Low-cost Earth-abundant Na-ion Storage (LENS) Consortium
LENSIn late 2024, the U.S. Department of Energy (DOE) awarded $50 million over the next five years to establish the Low-cost Earth-abundant Na-ion Storage (LENS) Consortium. LENS, funded by the DOE Vehicle Technologies Office, aims to discover, develop, and demonstrate a new class of sodium-ion batteries (NIBs). These NIBs will be designed to match or surpass the specific energy and energy density of current graphite/lithium iron phosphate (LFP) batteries, while also having a long life and low cost. The Consortium’s goal is to minimize — and ultimately eliminate — reliance on critical elements. To achieve this goal, LENS will develop a comprehensive understanding of the challenges encountered in current NIB materials — including the role of the electrode, electrolyte, interfaces, inactive materials, and interactions at the device — enabling researchers to design a new generation of batteries that alleviate current performance limitations.
LENS has assembled a world-class team from the following national laboratories and universities:
National Laboratories
- Argonne National Laboratory
- Brookhaven National Laboratory
- Lawrence Berkeley National Laboratory
- Pacific Northwest National Laboratory
- Sandia National Laboratory
- SLAC National Accelerator Laboratory
Universities
- Florida State University
- University of California San Diego
- University of Houston
- University of Illinois Chicago
- University of Maryland
- University of Rhode Island
- University of Wisconsin–Madison
- Virginia Tech
The LENS team collectively possesses decades of experience studying and developing novel materials for sodium-ion batteries (NIBs). Each member has been carefully chosen to fill a critical need to ensure rapid improvement to NIB technology. The team brings expertise in new material discovery, controlled synthesis, cost-effective scale-up, reproducible cell assembly from coin to 2-Ah pouch cells, comprehensive cell design and testing, multimodal characterization, technoeconomic analysis (TEA), and modeling across scales.

