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.

PNNL researchers have developed a new, physics-informed machine learning model that accurately predicts how heat accumulates and dissipates during friction stir processing.

PNNL researchers have developed a new class of chemistry focused on carbon capture technology and made incremental strides in driving down costs.

Pacific Northwest marsh carbon stocks are twice the global average. Long-term sea-level rise impacts will likely decrease ecosystem carbon stocks.