Model allows energy storage researchers to more quickly and easily identify the best performing battery designs without the need for extensive physical prototyping or computationally expensive simulations.
Global experts gathered at PNNL for the 9th International Conference on Sodium Batteries, sharing advancements in sodium battery research and development.
The Sodium-ion Alliance for Grid Energy Storage, led by PNNL, is focused on demonstrating high-performance, low-cost, safe sodium-ion batteries tested for real-world grid applications.
The Grid Storage Launchpad dedication event was attended by leaders in grid and transportation energy storage, battery innovation, and industry stakeholders working to transform America’s energy system.
Erich Hsieh, Deputy Assistant Secretary for OE’s Energy Storage Division, shared insights about the Grid Storage Launchpad and energy storage innovations .
In the latest issue of the Domestic Preparedness Journal, Ashley Bradley and Kristin Omberg share how new research is shedding light on the scientific and technological challenges with detecting fentanyl.
Research at PNNL and the University of Texas at El Paso are addressing computational challenges of thinking beyond the list and developing bioagent-agnostic signatures to assess threats.
PNNL is supporting the Department of Homeland Security Science and Technology Directorate's Chemical Security Analysis Center in improving capabilities to enhance detection and analysis of chemical threats.
A new report highlights the results of an assessment PNNL conducted of field-portable detection products used by first responders to detect illicit substances like fentanyl in the field.
A team of researchers from PNNL provided technical knowledge and support to test a suite of techniques that detect genetically modified bacteria, viruses, and cells.
PNNL’s ARENA test bed analyzes how electrical cables degrade in extreme environments and how nondestructive examination inspection technologies can detect and locate damage.
The ChemSpace Tool, when fully developed, is intended to divide chemical space into three subsets: the detectable space, the identifiable space, and the region that includes compounds that are not detectable or identifiable.